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patchy631--ai-engineering-hub/art_mcp_rl/mcp_rl.ipynb
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2026-07-13 12:37:47 +08:00

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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"🦥 Unsloth: Will patch your computer to enable 2x faster free finetuning.\n",
"🦥 Unsloth Zoo will now patch everything to make training faster!\n"
]
}
],
"source": [
"import os\n",
"import unsloth\n",
"\n",
"os.environ[\"UNSLOTH_FORCE_FLOAT16\"] = \"1\""
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "caZYLROd8xnV"
},
"source": [
"To teach a model to use your MCP server, click **Runtime** > **Run all**. Make sure you've enabled a free Tesla T4 GPU and edit the [configuration](#configuration) cell below!\n",
"\n",
"<div class=\"align-center\">\n",
"<a href=\"https://github.com/openpipe/art\"><img src=\"https://github.com/openpipe/art/raw/main/assets/ART_pill.png\" height=\"50\"></a>\n",
"<a href=\"https://discord.gg/zbBHRUpwf4\"><img src=\"https://github.com/openpipe/art/raw/main/assets/Discord.png\" height=\"50\"></a>\n",
"<a href=\"https://art.openpipe.ai\"><img src=\"https://github.com/openpipe/art/raw/main/assets/Documentation_pill.png\" height=\"50\"></a>\n",
"\n",
"Questions? Join the Discord and ask away! For feature requests or to leave a star, visit our [GitHub](https://github.com/openpipe/art).\n",
"\n",
"</div>\n",
"\n",
"<a href=\"https://art.openpipe.ai/\"><img src=\"https://github.com/openpipe/art/raw/main/assets/Header_separator.png\" height=\"5\"></a>\n",
"\n",
"**MCP•RL: Teach you agent how to use any MCP server**\n",
"\n",
"This notebook shows how to train a Qwen 2.5 3B model to effectively use any MCP server. Simply provide an MCP server url and the notebook will:\n",
"\n",
"1. Query the server's tools\n",
"2. Generate a set of input tasks that use those tools\n",
"3. Train the model on those tasks using automatic RULER evaluation\n",
"4. Test the trained model by giving it new tasks to complete\n",
"\n",
"RULER judges response quality purely from the agent's final output - no labeled data required!\n",
"\n",
"*Note: In this notebook we use local MCP servers, but the technique below applies to all MCP servers!*\n"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"cellView": "form",
"id": "OsrwCDQ5cviC"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[2mUsing Python 3.12.11 environment at: /home/zeus/miniconda3/envs/cloudspace\u001b[0m\n",
"\u001b[2mAudited \u001b[1m5 packages\u001b[0m \u001b[2min 105ms\u001b[0m\u001b[0m\n"
]
}
],
"source": [
"# @title 💿 Installation\n",
"# Portions adapted from Unsloth Notebooks (https://github.com/unslothai/notebooks)\n",
"# Copyright (c) Unsloth contributors.\n",
"# License: GNU LGPL v3.0.\n",
"# Modifications by OpenPipe:\n",
"# - switched to uv\n",
"# - changed vllm/triton pinning logic\n",
"# - added protobuf pins\n",
"# - adjusted syntax for pushing to HF\n",
"# See /licenses/LGPL-3.0.txt and /licenses/GPL-3.0.txt for full text.\n",
"\n",
"import os\n",
"\n",
"if \"COLAB_\" not in \"\".join(os.environ.keys()):\n",
" !uv pip install \"openpipe-art[backend]==0.5.9\" tenacity \"mcp>=1.11.0\" \"gql<4\" aiohttp --prerelease allow --no-cache-dir\n",
"else:\n",
" try:\n",
" import numpy\n",
"\n",
" get_numpy = f\"numpy=={numpy.__version__}\"\n",
" except:\n",
" get_numpy = \"numpy\"\n",
" try:\n",
" import subprocess\n",
"\n",
" is_t4 = \"Tesla T4\" in str(subprocess.check_output([\"nvidia-smi\"]))\n",
" except:\n",
" is_t4 = False\n",
" get_vllm, get_triton = (\n",
" (\"vllm==0.9.2\", \"triton==3.2.0\") if is_t4 else (\"vllm\", \"triton\")\n",
" )\n",
" !uv pip install --upgrade \\\n",
" openpipe-art[backend]==0.4.11 tenacity pillow==11.3.0 protobuf==5.29.5 {get_vllm} {get_numpy} --prerelease allow --no-cache-dir\n",
" !uv pip install -qqq {get_triton}"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## MCP server "
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"!uv pip install fastmcp --quiet"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Popen: returncode: None args: ['python', 'mcp_server.py']>"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"\n",
"\u001b[2m╭──────────────────────────────────────────────────────────────────────────────╮\u001b[0m\n",
"\u001b[2m│\u001b[0m \u001b[2m│\u001b[0m\n",
"\u001b[2m│\u001b[0m \u001b[2m│\u001b[0m\n",
"\u001b[2m│\u001b[0m \u001b[36m \u001b[0m\u001b[36m▄\u001b[0m\u001b[36m▀\u001b[0m\u001b[36m▀\u001b[0m\u001b[36m \u001b[0m\u001b[36m▄\u001b[0m\u001b[36m▀\u001b[0m\u001b[36m█\u001b[0m\u001b[36m \u001b[0m\u001b[36m█\u001b[0m\u001b[36m▀\u001b[0m\u001b[36m▀\u001b[0m\u001b[36m \u001b[0m\u001b[36m▀\u001b[0m\u001b[36m█\u001b[0m\u001b[36m▀\u001b[0m\u001b[36m \u001b[0m\u001b[36m█\u001b[0m\u001b[36m▀\u001b[0m\u001b[36m▄\u001b[0m\u001b[36m▀\u001b[0m\u001b[36m█\u001b[0m\u001b[94m \u001b[0m\u001b[94m█\u001b[0m\u001b[94m▀\u001b[0m\u001b[94m▀\u001b[0m\u001b[94m \u001b[0m\u001b[94m█\u001b[0m\u001b[94m▀\u001b[0m\u001b[94m█\u001b[0m \u001b[2m│\u001b[0m\n",
"\u001b[2m│\u001b[0m \u001b[36m \u001b[0m\u001b[36m█\u001b[0m\u001b[36m▀\u001b[0m\u001b[36m \u001b[0m\u001b[36m \u001b[0m\u001b[36m█\u001b[0m\u001b[36m▀\u001b[0m\u001b[36m█\u001b[0m\u001b[36m \u001b[0m\u001b[36m▄\u001b[0m\u001b[36m▄\u001b[0m\u001b[36m█\u001b[0m\u001b[36m \u001b[0m\u001b[36m \u001b[0m\u001b[36m█\u001b[0m\u001b[36m \u001b[0m\u001b[36m \u001b[0m\u001b[36m█\u001b[0m\u001b[36m \u001b[0m\u001b[36m▀\u001b[0m\u001b[36m \u001b[0m\u001b[36m█\u001b[0m\u001b[94m \u001b[0m\u001b[94m█\u001b[0m\u001b[94m▄\u001b[0m\u001b[94m▄\u001b[0m\u001b[94m \u001b[0m\u001b[94m█\u001b[0m\u001b[94m▀\u001b[0m\u001b[94m▀\u001b[0m \u001b[2m│\u001b[0m\n",
"\u001b[2m│\u001b[0m \u001b[2m│\u001b[0m\n",
"\u001b[2m│\u001b[0m \u001b[2m│\u001b[0m\n",
"\u001b[2m│\u001b[0m \u001b[1;34mFastMCP 2.14.5\u001b[0m \u001b[2m│\u001b[0m\n",
"\u001b[2m│\u001b[0m \u001b[2mhttps://gofastmcp.com\u001b[0m \u001b[2m│\u001b[0m\n",
"\u001b[2m│\u001b[0m \u001b[2m│\u001b[0m\n",
"\u001b[2m│\u001b[0m \u001b[1m🖥 \u001b[0m\u001b[1m \u001b[0m\u001b[36mServer: \u001b[0m\u001b[36m \u001b[0m\u001b[2mcompany-db \u001b[0m \u001b[2m│\u001b[0m\n",
"\u001b[2m│\u001b[0m \u001b[1m🚀\u001b[0m\u001b[1m \u001b[0m\u001b[36mDeploy free:\u001b[0m\u001b[36m \u001b[0m\u001b[2mhttps://fastmcp.cloud\u001b[0m \u001b[2m│\u001b[0m\n",
"\u001b[2m│\u001b[0m \u001b[2m│\u001b[0m\n",
"\u001b[2m╰──────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n",
"\u001b[34m╭──────────────────────────────────────────────────────────────────────────────╮\u001b[0m\n",
"\u001b[34m│\u001b[0m \u001b[1m✨ FastMCP 3.0 is coming!\u001b[0m \u001b[34m│\u001b[0m\n",
"\u001b[34m│\u001b[0m \u001b[2mPin \u001b[0m\u001b[1;2m`fastmcp < 3`\u001b[0m\u001b[2m in production, then upgrade when you're ready.\u001b[0m \u001b[34m│\u001b[0m\n",
"\u001b[34m╰─────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n",
"\n",
"\n",
"\u001b[2;36m[02/16/26 18:44:53]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO \u001b[0m Starting MCP server \u001b[32m'company-db'\u001b[0m \u001b]8;id=214165;file:///home/zeus/miniconda3/envs/cloudspace/lib/python3.12/site-packages/fastmcp/server/server.py\u001b\\\u001b[2mserver.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=10307;file:///home/zeus/miniconda3/envs/cloudspace/lib/python3.12/site-packages/fastmcp/server/server.py#2580\u001b\\\u001b[2m2580\u001b[0m\u001b]8;;\u001b\\\n",
"\u001b[2;36m \u001b[0m with transport \u001b[32m'streamable-http'\u001b[0m on \u001b[2m \u001b[0m\n",
"\u001b[2;36m \u001b[0m \u001b[4;94mhttp://0.0.0.0:8903/mcp\u001b[0m \u001b[2m \u001b[0m\n",
"INFO: Started server process [77672]\n",
"INFO: Waiting for application startup.\n",
"INFO: Application startup complete.\n",
"INFO: Uvicorn running on http://0.0.0.0:8903 (Press CTRL+C to quit)\n"
]
}
],
"source": [
"import subprocess\n",
"subprocess.Popen([\"python\", \"mcp_server.py\"])"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "D8b8kgQ69ZDM"
},
"source": [
"<a name=\"configuration\"></a>\n",
"\n",
"### 🎯 Configuration - Edit These Settings\n",
"\n",
"Add an OpenRouter API key and MCP server url below."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"id": "so6r1_OG9en3"
},
"outputs": [],
"source": [
"# Required - Used for generating training inputs and RULER evaluation\n",
"OPENROUTER_API_KEY = \"\" # Put your OpenRouter key here\n",
"\n",
"# 🔌 Point to any MCP server\n",
"MCP_SERVER_URL = \"http://0.0.0.0:8903/mcp\"\n",
"\n",
"# Optional - Enables metric logging\n",
"WANDB_API_KEY = \"\"\n",
"\n",
"# Choose the base model to train\n",
"BASE_MODEL = \"Qwen/Qwen2.5-3B-Instruct\" # Options: \"Qwen/Qwen2.5-3B-Instruct\", \"Qwen/Qwen2.5-7B-Instruct\", etc."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"cellView": "form",
"id": "I_AFDSOv_LrB"
},
"outputs": [],
"source": [
"# @title Advanced Settings\n",
"\n",
"# Model configuration\n",
"MODEL_NAME = \"sql-agent-3b\" # Name for your trained model\n",
"PROJECT_NAME = \"mcp-rl\" # Project name for tracking\n",
"\n",
"# Training configuration\n",
"TRAINING_CONFIG = {\n",
" \"num_training_inputs\": 16, # Number of training inputs to generate\n",
" \"groups_per_step\": 2, # Inputs to process per training step\n",
" \"num_epochs\": 1, # Number of times through all data\n",
" \"rollouts_per_group\": 4, # Different responses per input (for RULER comparison)\n",
" \"learning_rate\": 1e-5, # Learning rate\n",
" \"max_training_steps\": None, # Maximum training steps (set to None for no limit)\n",
"}\n",
"\n",
"MAX_TURNS = 10 # Maximum number of turns for the model to generate during one rollout\n",
"\n",
"NUM_TEST_INPUTS = 8 # Number of test inputs to generate\n",
"RULER_MODEL = \"openrouter/openai/gpt-4o-mini\" # Model for RULER evaluation\n",
"INPUT_GENERATION_MODEL = \"openai/gpt-5-nano\"\n",
"\n",
"# Colab/T4 specific config to avoid OOM errors\n",
"MAX_TURNS = 3 # Decrease the number of turns to avoid OOM errors on a T4\n",
"MAX_SEQ_LENGTH = 16384 # Maximum sequence length\n",
"GPU_MEMORY_UTILIZATION = 0.8 # GPU memory usage (0.0-1.0)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"cellView": "form",
"id": "PfXGRuhhd7hr"
},
"outputs": [],
"source": [
"# @title Debug utilities\n",
"\n",
"import json\n",
"import time\n",
"import traceback\n",
"from typing import Any\n",
"\n",
"DEBUG_LOG = True # flip to False to silence logs\n",
"LOG_JSON_MAX = 2000 # cap large JSON prints\n",
"\n",
"\n",
"def _ts() -> str:\n",
" return time.strftime(\"%H:%M:%S\")\n",
"\n",
"\n",
"def log(msg: str, **kv):\n",
" if not DEBUG_LOG:\n",
" return\n",
" parts = [f\"[{_ts()}] {msg}\"]\n",
" if kv:\n",
" kv_str = \" \".join(f\"{k}={repr(v)}\" for k, v in kv.items())\n",
" parts.append(\"| \" + kv_str)\n",
" print(\" \".join(parts))\n",
"\n",
"\n",
"def log_json(title: str, payload: Any, max_len: int = LOG_JSON_MAX):\n",
" if not DEBUG_LOG:\n",
" return\n",
" try:\n",
" s = json.dumps(payload, indent=2, default=str)\n",
" except Exception:\n",
" s = str(payload)\n",
" if len(s) > max_len:\n",
" s = s[:max_len] + \"\\n... (truncated)\"\n",
" print(f\"[{_ts()}] {title}:\\n{s}\")"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"cellView": "form",
"id": "gxUn4E_IPjq8"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"INFO: 127.0.0.1:50804 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"INFO: 127.0.0.1:50810 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"INFO: 127.0.0.1:50818 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"INFO: 127.0.0.1:50826 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"INFO: 127.0.0.1:50840 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"INFO: 127.0.0.1:50854 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"Tools: ['list_tables', 'describe_table', 'run_query']\n",
"Resources: []\n"
]
}
],
"source": [
"# @title 🔌 MCP helpers\n",
"\n",
"from contextlib import asynccontextmanager\n",
"\n",
"import mcp.types as types\n",
"from mcp.client.session import ClientSession\n",
"from mcp.client.streamable_http import streamable_http_client\n",
"\n",
"\n",
"@asynccontextmanager\n",
"async def mcp_session():\n",
" \"\"\"\n",
" Connects to the remote Smithery MCP server using the full URL that includes\n",
" your API key & profile. No OAuth provider is used.\n",
" \"\"\"\n",
" async with streamable_http_client(MCP_SERVER_URL) as (read, write, _):\n",
" async with ClientSession(read, write) as session:\n",
" await session.initialize()\n",
" yield session\n",
"\n",
"\n",
"async def list_tools_and_resources():\n",
" \"\"\"Return (tools_result, resources_result) from the remote Smithery server.\"\"\"\n",
" async with mcp_session() as session:\n",
" tools = await session.list_tools()\n",
" try:\n",
" resources = await session.list_resources()\n",
" except Exception:\n",
" # Some servers don't implement resources; keep interface stable\n",
" class _Empty:\n",
" resources = []\n",
"\n",
" resources = _Empty()\n",
" return tools, resources\n",
"\n",
"\n",
"async def call_mcp_tool(tool_name: str, arguments: dict):\n",
" \"\"\"Invoke a tool on the remote Smithery server and return the CallToolResult.\"\"\"\n",
" async with mcp_session() as session:\n",
" return await session.call_tool(tool_name, arguments)\n",
"\n",
"\n",
"tools, resources = await list_tools_and_resources()\n",
"print(\"Tools:\", [t.name for t in tools.tools])\n",
"print(\n",
" \"Resources:\",\n",
" [getattr(r, \"uri\", None) for r in getattr(resources, \"resources\", []) or []],\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Mon Feb 16 18:45:24 2026 \n",
"+-----------------------------------------------------------------------------------------+\n",
"| NVIDIA-SMI 570.211.01 Driver Version: 570.211.01 CUDA Version: 12.8 |\n",
"|-----------------------------------------+------------------------+----------------------+\n",
"| GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC |\n",
"| Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. |\n",
"| | | MIG M. |\n",
"|=========================================+========================+======================|\n",
"| 0 Tesla T4 Off | 00000000:00:05.0 Off | 0 |\n",
"| N/A 47C P0 26W / 70W | 363MiB / 15360MiB | 0% Default |\n",
"| | | N/A |\n",
"+-----------------------------------------+------------------------+----------------------+\n",
" \n",
"+-----------------------------------------------------------------------------------------+\n",
"| Processes: |\n",
"| GPU GI CI PID Type Process name GPU Memory |\n",
"| ID ID Usage |\n",
"|=========================================================================================|\n",
"+-----------------------------------------------------------------------------------------+\n"
]
}
],
"source": [
"!nvidia-smi"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"def get_content_text(result) -> str:\n",
" # Extract text content from tool call result per MCP content schema\n",
" if isinstance(result, str):\n",
" return result\n",
" if hasattr(result, \"content\") and result.content:\n",
" out = \"\"\n",
" for item in result.content:\n",
" if isinstance(item, types.TextContent):\n",
" out += item.text\n",
" else:\n",
" out += str(item)\n",
" return out\n",
" if hasattr(result, \"structured\") and result.structured is not None:\n",
" try:\n",
" return json.dumps(result.structured)\n",
" except Exception:\n",
" return str(result.structured)\n",
" return str(result)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"cellView": "form",
"id": "nEB1JGY6Pjq8"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[18:45:34] \u001b[32mOK\u001b[0m OPENROUTER_API_KEY found.\n",
"INFO: 127.0.0.1:50000 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"INFO: 127.0.0.1:50016 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"INFO: 127.0.0.1:50026 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"INFO: 127.0.0.1:50040 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"INFO: 127.0.0.1:50042 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"INFO: 127.0.0.1:50058 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"INFO: 127.0.0.1:50064 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"INFO: 127.0.0.1:50070 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"INFO: 127.0.0.1:50084 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"INFO: 127.0.0.1:50088 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"INFO: 127.0.0.1:50104 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"INFO: 127.0.0.1:50110 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"INFO: 127.0.0.1:50112 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"INFO: 127.0.0.1:50128 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"INFO: 127.0.0.1:50144 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"INFO: 127.0.0.1:50150 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"INFO: 127.0.0.1:50158 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"INFO: 127.0.0.1:50168 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"INFO: 127.0.0.1:50184 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"INFO: 127.0.0.1:50190 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"INFO: 127.0.0.1:50204 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"INFO: 127.0.0.1:50210 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"INFO: 127.0.0.1:50222 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"INFO: 127.0.0.1:50238 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"INFO: 127.0.0.1:50240 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"INFO: 127.0.0.1:50244 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"INFO: 127.0.0.1:50248 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"INFO: 127.0.0.1:50256 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"INFO: 127.0.0.1:50264 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"INFO: 127.0.0.1:50276 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"INFO: 127.0.0.1:50290 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"INFO: 127.0.0.1:50306 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"INFO: 127.0.0.1:50308 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"INFO: 127.0.0.1:50322 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"INFO: 127.0.0.1:50338 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"INFO: 127.0.0.1:50348 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"INFO: 127.0.0.1:50362 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"INFO: 127.0.0.1:50366 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"INFO: 127.0.0.1:50378 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"INFO: 127.0.0.1:50382 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"INFO: 127.0.0.1:50386 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"INFO: 127.0.0.1:50400 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"[18:45:35] \u001b[34mINFO\u001b[0m Target total scenarios: 24\n",
"[18:45:35] \u001b[36mSTEP\u001b[0m Attempt 1/10 ...\n",
"[18:45:35] \u001b[32mOK\u001b[0m Using model: openai/gpt-5-nano\n",
"[18:45:35] \u001b[34mINFO\u001b[0m Available: 3 tool(s), 0 resource(s).\n",
"[18:45:35] \u001b[36mSTEP\u001b[0m Preparing prompt & JSON schema &\n",
"[18:45:35] \u001b[36mSTEP\u001b[0m Calling model: \u001b[1mopenai/gpt-5-nano\u001b[0m &\n",
"[18:46:20] \u001b[32mOK\u001b[0m Model responded in 44.96s.\n",
"[18:46:20] \u001b[34mINFO\u001b[0m Raw content length: 4235 chars.\n",
"[18:46:20] \u001b[32mOK\u001b[0m Parsed 24 scenario(s) successfully.\n",
"[18:46:20] \u001b[34mINFO\u001b[0m Difficulty distribution:\n",
"\u001b[2m 1/5: 1 █\u001b[0m\n",
"\u001b[2m 2/5: 6 ██████\u001b[0m\n",
"\u001b[2m 3/5: 11 ███████████\u001b[0m\n",
"\u001b[2m 4/5: 5 █████\u001b[0m\n",
"\u001b[2m 5/5: 1 █\u001b[0m\n",
"[18:46:20] \u001b[32mOK\u001b[0m Generated 24 scenarios in 44.97s total.\n",
"[18:46:20] \u001b[32mOK\u001b[0m Attempt 1 succeeded in 44.97s.\n",
"[18:46:20] \u001b[32mOK\u001b[0m Generated 24 scenarios total.\n",
"[18:46:20] \u001b[36mSTEP\u001b[0m Shuffling scenarios and splitting into train/val ...\n",
"[18:46:20] \u001b[32mOK\u001b[0m Train: 16 | Val: 8\n",
"[18:46:20] \u001b[34mINFO\u001b[0m Sample (train) preview:\n",
"\u001b[2m 1. List the top three earners and show their names, salaries, and department names. Then provide a summary and thorough ana& \u001b[90m(difficulty 3/5)\u001b[0m\u001b[0m\n",
"\u001b[2m 2. Identify departments that have no employees assigned. Then provide a summary and thorough analysis/report. \u001b[90m(difficulty 3/5)\u001b[0m\u001b[0m\n",
"\u001b[2m 3. For each department, present location, budget, and the number of employees in that department. Then provide a summary an& \u001b[90m(difficulty 4/5)\u001b[0m\u001b[0m\n",
"\u001b[2m 4. In the Marketing department, count hires after 2020 and report the average salary of those hires. Then generate a summar& \u001b[90m(difficulty 2/5)\u001b[0m\u001b[0m\n",
"\u001b[2m 5. Find the most senior engineer (earliest hire_date) and show their name, role, and hire date. Then produce a summary and& \u001b[90m(difficulty 2/5)\u001b[0m\u001b[0m\n",
"[18:46:20] \u001b[34mINFO\u001b[0m Sample (val) preview:\n",
"\u001b[2m 1. For every department, show its budget, the total budget allocated to its projects, and the remaining budget (budget minu& \u001b[90m(difficulty 4/5)\u001b[0m\u001b[0m\n",
"\u001b[2m 2. Determine which department has the most active projects. Then provide a summary and thorough analysis/report. \u001b[90m(difficulty 4/5)\u001b[0m\u001b[0m\n",
"\u001b[2m 3. Determine the most common job role among all employees. Then provide a summary and thorough analysis/report. \u001b[90m(difficulty 3/5)\u001b[0m\u001b[0m\n",
"\u001b[2m 4. Identify which department has the highest budget and report its name and location. Then produce a summary and thorough a& \u001b[90m(difficulty 2/5)\u001b[0m\u001b[0m\n",
"\u001b[2m 5. Produce a report of all projects including the project lead's name and the department name they belong to. Then provide& \u001b[90m(difficulty 3/5)\u001b[0m\u001b[0m\n",
"[18:46:20] \u001b[32mOK\u001b[0m Done.\n"
]
}
],
"source": [
"# @title Let's generate our train and validation scenarios!\n",
"\n",
"import os\n",
"import random\n",
"\n",
"from dotenv import load_dotenv\n",
"\n",
"# Import the generate_scenarios function from art.mcp and logging utilities\n",
"from art.mcp import generate_scenarios\n",
"from art.mcp.generate_scenarios import preview_scenarios\n",
"from art.utils.logging import info, ok, step, warn, err\n",
"\n",
"load_dotenv()\n",
"\n",
"# required env/key check\n",
"# If OPENROUTER_API_KEY exists as a var, use it; otherwise pull from env\n",
"_openrouter_key = os.getenv(\"OPENROUTER_API_KEY\")\n",
"try:\n",
" _openrouter_key = _openrouter_key if _openrouter_key else OPENROUTER_API_KEY # noqa: F821 (defined upstream in your notebook)\n",
"except NameError:\n",
" pass\n",
"\n",
"if _openrouter_key:\n",
" os.environ[\"OPENROUTER_API_KEY\"] = _openrouter_key\n",
" ok(\"OPENROUTER_API_KEY found.\")\n",
"else:\n",
" err(\"OPENROUTER_API_KEY is required for data generation and RULER evaluation.\")\n",
" raise ValueError(\n",
" \"OPENROUTER_API_KEY is required for data generation and RULER evaluation.\"\n",
" )\n",
"\n",
"# Convert MCP tools and resources to the expected format\n",
"tools_result, resources_result = await list_tools_and_resources()\n",
"\n",
"# Convert tools to the format expected by generate_scenarios\n",
"tools_list = []\n",
"for tool in tools_result.tools or []:\n",
" tools_list.append({\n",
" \"name\": tool.name,\n",
" \"description\": tool.description,\n",
" \"parameters\": tool.inputSchema,\n",
" })\n",
"\n",
"# Convert resources to the format expected by generate_scenarios\n",
"resources_list = []\n",
"for resource in getattr(resources_result, \"resources\", []) or []:\n",
" resources_list.append({\n",
" \"uri\": str(resource.uri),\n",
" \"name\": resource.name,\n",
" \"description\": resource.description,\n",
" \"mimeType\": resource.mimeType,\n",
" })\n",
"\n",
"# First, get the actual schema from your database\n",
"schema_info = \"\"\n",
"for table in [\"departments\", \"employees\", \"projects\"]:\n",
" result = await call_mcp_tool(\"describe_table\", {\"table_name\": table})\n",
" schema_info += f\"\\nTable '{table}': {get_content_text(result)}\"\n",
"\n",
"# Sample a few rows so the generator knows what kind of data exists\n",
"for table in [\"departments\", \"employees\", \"projects\"]:\n",
" result = await call_mcp_tool(\"run_query\", {\"sql\": f\"SELECT * FROM {table} LIMIT 3\"})\n",
" schema_info += f\"\\nSample data from '{table}': {get_content_text(result)}\"\n",
"\n",
"# Now enrich the tool descriptions with this context\n",
"enriched_tools_list = []\n",
"for tool in tools_list:\n",
" enriched = tool.copy()\n",
" if tool[\"name\"] == \"run_query\":\n",
" enriched[\"description\"] = (\n",
" tool[\"description\"] +\n",
" f\"\\n\\nAvailable database schema:{schema_info}\"\n",
" )\n",
" enriched_tools_list.append(enriched)\n",
"\n",
"\n",
"# Calculate total scenarios needed\n",
"try:\n",
" expected_total = TRAINING_CONFIG[\"num_training_inputs\"] + NUM_TEST_INPUTS # noqa: F821\n",
"except NameError:\n",
" err(\"TRAINING_CONFIG/NUM_TEST_INPUTS not defined in this notebook.\")\n",
" raise\n",
"\n",
"info(f\"Target total scenarios: {expected_total}\")\n",
"\n",
"# Generate scenarios using the art.mcp function\n",
"max_attempts = 10\n",
"scenarios = None\n",
"\n",
"for attempt in range(1, max_attempts + 1):\n",
" step(f\"Attempt {attempt}/{max_attempts} ...\")\n",
" t_attempt = time.perf_counter()\n",
" try:\n",
" scenario_collection = await generate_scenarios(\n",
" tools=enriched_tools_list,\n",
" resources=resources_list,\n",
" num_scenarios=expected_total,\n",
" show_preview=False, # We'll preview separately for train/val\n",
" generator_model=INPUT_GENERATION_MODEL,\n",
" generator_api_key=_openrouter_key,\n",
" )\n",
" # Convert GeneratedScenarioCollection to list of dicts for compatibility\n",
" scenarios = [{\"task\": s.task, \"difficulty\": s.difficulty} for s in scenario_collection.scenarios]\n",
" ok(f\"Attempt {attempt} succeeded in {time.perf_counter() - t_attempt:.2f}s.\")\n",
" break\n",
" except Exception as e:\n",
" warn(f\"Attempt {attempt} failed: {e}\")\n",
" if attempt < max_attempts:\n",
" time.sleep(min(1.5 * attempt, 6.0))\n",
" else:\n",
" err(\"All attempts exhausted.\")\n",
" raise\n",
"\n",
"# Split into train/val\n",
"ok(f\"Generated {len(scenarios)} scenarios total.\")\n",
"step(\"Shuffling scenarios and splitting into train/val ...\")\n",
"random.shuffle(scenarios)\n",
"\n",
"train_n = TRAINING_CONFIG[\"num_training_inputs\"] # noqa: F821\n",
"raw_train_scenarios = scenarios[:train_n]\n",
"raw_val_scenarios = scenarios[train_n:]\n",
"\n",
"ok(f\"Train: {len(raw_train_scenarios)} | Val: {len(raw_val_scenarios)}\")\n",
"\n",
"info(\"Sample (train) preview:\")\n",
"preview_scenarios(raw_train_scenarios, n=min(5, len(raw_train_scenarios)))\n",
"\n",
"info(\"Sample (val) preview:\")\n",
"preview_scenarios(raw_val_scenarios, n=min(5, len(raw_val_scenarios)))\n",
"\n",
"ok(\"Done.\")"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[{'task': 'List the top three earners and show their names, salaries, and department names. Then provide a summary and thorough analysis/report.',\n",
" 'difficulty': 3},\n",
" {'task': 'Identify departments that have no employees assigned. Then provide a summary and thorough analysis/report.',\n",
" 'difficulty': 3},\n",
" {'task': 'For each department, present location, budget, and the number of employees in that department. Then provide a summary and thorough analysis/report.',\n",
" 'difficulty': 4},\n",
" {'task': 'In the Marketing department, count hires after 2020 and report the average salary of those hires. Then generate a summary and a thorough report.',\n",
" 'difficulty': 2},\n",
" {'task': 'Find the most senior engineer (earliest hire_date) and show their name, role, and hire date. Then produce a summary and thorough analysis/report.',\n",
" 'difficulty': 2},\n",
" {'task': 'Compute for each department its headcount and total payroll (sum of salaries). Then generate a summary and a thorough analysis/report.',\n",
" 'difficulty': 3},\n",
" {'task': 'Compare salaries in the Engineering department to the overall average salary, listing any employees who earn above the overall average. Then deliver a summary and a thorough results report.',\n",
" 'difficulty': 3},\n",
" {'task': 'List all tables in the database and then generate a summary of what was found, perform a basic data-usage analysis, and produce a final report of the results.',\n",
" 'difficulty': 1},\n",
" {'task': 'Calculate the total budget across all departments and the average department budget. Then provide a summary and a thorough report of the results.',\n",
" 'difficulty': 2},\n",
" {'task': 'List employees who are listed as project leads (lead_id in projects) along with the project(s) they lead. Then provide a summary and thorough analysis/report.',\n",
" 'difficulty': 3},\n",
" {'task': 'Create a combined report of active projects per department, including the department budget. Then provide a summary and thorough analysis/report.',\n",
" 'difficulty': 3},\n",
" {'task': 'List employees whose salary exceeds the average salary for their own department. Then provide a summary and thorough analysis/report.',\n",
" 'difficulty': 4},\n",
" {'task': \"Produce a distribution of active projects by department (count per department with status 'active'). Then deliver a summary and a thorough report.\",\n",
" 'difficulty': 3},\n",
" {'task': 'Describe the departments table (column names, data types, and constraints) and provide a concise interpretation of how the table supports budget planning. Then generate a summary and thorough analysis/report of the results.',\n",
" 'difficulty': 2},\n",
" {'task': 'List all employees with their department name, including those without an assigned department. Then provide a summary and thorough analysis/report.',\n",
" 'difficulty': 2},\n",
" {'task': 'Compute the number of hires per calendar year and present a year-by-year trend. Then provide a summary and thorough analysis/report.',\n",
" 'difficulty': 3}]"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"raw_train_scenarios"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[{'task': 'For every department, show its budget, the total budget allocated to its projects, and the remaining budget (budget minus project budgets). Then provide a summary and a thorough analysis/report.',\n",
" 'difficulty': 4},\n",
" {'task': 'Determine which department has the most active projects. Then provide a summary and thorough analysis/report.',\n",
" 'difficulty': 4},\n",
" {'task': 'Determine the most common job role among all employees. Then provide a summary and thorough analysis/report.',\n",
" 'difficulty': 3},\n",
" {'task': 'Identify which department has the highest budget and report its name and location. Then produce a summary and thorough analysis/report.',\n",
" 'difficulty': 2},\n",
" {'task': \"Produce a report of all projects including the project lead's name and the department name they belong to. Then provide a summary and thorough analysis/report.\",\n",
" 'difficulty': 3},\n",
" {'task': 'For every department, calculate budget minus total salaries of employees in that department (budget variance). Then provide a summary and thorough analysis/report.',\n",
" 'difficulty': 3},\n",
" {'task': 'For each department, show budget, total salaries, and the difference (budget minus salaries). Then provide a summary and thorough analysis/report.',\n",
" 'difficulty': 4},\n",
" {'task': 'Simulate a 10% budget cut per department and identify which departments would still cover salaries, plus overall impact; then provide a summary and thorough analysis/report.',\n",
" 'difficulty': 5}]"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"raw_val_scenarios"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Register model with the server"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"WANDB_API_KEY is not set. We'll skip logging metrics to Weights & Biases.\n",
"==((====))== Unsloth 2025.12.9: Fast Qwen2 patching. Transformers: 4.57.3. vLLM: 0.13.0.\n",
" \\\\ /| Tesla T4. Num GPUs = 1. Max memory: 14.741 GB. Platform: Linux.\n",
"O^O/ \\_/ \\ Torch: 2.9.0+cu128. CUDA: 7.5. CUDA Toolkit: 12.8. Triton: 3.5.0\n",
"\\ / Bfloat16 = FALSE. FA [Xformers = 0.0.33.post1. FA2 = False]\n",
" \"-____-\" Free license: http://github.com/unslothai/unsloth\n",
"Unsloth: Fast downloading is enabled - ignore downloading bars which are red colored!\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Unsloth 2025.12.9 patched 36 layers with 36 QKV layers, 36 O layers and 36 MLP layers.\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[33m⚠️ Warning: 'huggingface-cli download' is deprecated. Use 'hf download' instead.\u001b[0m\n",
"/teamspace/studios/this_studio/.cache/huggingface/hub/models--Qwen--Qwen2.5-3B-Instruct/snapshots/aa8e72537993ba99e69dfaafa59ed015b17504d1\n",
"INFO 02-16 18:47:25 [model.py:514] Resolved architecture: Qwen2ForCausalLM\n",
"WARNING 02-16 18:47:25 [model.py:1955] Your device 'Tesla T4' (with compute capability 7.5) doesn't support torch.bfloat16. Falling back to torch.float16 for compatibility.\n",
"WARNING 02-16 18:47:25 [model.py:2005] Casting torch.bfloat16 to torch.float16.\n",
"INFO 02-16 18:47:25 [model.py:1661] Using max model len 32768\n",
"INFO 02-16 18:47:25 [scheduler.py:230] Chunked prefill is enabled with max_num_batched_tokens=2048.\n",
"WARNING 02-16 18:47:25 [vllm.py:622] Enforce eager set, overriding optimization level to -O0\n",
"INFO 02-16 18:47:25 [vllm.py:722] Cudagraph is disabled under eager mode\n",
"WARNING 02-16 18:47:27 [system_utils.py:136] We must use the `spawn` multiprocessing start method. Overriding VLLM_WORKER_MULTIPROC_METHOD to 'spawn'. See https://docs.vllm.ai/en/latest/usage/troubleshooting.html#python-multiprocessing for more information. Reasons: CUDA is initialized\n",
"\u001b[0;36m(EngineCore_DP0 pid=87084)\u001b[0;0m INFO 02-16 18:47:38 [core.py:93] Initializing a V1 LLM engine (v0.13.0) with config: model='Qwen/Qwen2.5-3B-Instruct', speculative_config=None, tokenizer='Qwen/Qwen2.5-3B-Instruct', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=False, dtype=torch.float16, max_seq_len=32768, download_dir=None, load_format=auto, tensor_parallel_size=1, pipeline_parallel_size=1, data_parallel_size=1, disable_custom_all_reduce=False, quantization=None, enforce_eager=True, kv_cache_dtype=auto, device_config=cuda, structured_outputs_config=StructuredOutputsConfig(backend='auto', disable_fallback=False, disable_any_whitespace=False, disable_additional_properties=False, reasoning_parser='', reasoning_parser_plugin='', enable_in_reasoning=False), observability_config=ObservabilityConfig(show_hidden_metrics_for_version=None, otlp_traces_endpoint=None, collect_detailed_traces=None, kv_cache_metrics=False, kv_cache_metrics_sample=0.01, cudagraph_metrics=False, enable_layerwise_nvtx_tracing=False), seed=0, served_model_name=Qwen/Qwen2.5-3B-Instruct, enable_prefix_caching=True, enable_chunked_prefill=True, pooler_config=None, compilation_config={'level': None, 'mode': <CompilationMode.NONE: 0>, 'debug_dump_path': None, 'cache_dir': '', 'compile_cache_save_format': 'binary', 'backend': 'inductor', 'custom_ops': ['all'], 'splitting_ops': [], 'compile_mm_encoder': False, 'compile_sizes': [], 'compile_ranges_split_points': [2048], 'inductor_compile_config': {'enable_auto_functionalized_v2': False, 'combo_kernels': True, 'benchmark_combo_kernel': True}, 'inductor_passes': {}, 'cudagraph_mode': <CUDAGraphMode.NONE: 0>, 'cudagraph_num_of_warmups': 0, 'cudagraph_capture_sizes': [], 'cudagraph_copy_inputs': False, 'cudagraph_specialize_lora': True, 'use_inductor_graph_partition': False, 'pass_config': {'fuse_norm_quant': False, 'fuse_act_quant': False, 'fuse_attn_quant': False, 'eliminate_noops': False, 'enable_sp': False, 'fuse_gemm_comms': False, 'fuse_allreduce_rms': False}, 'max_cudagraph_capture_size': 0, 'dynamic_shapes_config': {'type': <DynamicShapesType.BACKED: 'backed'>, 'evaluate_guards': False}, 'local_cache_dir': None}\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\u001b[0;36m(EngineCore_DP0 pid=87084)\u001b[0;0m /home/zeus/miniconda3/envs/cloudspace/lib/python3.12/site-packages/art/__init__.py:37: UserWarning: WARNING: Unsloth should be imported before [transformers] to ensure all optimizations are applied. Your code may run slower or encounter memory issues without these optimizations.\n",
"\u001b[0;36m(EngineCore_DP0 pid=87084)\u001b[0;0m \n",
"\u001b[0;36m(EngineCore_DP0 pid=87084)\u001b[0;0m Please restructure your imports with 'import unsloth' at the top of your file.\n",
"\u001b[0;36m(EngineCore_DP0 pid=87084)\u001b[0;0m import unsloth # noqa: F401\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[0;36m(EngineCore_DP0 pid=87084)\u001b[0;0m 🦥 Unsloth: Will patch your computer to enable 2x faster free finetuning.\n",
"\u001b[0;36m(EngineCore_DP0 pid=87084)\u001b[0;0m 🦥 Unsloth Zoo will now patch everything to make training faster!\n",
"\u001b[0;36m(EngineCore_DP0 pid=87084)\u001b[0;0m INFO 02-16 18:47:53 [worker_base.py:283] Injected <class 'art.vllm.engine.WorkerExtension'> into <class 'vllm.v1.worker.gpu_worker.Worker'> for extended collective_rpc calls ['run', 'time']\n",
"\u001b[0;36m(EngineCore_DP0 pid=87084)\u001b[0;0m INFO 02-16 18:47:53 [parallel_state.py:1203] world_size=1 rank=0 local_rank=0 distributed_init_method=tcp://10.128.0.201:50233 backend=nccl\n",
"\u001b[0;36m(EngineCore_DP0 pid=87084)\u001b[0;0m INFO 02-16 18:47:53 [parallel_state.py:1411] rank 0 in world size 1 is assigned as DP rank 0, PP rank 0, PCP rank 0, TP rank 0, EP rank 0\n",
"\u001b[0;36m(EngineCore_DP0 pid=87084)\u001b[0;0m INFO 02-16 18:47:54 [gpu_model_runner.py:3562] Starting to load model Qwen/Qwen2.5-3B-Instruct...\n",
"\u001b[0;36m(EngineCore_DP0 pid=87084)\u001b[0;0m INFO 02-16 18:47:55 [cuda.py:351] Using FLASHINFER attention backend out of potential backends: ('FLASHINFER', 'TRITON_ATTN', 'FLEX_ATTENTION')\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Loading safetensors checkpoint shards: 0% Completed | 0/2 [00:00<?, ?it/s]\n",
"Loading safetensors checkpoint shards: 50% Completed | 1/2 [00:03<00:03, 3.46s/it]\n",
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"\u001b[0;36m(EngineCore_DP0 pid=87084)\u001b[0;0m \n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[0;36m(EngineCore_DP0 pid=87084)\u001b[0;0m INFO 02-16 18:48:01 [default_loader.py:308] Loading weights took 5.83 seconds\n",
"\u001b[0;36m(EngineCore_DP0 pid=87084)\u001b[0;0m INFO 02-16 18:48:01 [punica_selector.py:20] Using PunicaWrapperGPU.\n",
"\u001b[0;36m(EngineCore_DP0 pid=87084)\u001b[0;0m INFO 02-16 18:48:02 [gpu_model_runner.py:3659] Model loading took 5.9169 GiB memory and 6.699443 seconds\n",
"\u001b[0;36m(EngineCore_DP0 pid=87084)\u001b[0;0m INFO 02-16 18:48:05 [gpu_worker.py:375] Available KV cache memory: 5.14 GiB\n",
"\u001b[0;36m(EngineCore_DP0 pid=87084)\u001b[0;0m INFO 02-16 18:48:05 [kv_cache_utils.py:1291] GPU KV cache size: 149,648 tokens\n",
"\u001b[0;36m(EngineCore_DP0 pid=87084)\u001b[0;0m INFO 02-16 18:48:05 [kv_cache_utils.py:1296] Maximum concurrency for 32,768 tokens per request: 4.57x\n",
"\u001b[0;36m(EngineCore_DP0 pid=87084)\u001b[0;0m INFO 02-16 18:48:05 [kernel_warmup.py:65] Warming up FlashInfer attention.\n",
"\u001b[0;36m(EngineCore_DP0 pid=87084)\u001b[0;0m INFO 02-16 18:48:08 [core.py:259] init engine (profile, create kv cache, warmup model) took 5.71 seconds\n",
"\u001b[0;36m(EngineCore_DP0 pid=87084)\u001b[0;0m WARNING 02-16 18:48:10 [vllm.py:629] Inductor compilation was disabled by user settings,Optimizations settings that are only active duringInductor compilation will be ignored.\n",
"\u001b[0;36m(EngineCore_DP0 pid=87084)\u001b[0;0m INFO 02-16 18:48:10 [vllm.py:722] Cudagraph is disabled under eager mode\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m Model created!\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m Base model: Qwen/Qwen2.5-3B-Instruct\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m Model name: sql-agent-3b\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m Project name: mcp-rl\n"
]
}
],
"source": [
"# @title Run this cell to train your model!\n",
"\n",
"import os\n",
"import random\n",
"from dataclasses import dataclass\n",
"\n",
"import weave\n",
"from dotenv import load_dotenv\n",
"from openai import AsyncOpenAI\n",
"\n",
"import art\n",
"from art.local import LocalBackend\n",
"from art.rewards import ruler_score_group\n",
"from art.utils import iterate_dataset\n",
"\n",
"load_dotenv()\n",
"\n",
"# Optional\n",
"if WANDB_API_KEY:\n",
" os.environ[\"WANDB_API_KEY\"] = WANDB_API_KEY\n",
" weave.init(PROJECT_NAME)\n",
"else:\n",
" print(\"WANDB_API_KEY is not set. We'll skip logging metrics to Weights & Biases.\")\n",
"\n",
"random.seed(42)\n",
"\n",
"# Declare the model\n",
"model = art.TrainableModel(\n",
" name=MODEL_NAME,\n",
" project=PROJECT_NAME,\n",
" base_model=BASE_MODEL,\n",
")\n",
"\n",
"# Clear GPU memory before registering\n",
"import torch, gc\n",
"gc.collect()\n",
"torch.cuda.empty_cache()\n",
"\n",
"# To run on a T4, we need to override some config defaults.\n",
"model._internal_config = art.dev.InternalModelConfig(\n",
" init_args=art.dev.InitArgs(\n",
" max_seq_length=MAX_SEQ_LENGTH,\n",
" dtype=\"float16\",\n",
" ),\n",
" engine_args=art.dev.EngineArgs(\n",
" enforce_eager=True,\n",
" gpu_memory_utilization=0.80,\n",
" ),\n",
")\n",
"\n",
"# Initialize the server\n",
"backend = LocalBackend(\n",
" in_process=True,\n",
" path=\"./.art\",\n",
")\n",
"\n",
"# Register the model with the local Backend\n",
"await model.register(backend)\n",
"\n",
"print(\"Model created!\")\n",
"print(\"Base model:\", BASE_MODEL)\n",
"print(\"Model name:\", MODEL_NAME)\n",
"print(\"Project name:\", PROJECT_NAME)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## RULER in action"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[0;36m(APIServer pid=7894)\u001b[0;0m \u001b[0;36m(APIServer pid=7894)\u001b[0;0m INFO: 127.0.0.1:50730 - \"GET /v1/models HTTP/1.1\" 404 Not Found\n",
"\u001b[0;36m(APIServer pid=7894)\u001b[0;0m \u001b[0;36m(APIServer pid=7894)\u001b[0;0m INFO: 127.0.0.1:50958 - \"GET /v1/models HTTP/1.1\" 404 Not Found\n",
"\u001b[0;36m(APIServer pid=7894)\u001b[0;0m \u001b[0;36m(APIServer pid=7894)\u001b[0;0m INFO: 127.0.0.1:50730 - \"GET /v1/models HTTP/1.1\" 404 Not Found\n",
"\u001b[0;36m(APIServer pid=7894)\u001b[0;0m \u001b[0;36m(APIServer pid=7894)\u001b[0;0m INFO: 127.0.0.1:50958 - \"GET /v1/models HTTP/1.1\" 404 Not Found\n",
"\u001b[0;36m(APIServer pid=7894)\u001b[0;0m \u001b[0;36m(APIServer pid=7894)\u001b[0;0m INFO: 127.0.0.1:50730 - \"GET /v1/models HTTP/1.1\" 404 Not Found\n",
"\u001b[0;36m(APIServer pid=7894)\u001b[0;0m \u001b[0;36m(APIServer pid=7894)\u001b[0;0m INFO: 127.0.0.1:50958 - \"GET /v1/models HTTP/1.1\" 404 Not Found\n",
"\u001b[0;36m(APIServer pid=7894)\u001b[0;0m \u001b[0;36m(APIServer pid=7894)\u001b[0;0m INFO: 127.0.0.1:50730 - \"GET /v1/models HTTP/1.1\" 404 Not Found\n",
"\u001b[0;36m(APIServer pid=7894)\u001b[0;0m \u001b[0;36m(APIServer pid=7894)\u001b[0;0m INFO: 127.0.0.1:50958 - \"GET /v1/models HTTP/1.1\" 404 Not Found\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\u001b[0;36m(APIServer pid=7894)\u001b[0;0m \u001b[0;36m(APIServer pid=7894)\u001b[0;0m /home/zeus/miniconda3/envs/cloudspace/lib/python3.12/site-packages/aiohttp/connector.py:993: DeprecationWarning: enable_cleanup_closed ignored because https://github.com/python/cpython/pull/118960 is fixed in Python version sys.version_info(major=3, minor=12, micro=11, releaselevel='final', serial=0)\n",
"\u001b[0;36m(APIServer pid=7894)\u001b[0;0m \u001b[0;36m(APIServer pid=7894)\u001b[0;0m super().__init__(\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[0;36m(APIServer pid=7894)\u001b[0;0m \u001b[0;36m(APIServer pid=7894)\u001b[0;0m INFO: 127.0.0.1:50730 - \"GET /v1/models HTTP/1.1\" 404 Not Found\n",
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"\u001b[0;36m(APIServer pid=7894)\u001b[0;0m \u001b[0;36m(APIServer pid=7894)\u001b[0;0m INFO: 127.0.0.1:50730 - \"GET /v1/models HTTP/1.1\" 404 Not Found\n",
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"\u001b[0;36m(APIServer pid=7894)\u001b[0;0m \u001b[0;36m(APIServer pid=7894)\u001b[0;0m INFO: 127.0.0.1:50730 - \"GET /v1/models HTTP/1.1\" 404 Not Found\n",
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"\u001b[0;36m(APIServer pid=7894)\u001b[0;0m \u001b[0;36m(APIServer pid=7894)\u001b[0;0m INFO: 127.0.0.1:50730 - \"GET /v1/models HTTP/1.1\" 404 Not Found\n",
"\u001b[0;36m(APIServer pid=7894)\u001b[0;0m \u001b[0;36m(APIServer pid=7894)\u001b[0;0m INFO: 127.0.0.1:50958 - \"GET /v1/models HTTP/1.1\" 404 Not Found\n",
"\u001b[0;36m(APIServer pid=7894)\u001b[0;0m \u001b[0;36m(APIServer pid=7894)\u001b[0;0m INFO: 127.0.0.1:50730 - \"GET /v1/models HTTP/1.1\" 404 Not Found\n",
"\u001b[0;36m(APIServer pid=7894)\u001b[0;0m \u001b[0;36m(APIServer pid=7894)\u001b[0;0m INFO: 127.0.0.1:50958 - \"GET /v1/models HTTP/1.1\" 404 Not Found\n"
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"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'scores'</span>: <span style=\"font-weight: bold\">[</span>\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'1'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'This trajectory successfully counts to 10 using numeric symbols as requested, achieving</span>\n",
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"<span style=\"color: #008000; text-decoration-color: #008000\">which does not fulfill the goal as specified.'</span>,\n",
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" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'This trajectory does not count at all but instead uses letters. It does not achieve the</span>\n",
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"text": [
"\u001b[0;36m(APIServer pid=7894)\u001b[0;0m \u001b[0;36m(APIServer pid=7894)\u001b[0;0m INFO: 127.0.0.1:50730 - \"GET /v1/models HTTP/1.1\" 404 Not Found\n",
"\u001b[0;36m(APIServer pid=7894)\u001b[0;0m \u001b[0;36m(APIServer pid=7894)\u001b[0;0m INFO: 127.0.0.1:50958 - \"GET /v1/models HTTP/1.1\" 404 Not Found\n"
]
}
],
"source": [
"import art\n",
"from art.rewards import ruler_score_group\n",
"\n",
"base_messages = [\n",
" {\"role\": \"system\", \"content\": \"You count numbers using numeric symbols.\"},\n",
" {\"role\": \"user\", \"content\": \"Count to 10.\"},\n",
"]\n",
"\n",
"good_trajectory = art.Trajectory(\n",
" messages_and_choices=[\n",
" *base_messages,\n",
" {\"role\": \"assistant\", \"content\": \"1, 2, 3, 4, 5, 6, 7, 8, 9, 10\"},\n",
" ],\n",
" reward=0,\n",
")\n",
"\n",
"mediocre_trajectory = art.Trajectory(\n",
" messages_and_choices=[\n",
" *base_messages,\n",
" {\"role\": \"assistant\",\n",
" \"content\": \"one, two, three, four, five, six, seven, eight, nine, ten\"},\n",
" ],\n",
" reward=0,\n",
")\n",
"\n",
"bad_trajectory = art.Trajectory(\n",
" messages_and_choices=[\n",
" *base_messages,\n",
" {\"role\": \"assistant\", \"content\": \"a, b, c, d, e, f, g, h, i, j\"},\n",
" ],\n",
" reward=0,\n",
")\n",
"\n",
"sample_group = art.TrajectoryGroup(\n",
" trajectories=[good_trajectory, mediocre_trajectory, bad_trajectory]\n",
")\n",
"\n",
"judged_group = await ruler_score_group(\n",
" sample_group, \"openrouter/openai/gpt-4o-mini\", debug=True\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Define rollout function"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"cellView": "form",
"id": "FET-_U0IPjq8"
},
"outputs": [],
"source": [
"@dataclass\n",
"class McpScenario:\n",
" \"\"\"A scenario for MCP agent evaluation against a remote Smithery server.\"\"\"\n",
"\n",
" task_description: str\n",
" max_turns: int = MAX_TURNS\n",
"\n",
"\n",
"@weave.op()\n",
"async def rollout(\n",
" model: art.Model,\n",
" scenario: McpScenario,\n",
" debug: bool = False,\n",
") -> art.Trajectory:\n",
" \"\"\"Run an MCP agent rollout against the remote Smithery MCP server.\"\"\"\n",
" traj = art.Trajectory(\n",
" messages_and_choices=[],\n",
" reward=0,\n",
" metadata={\"task\": scenario.task_description},\n",
" metrics={\n",
" \"task_completed\": False,\n",
" \"success\": False,\n",
" \"ran_out_of_turns\": False,\n",
" },\n",
" scenario=scenario,\n",
" )\n",
"\n",
" # Discover available tools from the remote server\n",
" tools_result, _resources_result = await list_tools_and_resources()\n",
" tool_names = [t.name for t in tools_result.tools]\n",
" log(\"rollout: discovered tools\", count=len(tool_names), names=tool_names)\n",
"\n",
" # Convert to OpenAI tool format\n",
" tool_schemas = []\n",
" for tool in tools_result.tools:\n",
" tool_schema = {\n",
" \"type\": \"function\",\n",
" \"function\": {\n",
" \"name\": tool.name,\n",
" \"description\": tool.description or f\"MCP tool: {tool.name}\",\n",
" \"parameters\": tool.inputSchema or {\"type\": \"object\", \"properties\": {}},\n",
" },\n",
" }\n",
" tool_schemas.append(tool_schema)\n",
"\n",
" # Add completion tool schema\n",
" tool_schemas.append(\n",
" {\n",
" \"type\": \"function\",\n",
" \"function\": {\n",
" \"name\": \"complete_task\",\n",
" \"description\": \"Complete the task with a summary\",\n",
" \"parameters\": {\n",
" \"type\": \"object\",\n",
" \"properties\": {\n",
" \"summary\": {\n",
" \"type\": \"string\",\n",
" \"description\": \"Summary of accomplishments\",\n",
" }\n",
" },\n",
" \"required\": [\"summary\"],\n",
" },\n",
" },\n",
" }\n",
" )\n",
"\n",
" traj.tools = tool_schemas\n",
"\n",
" # Initialize conversation\n",
" system_prompt = (\n",
" f\"You are a database agent with access to a live SQL database. \"\n",
" f\"The database is working correctly. DO NOT claim there are errors \"\n",
" f\"unless a tool explicitly returns an error message. \"\n",
" f\"ALWAYS use tools to answer questions — never simulate or guess. \"\n",
" f\"Start by calling list_tables, then describe_table, then run_query. \"\n",
" f\"Call 'complete_task' with your answer when done. \"\n",
" f\"You have {scenario.max_turns} turns.\"\n",
" )\n",
"\n",
" traj.messages_and_choices = [\n",
" {\"role\": \"system\", \"content\": system_prompt},\n",
" {\n",
" \"role\": \"user\",\n",
" \"content\": f\"Please complete this task: {scenario.task_description}\",\n",
" },\n",
" ]\n",
"\n",
" num_turns = 0\n",
" task_completed = False\n",
"\n",
" # Main interaction loop\n",
" while num_turns < scenario.max_turns and not task_completed:\n",
" num_turns += 1\n",
"\n",
" try:\n",
" # === Log request ===\n",
" last_user = next(\n",
" (m for m in reversed(traj.messages()) if m[\"role\"] == \"user\"), None\n",
" )\n",
" log(\n",
" \"LLM request\",\n",
" step=num_turns,\n",
" model=(model.inference_model_name or model.name),\n",
" tools=len(tool_schemas),\n",
" last_user=(last_user[\"content\"][:160] + \"...\" if last_user else None),\n",
" )\n",
"\n",
" # Get LLM response\n",
" async with traj.track_duration(\"llm_completion\"):\n",
" openai_client = AsyncOpenAI(\n",
" api_key=model.inference_api_key,\n",
" base_url=model.inference_base_url,\n",
" )\n",
"\n",
" # We also log the request body (without huge params)\n",
" req_preview = {\n",
" \"model\": model.inference_model_name\n",
" if model.inference_model_name\n",
" else model.name,\n",
" \"messages_len\": len(traj.messages()),\n",
" \"tools_len\": len(tool_schemas),\n",
" }\n",
" log_json(\"LLM request (preview)\", req_preview)\n",
"\n",
" response = await openai_client.chat.completions.create(\n",
" model=model.inference_model_name\n",
" if model.inference_model_name\n",
" else model.name,\n",
" messages=traj.messages(),\n",
" tools=tool_schemas,\n",
" max_completion_tokens=8000,\n",
" )\n",
"\n",
" # === Log response ===\n",
" choice = response.choices[0]\n",
"\n",
" finish_reason = getattr(choice, \"finish_reason\", None)\n",
" msg = choice.message\n",
" has_tools = bool(getattr(msg, \"tool_calls\", None))\n",
" content_preview = (\n",
" (msg.content[:200] + \"...\")\n",
" if isinstance(msg.content, str) and msg.content\n",
" else str(msg.content)[:200]\n",
" )\n",
" log(\n",
" \"LLM response parsed\",\n",
" finish_reason=finish_reason,\n",
" has_tool_calls=has_tools,\n",
" content_preview=content_preview,\n",
" )\n",
"\n",
" traj.messages_and_choices.append(choice)\n",
"\n",
" # Handle tool calls\n",
" if msg.tool_calls:\n",
" for tool_call in msg.tool_calls:\n",
" try:\n",
" log(\n",
" \"Tool call received\",\n",
" name=tool_call.function.name,\n",
" raw_args=tool_call.function.arguments,\n",
" )\n",
" tool_args = json.loads(tool_call.function.arguments or \"{}\")\n",
"\n",
" if tool_call.function.name == \"complete_task\":\n",
" traj.metrics[\"task_completed\"] = True\n",
" task_completed = True\n",
" traj.logs.append(\n",
" f\"Task completion attempted with summary: {tool_args.get('summary', '')}\"\n",
" )\n",
" # We still append a tool message for completeness\n",
" traj.messages_and_choices.append(\n",
" {\n",
" \"role\": \"tool\",\n",
" \"tool_call_id\": tool_call.id,\n",
" \"content\": \"Task marked complete.\",\n",
" }\n",
" )\n",
" else:\n",
" # 🔧 Call MCP tool through remote Smithery session\n",
" result = await call_mcp_tool(\n",
" tool_call.function.name, tool_args\n",
" )\n",
"\n",
" content_text = get_content_text(result)\n",
" log(\n",
" \"Tool result\",\n",
" name=tool_call.function.name,\n",
" len=len(content_text),\n",
" )\n",
"\n",
" if len(content_text) > 20000:\n",
" # print(\n",
" # f\"Tool call result for {tool_call.function.name} is too long: {len(content_text)}\"\n",
" # )\n",
" # print(f\"Args: {tool_args}\")\n",
" # print(content_text[:1000])\n",
" # print(content_text[-1000:])\n",
" raise Exception(\n",
" f\"Tool call result for {tool_call.function.name} is too long: {len(content_text)}\"\n",
" )\n",
"\n",
" # Add tool response\n",
" traj.messages_and_choices.append(\n",
" {\n",
" \"role\": \"tool\",\n",
" \"tool_call_id\": tool_call.id,\n",
" \"content\": content_text,\n",
" }\n",
" )\n",
"\n",
" except Exception as e:\n",
" traceback.print_exc()\n",
" traj.logs.append(f\"Tool call error: {e}\")\n",
"\n",
" # Add error response\n",
" traj.messages_and_choices.append(\n",
" {\n",
" \"role\": \"tool\",\n",
" \"tool_call_id\": tool_call.id,\n",
" \"content\": f\"Error: {str(e)}\",\n",
" }\n",
" )\n",
" else:\n",
" # No tool calls — log and continue (RULER will likely give 0)\n",
" log(\n",
" \"LLM returned no tool_calls; skipping tool execution\",\n",
" turn=num_turns,\n",
" )\n",
" # You can consider breaking here or letting it try another turn\n",
" # break\n",
"\n",
" except Exception as e:\n",
" traceback.print_exc()\n",
" traj.logs.append(f\"Error in turn {num_turns}: {e}\")\n",
" break\n",
"\n",
" if not task_completed and num_turns == scenario.max_turns:\n",
" traj.metrics[\"ran_out_of_turns\"] = True\n",
"\n",
" traj.metrics[\"num_turns\"] = num_turns\n",
"\n",
" return traj.finish()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Training pipeline"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m Using config: max_turns=3, rollouts_per_group=4, groups_per_step=2, num_epochs=1, learning_rate=1e-05\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "b34ac9f344fa4304b3b9cec3d33a1926",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"Iterating dataset: 0%| | 0/8 [00:00<?, ?batch/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Gathering trajectory groups with RULER scoring...\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "d783293a92a747c5a31e386a64b8623a",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"train gather step 0: 0%| | 0/8 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"[weave.trace.op|WARNING]Warning: Traces will not be logged. Call weave.init to log your traces to a project.\n",
" (subsequent messages of this type will be suppressed)\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50554 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50564 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50572 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50588 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50596 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50604 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50618 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50620 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50630 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50640 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50644 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50648 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50654 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50664 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50666 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50672 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50676 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50678 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50680 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50694 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50710 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50726 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50712 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50736 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50750 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50764 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50780 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50784 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50786 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50790 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50800 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50810 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50812 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50818 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50834 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50836 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50838 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50852 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50864 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50870 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50876 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:38] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:38] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Create a combined report of active projects per department, including the department budget. Then provide a summary and thorough anal...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:38] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50890 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50894 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50908 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50910 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50918 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50924 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:38] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:38] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Create a combined report of active projects per department, including the department budget. Then provide a summary and thorough anal...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50936 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:38] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:38] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:38] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Create a combined report of active projects per department, including the department budget. Then provide a summary and thorough anal...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:38] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:38] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:38] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Create a combined report of active projects per department, including the department budget. Then provide a summary and thorough anal...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:38] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:38] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:38] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List all employees with their department name, including those without an assigned department. Then provide a summary and thorough an...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:38] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:38] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:38] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List all employees with their department name, including those without an assigned department. Then provide a summary and thorough an...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:38] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:38] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:38] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List all employees with their department name, including those without an assigned department. Then provide a summary and thorough an...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:38] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:38] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:38] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List all employees with their department name, including those without an assigned department. Then provide a summary and thorough an...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:38] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(EngineCore_DP0 pid=87084)\u001b[0;0m WARNING 02-16 18:48:38 [utils.py:250] Using default LoRA kernel configs\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:53] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='None'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:53] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:53] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='None'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:53] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:53] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='None'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:53] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:53] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='None'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:53] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50492 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50500 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50510 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50516 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50524 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50532 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50540 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50552 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50554 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50564 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50572 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50582 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50588 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50596 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50600 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50610 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50616 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50620 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50624 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50642 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50628 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:53] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:53] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List all employees with their department name, including those without an assigned department. Then provide a summary and thorough an...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:54] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50658 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50660 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50670 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:54] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:54] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List all employees with their department name, including those without an assigned department. Then provide a summary and thorough an...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:54] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:54] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:54] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List all employees with their department name, including those without an assigned department. Then provide a summary and thorough an...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:54] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:54] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:54] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List all employees with their department name, including those without an assigned department. Then provide a summary and thorough an...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:48:54] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:09] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='To proceed, I first need to know the database schema and any relevant tables. Could you please specify which tables contain project information and departmental budgets?\\n...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:09] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50048 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50060 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50066 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50068 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50074 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50084 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:09] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:09] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Create a combined report of active projects per department, including the department budget. Then provide a summary and thorough anal...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:09] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:09] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='To proceed, I need to know which tables are available in the database. Could you please list all the tables using the `list_tables` function?\\n...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:09] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50092 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50106 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50118 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50124 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50134 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50144 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:09] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:09] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Create a combined report of active projects per department, including the department budget. Then provide a summary and thorough anal...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:09] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:10] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='To proceed, I need to know which tables are available in our database that contain information about projects, departments, and their budgets. Could you please list the tables using the `list_tables` ...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:10] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50158 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50168 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50182 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50184 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50200 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50202 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:10] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:10] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Create a combined report of active projects per department, including the department budget. Then provide a summary and thorough anal...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:10] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:12] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"We have three tables: 'departments', 'employees', and 'projects'. Let's start with 'employees' table to list all employees along with their department names.\\n...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:12] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50214 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50228 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50232 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50238 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50248 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50250 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:12] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:12] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List all employees with their department name, including those without an assigned department. Then provide a summary and thorough an...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:12] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:12] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"We have the following tables available: 'departments', 'employees', and 'projects'. Now, I will proceed to describe the 'employees' table to understand its structure.\\n...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:12] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50262 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50264 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50276 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50278 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50290 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50292 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:12] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:12] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List all employees with their department name, including those without an assigned department. Then provide a summary and thorough an...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:12] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:12] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"We have the following tables available: 'departments', 'employees', and 'projects'. Next, I will describe the 'employees' table to determine the columns we need to retrieve.\\n...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:12] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50308 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50312 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50324 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50330 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50340 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50348 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:12] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:12] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List all employees with their department name, including those without an assigned department. Then provide a summary and thorough an...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:12] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:13] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='None'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:13] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50358 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50362 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50364 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50380 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50390 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50402 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:13] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:13] Tool call received | name='describe_table' raw_args='{\"table_name\": \"departments\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50410 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50426 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50434 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50440 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50444 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50456 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:13] Tool result | name='describe_table' len=395\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:13] Tool call received | name='describe_table' raw_args='{\"table_name\": \"projects\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50458 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50460 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50470 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50486 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50490 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50504 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:13] Tool result | name='describe_table' len=603\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:13] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List all employees with their department name, including those without an assigned department. Then provide a summary and thorough an...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:13] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 8,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:13] LLM response parsed | finish_reason='stop' has_tool_calls=False content_preview='ocale_task\\n{\"summary\": \"To fulfill your request, I will first list all tables in the database to identify potential candidate tables for projects and departments. Then, I will describe these tables to...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:13] LLM returned no tool_calls; skipping tool execution | turn=1\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:13] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Create a combined report of active projects per department, including the department budget. Then provide a summary and thorough anal...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:13] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 3,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:15] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='None'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:15] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50510 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50518 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50520 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50536 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50538 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50546 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:15] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:15] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Create a combined report of active projects per department, including the department budget. Then provide a summary and thorough anal...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:15] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 5,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:16] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The database contains the following tables: 'departments', 'employees', and 'projects'. \\n\\nLet's start by determining the structure of the 'departments', 'projects', and 'employees' tables. I will firs...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:16] Tool call received | name='describe_table' raw_args='{\"table_name\": \"departments\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50550 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50562 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50566 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50578 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50594 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50604 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:16] Tool result | name='describe_table' len=395\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:16] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Create a combined report of active projects per department, including the department budget. Then provide a summary and thorough anal...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:16] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:18] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The available tables in the database are 'departments', 'employees', and 'projects'. \\n\\nFirst, let's describe the 'projects' table to understand its structure. Could you please call the `describe_table...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:18] Tool call received | name='describe_table' raw_args='{\"table_name\": \"projects\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50380 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50386 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50398 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50408 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50420 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50434 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:18] Tool result | name='describe_table' len=603\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:18] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Create a combined report of active projects per department, including the department budget. Then provide a summary and thorough anal...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:18] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:18] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The database contains the following tables: 'departments', 'employees', and 'projects'. Let's start with the 'employees' table to describe its columns and then create a query to get the combined repor...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:18] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50436 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50442 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50450 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50466 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50476 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50492 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:18] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:18] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Create a combined report of active projects per department, including the department budget. Then provide a summary and thorough anal...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:18] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:20] LLM response parsed | finish_reason='stop' has_tool_calls=False content_preview=\"The 'employees' table has columns: 'id', 'name', 'department_id', 'role', 'salary', and 'hire_date'. The 'department_id' column could be useful in joining with the 'departments' table to get the depar...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:20] LLM returned no tool_calls; skipping tool execution | turn=3\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:21] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The 'employees' table has the following columns: id, name, department_id, role, salary, and hire_date. Now, I will run a query to get the list of employees with their department name, including those ...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:21] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT employees.name, departments.department_name FROM employees LEFT JOIN departments ON employees.department_id = departments.id;\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50496 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50508 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50522 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50538 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50542 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50544 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:21] Tool result | name='run_query' len=56\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:23] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"Based on the tables listed, we have 'departments', 'employees', and 'projects'. We need to gather information from 'projects' to find active projects and from 'departments' to get the budgets. First, ...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:23] Tool call received | name='describe_table' raw_args='{\"table_name\": \"projects\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50556 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50562 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50576 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50582 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50590 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50602 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:23] Tool result | name='describe_table' len=603\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:24] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='Based on the descriptions returned by the `describe_table` function, we have three tables: `employees`, `departments`, and `projects`. The `employees` table has a `department_id` column which we need ...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:24] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT id, name, role, salary, hire_date FROM employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50606 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50620 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50636 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50646 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50660 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50666 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:24] Tool result | name='run_query' len=2275\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:25] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The 'departments' table has four columns: 'id' (INTEGER, primary key), 'name' (TEXT, not nullable), 'location' (TEXT, not nullable), and 'budget' (REAL, not nullable).\\n\\nNext, let's describe the 'proje...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:25] Tool call received | name='describe_table' raw_args='{\"table_name\": \"projects\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50676 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50692 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50708 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50714 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50720 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50722 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:25] Tool result | name='describe_table' len=603\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:26] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The 'employees' table includes columns like 'name', 'department_id', and 'hire_date'. Since 'department_id' is nullable, it indicates that an employee could not be assigned to a department or their de...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:26] Tool call received | name='run_query' raw_args='{\"sql\": \"RUNTIME_QUERY\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50726 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50732 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50738 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50746 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50748 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50760 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:26] Tool result | name='run_query' len=45\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:35] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The table 'employees' has the following columns:\\n\\n- `id` (INTEGER, primary key, nullable=true)\\n- `name` (TEXT, nullable=false, primary key=false)\\n- `department_id` (INTEGER, nullable=true, primary key...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:35] Tool call received | name='describe_table' raw_args='{\"table_name\": \"projects\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50096 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50110 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50120 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50122 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50130 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50136 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:35] Tool result | name='describe_table' len=603\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:52] LLM response parsed | finish_reason='stop' has_tool_calls=False content_preview=\"The 'projects' table has the following structure:\\n- An `id` which is an integer and the primary key (nullable=true).\\n- A `name` which is a text and the primary key (nullable=false).\\n- A `department_id...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:49:52] LLM returned no tool_calls; skipping tool execution | turn=3\n"
]
},
{
"data": {
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
"<span style=\"font-weight: bold\">[</span>RULER<span style=\"font-weight: bold\">]</span> Pretty-printed LLM choice JSON:\n",
"</pre>\n"
],
"text/plain": [
"\n",
"\u001b[1m[\u001b[0mRULER\u001b[1m]\u001b[0m Pretty-printed LLM choice JSON:\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'scores'</span>: <span style=\"font-weight: bold\">[</span>\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'1'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'The trajectory efficiently lists the necessary tables and describes the required ones </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">to prepare for the final query. It follows a logical progression towards the goal but does not yet perform the </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">final query for results.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.7</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'2'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">\"This trajectory correctly identifies the tables but aims to describe the department </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">table first, which is not optimal since the query focuses on 'projects'. It does begin to gather necessary </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">information but lacks efficiency in approach.\"</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'3'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">\"The trajectory begins similarly to Trajectory 2 but makes an additional detour by </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">focusing on the 'employees' table initially, which is less relevant to the task at hand. It shows understanding but</span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">strays from efficiency.\"</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.4</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'4'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">\"This trajectory effectively outlines its intentions and requests information about the </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">'projects' table first, which is on track to create the required report. However, it still does not execute the </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">final query, leaving it incomplete.\"</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.6</span>\n",
" <span style=\"font-weight: bold\">}</span>\n",
" <span style=\"font-weight: bold\">]</span>\n",
"<span style=\"font-weight: bold\">}</span>\n",
"</pre>\n"
],
"text/plain": [
"\u001b[1m{\u001b[0m\n",
" \u001b[32m'scores'\u001b[0m: \u001b[1m[\u001b[0m\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'1'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'The trajectory efficiently lists the necessary tables and describes the required ones \u001b[0m\n",
"\u001b[32mto prepare for the final query. It follows a logical progression towards the goal but does not yet perform the \u001b[0m\n",
"\u001b[32mfinal query for results.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.7\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'2'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m\"This trajectory correctly identifies the tables but aims to describe the department \u001b[0m\n",
"\u001b[32mtable first, which is not optimal since the query focuses on 'projects'. It does begin to gather necessary \u001b[0m\n",
"\u001b[32minformation but lacks efficiency in approach.\"\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.5\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'3'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m\"The trajectory begins similarly to Trajectory 2 but makes an additional detour by \u001b[0m\n",
"\u001b[32mfocusing on the 'employees' table initially, which is less relevant to the task at hand. It shows understanding but\u001b[0m\n",
"\u001b[32mstrays from efficiency.\"\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.4\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'4'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m\"This trajectory effectively outlines its intentions and requests information about the \u001b[0m\n",
"\u001b[32m'projects' table first, which is on track to create the required report. However, it still does not execute the \u001b[0m\n",
"\u001b[32mfinal query, leaving it incomplete.\"\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.6\u001b[0m\n",
" \u001b[1m}\u001b[0m\n",
" \u001b[1m]\u001b[0m\n",
"\u001b[1m}\u001b[0m\n"
]
},
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{
"data": {
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"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
"<span style=\"font-weight: bold\">[</span>RULER<span style=\"font-weight: bold\">]</span> Pretty-printed LLM choice JSON:\n",
"</pre>\n"
],
"text/plain": [
"\n",
"\u001b[1m[\u001b[0mRULER\u001b[1m]\u001b[0m Pretty-printed LLM choice JSON:\n"
]
},
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"output_type": "display_data"
},
{
"data": {
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'scores'</span>: <span style=\"font-weight: bold\">[</span>\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'1'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'This trajectory successfully identifies the necessary tables and their structure, but </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">does not complete the task of listing employees and their departments with a successful query execution.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'2'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'This trajectory correctly identifies the tables and the structure but fails at the </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">query stage and receives an error. Did not achieve the goal of listing employees with their department names, </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">leading to a lower score.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.3</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'3'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'This trajectory not only retrieves the employee data correctly but also demonstrates </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">awareness of how to join tables to get the department names. However, it falls short of producing the final output </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">of employees with their department names due to a lack of a join in the execution step. Overall, it shows </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">significant progress but does not complete the task as intended.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.7</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'4'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'Like trajectory 3, this trajectory accurately recognizes the relevant tables and their </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">structure. However, an attempt to run the SQL query encountered an error. It demonstrates an understanding of the </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">task but fails to achieve the goal, leading to a reduced score.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.4</span>\n",
" <span style=\"font-weight: bold\">}</span>\n",
" <span style=\"font-weight: bold\">]</span>\n",
"<span style=\"font-weight: bold\">}</span>\n",
"</pre>\n"
],
"text/plain": [
"\u001b[1m{\u001b[0m\n",
" \u001b[32m'scores'\u001b[0m: \u001b[1m[\u001b[0m\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'1'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'This trajectory successfully identifies the necessary tables and their structure, but \u001b[0m\n",
"\u001b[32mdoes not complete the task of listing employees and their departments with a successful query execution.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.5\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'2'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'This trajectory correctly identifies the tables and the structure but fails at the \u001b[0m\n",
"\u001b[32mquery stage and receives an error. Did not achieve the goal of listing employees with their department names, \u001b[0m\n",
"\u001b[32mleading to a lower score.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.3\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'3'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'This trajectory not only retrieves the employee data correctly but also demonstrates \u001b[0m\n",
"\u001b[32mawareness of how to join tables to get the department names. However, it falls short of producing the final output \u001b[0m\n",
"\u001b[32mof employees with their department names due to a lack of a join in the execution step. Overall, it shows \u001b[0m\n",
"\u001b[32msignificant progress but does not complete the task as intended.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.7\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'4'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'Like trajectory 3, this trajectory accurately recognizes the relevant tables and their \u001b[0m\n",
"\u001b[32mstructure. However, an attempt to run the SQL query encountered an error. It demonstrates an understanding of the \u001b[0m\n",
"\u001b[32mtask but fails to achieve the goal, leading to a reduced score.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.4\u001b[0m\n",
" \u001b[1m}\u001b[0m\n",
" \u001b[1m]\u001b[0m\n",
"\u001b[1m}\u001b[0m\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m starting train\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m /tmp/ipykernel_75472/1714310424.py:52: DeprecationWarning: model.train() is deprecated. Use backend.train(model, ...) instead.\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Migration guide:\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m # Before (deprecated):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m await model.train(trajectory_groups, config=TrainConfig(learning_rate=5e-6))\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m # After (recommended):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m result = await backend.train(model, trajectory_groups, learning_rate=5e-6)\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m await model.log(trajectory_groups, metrics=result.metrics, step=result.step, split='train')\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Key differences:\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m - backend.train() does NOT automatically log trajectories or metrics\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m - backend.train() returns a TrainResult with step, metrics, and checkpoint info\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m - Each backend has its own type-checked parameters (no more generic config objects)\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m await model.train(\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Packed 8 trajectories into 4 sequences of length 2048\n"
]
},
{
"data": {
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"model_id": "63167966af734d44aee26893c16f64c2",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"train: 0%| | 0/4 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m The model is already on multiple devices. Skipping the move to device specified in `args`.\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m ==((====))== Unsloth - 2x faster free finetuning | Num GPUs used = 1\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \\\\ /| Num examples = 10,000,000 | Num Epochs = 3 | Total steps = 30,000,000\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m O^O/ \\_/ \\ Batch size per device = 2 | Gradient accumulation steps = 1\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \\ / Data Parallel GPUs = 1 | Total batch size (2 x 1 x 1) = 2\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"-____-\" Trainable parameters = 14,966,784 of 3,100,905,472 (0.48% trained)\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Unsloth: Will smartly offload gradients to save VRAM!\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Gathering trajectory groups with RULER scoring...\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "ee7d68dee799412fbb497c6c19db2368",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"train gather step 1: 0%| | 0/8 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50398 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50402 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50406 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50410 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50424 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50432 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50448 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50450 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50460 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50462 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50472 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50486 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50490 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50498 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50506 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50516 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50532 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50542 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50544 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50550 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50566 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50586 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50574 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50596 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50612 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50614 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50630 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50644 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50646 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50662 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50672 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50678 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50692 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50700 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50710 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50724 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50734 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50740 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50744 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50752 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50768 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:50:57] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:50:57] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Compute for each department its headcount and total payroll (sum of salaries). Then generate a summary and a thorough analysis/report...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:50:57] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50772 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50778 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50792 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50796 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50806 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50816 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:50:57] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:50:57] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Compute for each department its headcount and total payroll (sum of salaries). Then generate a summary and a thorough analysis/report...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50826 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:50:57] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:50:57] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:50:57] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Compute for each department its headcount and total payroll (sum of salaries). Then generate a summary and a thorough analysis/report...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:50:57] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:50:57] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:50:57] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Compute for each department its headcount and total payroll (sum of salaries). Then generate a summary and a thorough analysis/report...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:50:57] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:50:57] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:50:57] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Identify departments that have no employees assigned. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:50:57] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:50:57] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:50:57] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Identify departments that have no employees assigned. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:50:57] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:50:57] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:50:57] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Identify departments that have no employees assigned. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:50:57] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:50:57] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:50:57] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Identify departments that have no employees assigned. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:50:57] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:02] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"To start, let's list all the tables available in the database to understand what data we are working with.\\n...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:02] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50962 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50966 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50968 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50972 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50980 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50992 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:02] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:02] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Compute for each department its headcount and total payroll (sum of salaries). Then generate a summary and a thorough analysis/report...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:02] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:03] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"To proceed with your request, I first need to gather the necessary information. Let's start by listing all the tables in the database.\\n...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:03] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50008 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50018 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50020 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50032 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50042 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50048 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:03] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:03] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Compute for each department its headcount and total payroll (sum of salaries). Then generate a summary and a thorough analysis/report...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:03] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:04] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"To proceed, I need to first identify the table that contains information about departments and their employees. Let's start by listing the tables in the database to determine which one holds this info...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:04] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50050 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50058 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50064 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50080 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50096 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50112 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:04] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:04] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Identify departments that have no employees assigned. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:04] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:04] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='To proceed with the task of computing for each department its headcount and total payroll, I first need to list the tables available in the database. Please allow me to execute the following action:\\n...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:04] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50114 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50118 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50130 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50138 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50150 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50166 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:04] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:04] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Compute for each department its headcount and total payroll (sum of salaries). Then generate a summary and a thorough analysis/report...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:04] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:04] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"To identify departments that have no employees assigned, we first need to list all tables in the database and then check each table for columns that might indicate department assignments. Let's start ...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:04] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50170 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50178 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50190 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50194 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50198 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50212 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:04] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:04] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Identify departments that have no employees assigned. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:04] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:05] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='To proceed with identifying departments that have no employees assigned, we first need to list the tables in our database and then explore the structure of at least one of those tables to understand w...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:05] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50226 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50230 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50242 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50250 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50254 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50262 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:05] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:05] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Identify departments that have no employees assigned. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:05] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:08] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='To proceed with identifying departments that have no employees assigned, I first need to list all the tables in the database. Could you please confirm if there is a table named `Departments` that migh...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:08] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50722 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50728 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50734 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50740 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50756 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50764 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:08] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:08] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Identify departments that have no employees assigned. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:08] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:08] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='To proceed with your request, we first need to identify the relevant tables and columns in the database that contain the necessary information for calculating headcount and total payroll by department...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:08] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50778 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50784 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50790 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50800 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50806 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50820 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:08] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:08] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Compute for each department its headcount and total payroll (sum of salaries). Then generate a summary and a thorough analysis/report...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:08] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:08] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The database contains three tables: 'departments', 'employees', and 'projects'. Next, we need to describe the structure of the 'employees' table to understand its columns.\\n\\n...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:08] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50836 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50846 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50848 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50852 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50858 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50870 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:08] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:08] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Compute for each department its headcount and total payroll (sum of salaries). Then generate a summary and a thorough analysis/report...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:08] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:13] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The database contains the following tables: 'departments', 'employees', and 'projects'. \\n\\nNext, I will describe the structure of the 'employees' table to understand its columns, which will help me com...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:13] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50884 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50888 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50896 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50908 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50922 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50924 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:13] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:13] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Compute for each department its headcount and total payroll (sum of salaries). Then generate a summary and a thorough analysis/report...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:13] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:13] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The database contains three tables: 'departments', 'employees', and 'projects'. Now, we need to determine which of these tables could have department information, namely by examining each table for co...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:13] Tool call received | name='describe_table' raw_args='{\"table_name\": \"departments\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50940 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50956 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50968 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50980 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50992 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50008 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:13] Tool result | name='describe_table' len=395\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:13] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Identify departments that have no employees assigned. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:13] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:13] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"Our database contains three tables: 'departments', 'employees', and 'projects'. To find departments that have no employees assigned, we need to look into the 'employees' table. Let's describe the tabl...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:13] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50024 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50032 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50046 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50052 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50056 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50060 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:13] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:13] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Identify departments that have no employees assigned. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:13] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:14] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The database contains three tables: 'departments', 'employees', and 'projects'. The 'departments' table should be where we find the department names, and we'll check if there are employees associated ...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:14] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50070 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50072 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50086 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50100 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50110 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50116 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:14] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:14] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Identify departments that have no employees assigned. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:14] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:18] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The database contains three tables: 'departments', 'employees', and 'projects'. We need to focus on the 'employees' table, which likely includes a field indicating the department each employee belongs...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:18] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50780 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50786 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50802 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50814 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50818 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50832 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:18] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:18] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Compute for each department its headcount and total payroll (sum of salaries). Then generate a summary and a thorough analysis/report...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:18] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:21] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='The listed tables are \"departments\", \"employees\", and \"projects\". It seems there isn\\'t a direct table named \"Employees\" or a \"Department_Employees\" table to link departments with their employees. Let\\'...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:21] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT DISTINCT department_id FROM employees WHERE department_id IS NOT NULL\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50844 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50850 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50852 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50854 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50858 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50868 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:21] Tool result | name='run_query' len=229\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:21] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Identify departments that have no employees assigned. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:21] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:22] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The 'departments' table has columns such as 'id', 'name', 'location', and 'budget'. It does not have a column that explicitly states the department number or name. \\n\\nNext, let's check the 'employees' ...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:22] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50872 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50888 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50892 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50908 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50914 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50930 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:22] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:26] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The 'employees' table has several columns and among them, 'department_id' seems relevant because it would allow us to match employees to their respective departments. Now, we will query the 'employees...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:26] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT department_id FROM departments WHERE department_id NOT IN (SELECT department_id FROM employees)\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50946 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50950 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50956 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50968 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50982 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50984 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:26] Tool result | name='run_query' len=42\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:27] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The 'employees' table includes a column called 'department_id' which seems to reference departments. Now, let's see which departments in the 'departments' table do not have any employees associated wi...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:27] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT dp.name FROM departments dp LEFT JOIN employees em ON dp.id = em.department_id WHERE em.department_id IS NULL\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50000 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50016 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50020 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50028 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50030 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50040 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:27] Tool result | name='run_query' len=37\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:31] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The 'employees' table has the following structure:\\n- `id`: INTEGER, primary key, not nullable\\n- `name`: TEXT, not nullable\\n- `department_id`: INTEGER, nullable\\n- `role`: TEXT, not nullable\\n- `salary`:...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:31] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT departments.department_name, COUNT(employees.id) AS headcount, SUM(employees.salary) AS total_payroll FROM employees JOIN departments ON employees.department_id = departments.id GROUP BY departments.department_name\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50292 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50306 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50316 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50332 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50340 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50348 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:31] Tool result | name='run_query' len=56\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:35] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The 'employees' table has the following structure:\\n- `id`: An integer that uniquely identifies each employee, allowing NULL.\\n- `name`: Text containing the name of the employee, cannot be NULL.\\n- `depa...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:35] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT d.name AS department_name, COUNT(e.id) AS headcount, SUM(e.salary) AS total_payroll FROM employees e JOIN departments d ON e.department_id = d.id GROUP BY d.name ORDER BY d.name\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50356 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50372 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50388 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50402 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50414 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50430 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:35] Tool result | name='run_query' len=566\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:41] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The 'employees' table includes fields like `id`, `name`, `department_id`, `role`, `salary`, and `hire_date`. The `id` field is the primary key, while the `name`, `department_id`, `role`, and `salary` ...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:41] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT e.department_id, COUNT(*) AS headcount, SUM(e.salary) AS total_payroll FROM employees e WHERE e.department_id IS NOT NULL GROUP BY e.department_id;\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50410 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50418 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50424 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50432 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50434 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50448 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:41] Tool result | name='run_query' len=504\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:46] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='The database contains three tables: `departments`, `employees`, and `projects`. Next, we need to retrieve the required headcount and total payroll information for each department. However, since the `...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:46] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT d.department_name, COUNT(e.employee_id) as headcount, SUM(e.salary) as total_payroll FROM departments d JOIN employees e ON d.department_id = e.department_id GROUP BY d.department_name;\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50458 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50474 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50476 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50488 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50502 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50506 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:46] Tool result | name='run_query' len=46\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:46] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Compute for each department its headcount and total payroll (sum of salaries). Then generate a summary and a thorough analysis/report...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:46] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:49] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='The query executed successfully and returned five distinct department IDs: 1, 2, 3, 4, and 5, where `department_id IS NOT NULL`. This means that each of these departments has at least one employee ass...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:51:49] Tool call received | name='complete_task' raw_args='{\"summary\": \"No Department found with no employees assigned. There are 5 Departments with assigned employees (departments 1, 2, 3, 4, and 5) and in total there are 5 employees.\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:00] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='It seems there was an error because no such column as `department_name` exists in the `departments` table according to the database schema. In this case, we will use the `department_id` as the identif...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:00] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT d.department_id, COUNT(e.employee_id) as headcount, SUM(e.salary) as total_payroll FROM departments d JOIN employees e ON d.department_id = e.department_id GROUP BY d.department_id;\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50802 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50814 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50830 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50844 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50848 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50854 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:00] Tool result | name='run_query' len=44\n"
]
},
{
"data": {
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"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
"<span style=\"font-weight: bold\">[</span>RULER<span style=\"font-weight: bold\">]</span> Pretty-printed LLM choice JSON:\n",
"</pre>\n"
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"text/plain": [
"\n",
"\u001b[1m[\u001b[0mRULER\u001b[1m]\u001b[0m Pretty-printed LLM choice JSON:\n"
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{
"data": {
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'scores'</span>: <span style=\"font-weight: bold\">[</span>\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'1'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'This trajectory attempted to compute the required data but encountered an error due to </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">an incorrect column reference. Thus, it did not achieve the goal. It made progress by listing and describing the </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">tables, showing understanding but failing on the critical query.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.3</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'2'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">\"This trajectory successfully listed the tables, examined the 'employees' schema, and </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">executed the correct SQL query to compute headcount and total payroll by department, achieving the goal efficiently</span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">and correctly. The results show clear output and aggregation by departments.\"</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'3'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">\"This trajectory also successfully retrieved the necessary information by listing the </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">tables and describing the 'employees' table. However, it produced results using the department ID instead of names,</span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">showing partial clarity but missing what could have been more user-friendly outputs. Overall, it achieved the task </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">effectively but less efficiently than trajectory 2.\"</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.8</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'4'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'This trajectory attempted to perform the task but encountered errors in SQL execution </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">related to column names that do not exist. It failed to compute the required headcount and total payroll, thereby </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">not achieving the goal. It did show some understanding of the underlying data structure but did not progress </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">substantially towards the desired outcome.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.2</span>\n",
" <span style=\"font-weight: bold\">}</span>\n",
" <span style=\"font-weight: bold\">]</span>\n",
"<span style=\"font-weight: bold\">}</span>\n",
"</pre>\n"
],
"text/plain": [
"\u001b[1m{\u001b[0m\n",
" \u001b[32m'scores'\u001b[0m: \u001b[1m[\u001b[0m\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'1'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'This trajectory attempted to compute the required data but encountered an error due to \u001b[0m\n",
"\u001b[32man incorrect column reference. Thus, it did not achieve the goal. It made progress by listing and describing the \u001b[0m\n",
"\u001b[32mtables, showing understanding but failing on the critical query.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.3\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'2'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m\"This trajectory successfully listed the tables, examined the 'employees' schema, and \u001b[0m\n",
"\u001b[32mexecuted the correct SQL query to compute headcount and total payroll by department, achieving the goal efficiently\u001b[0m\n",
"\u001b[32mand correctly. The results show clear output and aggregation by departments.\"\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m1.0\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'3'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m\"This trajectory also successfully retrieved the necessary information by listing the \u001b[0m\n",
"\u001b[32mtables and describing the 'employees' table. However, it produced results using the department ID instead of names,\u001b[0m\n",
"\u001b[32mshowing partial clarity but missing what could have been more user-friendly outputs. Overall, it achieved the task \u001b[0m\n",
"\u001b[32meffectively but less efficiently than trajectory 2.\"\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.8\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'4'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'This trajectory attempted to perform the task but encountered errors in SQL execution \u001b[0m\n",
"\u001b[32mrelated to column names that do not exist. It failed to compute the required headcount and total payroll, thereby \u001b[0m\n",
"\u001b[32mnot achieving the goal. It did show some understanding of the underlying data structure but did not progress \u001b[0m\n",
"\u001b[32msubstantially towards the desired outcome.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.2\u001b[0m\n",
" \u001b[1m}\u001b[0m\n",
" \u001b[1m]\u001b[0m\n",
"\u001b[1m}\u001b[0m\n"
]
},
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"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
"<span style=\"font-weight: bold\">[</span>RULER<span style=\"font-weight: bold\">]</span> Pretty-printed LLM choice JSON:\n",
"</pre>\n"
],
"text/plain": [
"\n",
"\u001b[1m[\u001b[0mRULER\u001b[1m]\u001b[0m Pretty-printed LLM choice JSON:\n"
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{
"data": {
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'scores'</span>: <span style=\"font-weight: bold\">[</span>\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'1'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'The trajectory outlines a logical procedure but does not proceed to identify which </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">departments have no employees. It stops short of analyzing the relationship between departments and employees.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.3</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'2'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'This trajectory makes progress by aiming to analyze the relevant tables but encounters </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">an error in the query which is a major setback. It shows an understanding of the task but fails to complete it </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">successfully.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.4</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'3'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'The trajectory successfully identifies the relevant tables and describes the employees </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">table correctly. However, the final query results show that it did not effectively check the department </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">associations, missing the opportunity to provide a proper conclusion.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'4'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'This trajectory efficiently identifies the tables, examines the employees for linked </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">department IDs, and executes queries that lead to a comprehensive conclusion about the departments with no assigned</span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">employees. It successfully summarizes the findings, demonstrating a clear understanding of the task and successful </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">data retrieval.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span>\n",
" <span style=\"font-weight: bold\">}</span>\n",
" <span style=\"font-weight: bold\">]</span>\n",
"<span style=\"font-weight: bold\">}</span>\n",
"</pre>\n"
],
"text/plain": [
"\u001b[1m{\u001b[0m\n",
" \u001b[32m'scores'\u001b[0m: \u001b[1m[\u001b[0m\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'1'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'The trajectory outlines a logical procedure but does not proceed to identify which \u001b[0m\n",
"\u001b[32mdepartments have no employees. It stops short of analyzing the relationship between departments and employees.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.3\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'2'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'This trajectory makes progress by aiming to analyze the relevant tables but encounters \u001b[0m\n",
"\u001b[32man error in the query which is a major setback. It shows an understanding of the task but fails to complete it \u001b[0m\n",
"\u001b[32msuccessfully.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.4\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'3'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'The trajectory successfully identifies the relevant tables and describes the employees \u001b[0m\n",
"\u001b[32mtable correctly. However, the final query results show that it did not effectively check the department \u001b[0m\n",
"\u001b[32massociations, missing the opportunity to provide a proper conclusion.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.5\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'4'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'This trajectory efficiently identifies the tables, examines the employees for linked \u001b[0m\n",
"\u001b[32mdepartment IDs, and executes queries that lead to a comprehensive conclusion about the departments with no assigned\u001b[0m\n",
"\u001b[32memployees. It successfully summarizes the findings, demonstrating a clear understanding of the task and successful \u001b[0m\n",
"\u001b[32mdata retrieval.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m1.0\u001b[0m\n",
" \u001b[1m}\u001b[0m\n",
" \u001b[1m]\u001b[0m\n",
"\u001b[1m}\u001b[0m\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m starting train\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m /tmp/ipykernel_75472/1714310424.py:52: DeprecationWarning: model.train() is deprecated. Use backend.train(model, ...) instead.\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Migration guide:\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m # Before (deprecated):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m await model.train(trajectory_groups, config=TrainConfig(learning_rate=5e-6))\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m # After (recommended):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m result = await backend.train(model, trajectory_groups, learning_rate=5e-6)\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m await model.log(trajectory_groups, metrics=result.metrics, step=result.step, split='train')\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Key differences:\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m - backend.train() does NOT automatically log trajectories or metrics\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m - backend.train() returns a TrainResult with step, metrics, and checkpoint info\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m - Each backend has its own type-checked parameters (no more generic config objects)\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m await model.train(\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Packed 8 trajectories into 4 sequences of length 2048\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "77bbd05b573248b4868a7605e3b041b7",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"train: 0%| | 0/4 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Gathering trajectory groups with RULER scoring...\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "1cb7b1b5925248ec83f0ec6175506b6b",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"train gather step 2: 0%| | 0/8 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50650 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50660 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50662 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50672 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50676 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50682 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50684 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50698 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50704 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50686 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50712 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50728 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50742 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50754 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50760 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50766 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50774 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50778 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50786 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50808 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50794 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50820 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50828 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50842 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50846 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50860 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50862 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50876 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50884 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50898 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50900 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50912 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50920 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50922 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50924 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50928 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50938 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50956 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50954 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50960 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50962 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50978 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:39] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:39] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List employees who are listed as project leads (lead_id in projects) along with the project(s) they lead. Then provide a summary and ...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:39] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:39] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:39] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List employees who are listed as project leads (lead_id in projects) along with the project(s) they lead. Then provide a summary and ...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:39] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50994 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50998 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:39] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:39] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List employees who are listed as project leads (lead_id in projects) along with the project(s) they lead. Then provide a summary and ...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50014 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50016 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50024 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:39] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50032 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:39] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:39] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List employees who are listed as project leads (lead_id in projects) along with the project(s) they lead. Then provide a summary and ...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:39] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:39] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:39] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: For each department, present location, budget, and the number of employees in that department. Then provide a summary and thorough an...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:39] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:39] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:39] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: For each department, present location, budget, and the number of employees in that department. Then provide a summary and thorough an...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:39] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:39] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:39] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: For each department, present location, budget, and the number of employees in that department. Then provide a summary and thorough an...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:39] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:39] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:39] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: For each department, present location, budget, and the number of employees in that department. Then provide a summary and thorough an...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:39] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:41] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='None'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:41] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50034 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50038 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50048 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50064 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50068 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50084 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:41] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:41] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List employees who are listed as project leads (lead_id in projects) along with the project(s) they lead. Then provide a summary and ...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:41] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:41] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='None'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:41] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:41] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='None'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:41] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50092 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50104 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50112 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50118 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50128 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50144 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50146 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50154 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50168 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50180 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50186 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:41] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:41] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List employees who are listed as project leads (lead_id in projects) along with the project(s) they lead. Then provide a summary and ...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:41] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50198 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:41] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:41] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List employees who are listed as project leads (lead_id in projects) along with the project(s) they lead. Then provide a summary and ...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:41] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:44] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='To proceed with your request, I first need to list all the tables available in the database to ensure we have access to the necessary data.\\n...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:44] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50208 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50222 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50228 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50234 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50236 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50252 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:44] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:44] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: For each department, present location, budget, and the number of employees in that department. Then provide a summary and thorough an...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:44] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:45] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"To address your request, I need to follow a few steps. First, I will list the tables present in the database to proceed with the analysis. Let's start by listing the tables.\\n...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:45] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50258 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50266 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50282 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50288 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50298 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50300 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:45] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:45] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List employees who are listed as project leads (lead_id in projects) along with the project(s) they lead. Then provide a summary and ...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:45] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:46] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"To proceed with your request, I first need to identify the relevant tables in our database that contain information about departments, locations, budgets, and employees. Let's start by listing the tab...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:46] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50310 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50324 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50338 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50340 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50350 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50360 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:46] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:46] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: For each department, present location, budget, and the number of employees in that department. Then provide a summary and thorough an...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:46] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:46] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"To proceed with the task, I first need to identify the relevant tables in the database that contain information about departments, their locations, budgets, and employee counts. Let's start by listing...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:46] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50364 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50366 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50368 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50372 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50382 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50398 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:46] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:46] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: For each department, present location, budget, and the number of employees in that department. Then provide a summary and thorough an...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:46] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:47] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"We have identified the following tables in the database: 'departments', 'employees', and 'projects'. Let's proceed by describing the 'employees' and 'projects' tables to understand their schema better...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:47] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:47] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The tables present in the database are 'departments', 'employees', and 'projects'. Next, I will proceed to describe the table 'employees' to determine which columns are relevant for our query.\\n...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:47] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50406 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50418 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50432 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50436 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50442 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50444 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50454 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50456 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50460 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50474 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50484 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50496 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:47] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:47] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List employees who are listed as project leads (lead_id in projects) along with the project(s) they lead. Then provide a summary and ...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:47] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:47] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:47] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List employees who are listed as project leads (lead_id in projects) along with the project(s) they lead. Then provide a summary and ...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:47] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:48] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"To proceed with your request, I need to first identify the tables that might contain the necessary data such as departments, their locations, budgets, and the number of employees. Let's list the table...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:48] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50816 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50832 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50834 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50844 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50856 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50872 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:48] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:48] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50878 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50890 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50894 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50906 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50914 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50922 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:48] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:48] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: For each department, present location, budget, and the number of employees in that department. Then provide a summary and thorough an...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:48] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 5,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:51] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"We have listed the tables in the database as 'departments', 'employees', and 'projects'. Now, let's proceed with describing these tables to determine the necessary columns.\\n...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:51] Tool call received | name='describe_table' raw_args='{\"table_name\": \"departments\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50924 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50936 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50950 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50960 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50972 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50976 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:51] Tool result | name='describe_table' len=395\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:51] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50990 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50002 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50014 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50016 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50020 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50024 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:51] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:51] Tool call received | name='describe_table' raw_args='{\"table_name\": \"projects\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50032 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50040 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50044 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50056 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50072 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50082 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:51] Tool result | name='describe_table' len=603\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:51] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List employees who are listed as project leads (lead_id in projects) along with the project(s) they lead. Then provide a summary and ...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:51] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 8,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:53] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='The database contains three tables: `departments`, `employees`, and `projects`. Next, I will describe the `employees` table to understand its structure and identify relevant columns like `employee_id`...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:53] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50096 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50100 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50104 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50114 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50118 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50132 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:53] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:53] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List employees who are listed as project leads (lead_id in projects) along with the project(s) they lead. Then provide a summary and ...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:53] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:55] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='The database contains three tables: `departments`, `employees`, and `projects`. Given this information, to answer your query, we can only use the `departments` and `employees` tables because `projects...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:55] Tool call received | name='describe_table' raw_args='{\"table_name\": \"departments\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50146 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50160 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50174 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50190 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50198 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50208 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:55] Tool result | name='describe_table' len=395\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:55] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: For each department, present location, budget, and the number of employees in that department. Then provide a summary and thorough an...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:55] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:59] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='The database contains three tables: `departments`, `employees`, and `projects`. For your query, we are particularly interested in the `departments` table which should contain information about departm...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:59] Tool call received | name='describe_table' raw_args='{\"table_name\": \"departments\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50802 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50808 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50810 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50826 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50830 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50834 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:59] Tool result | name='describe_table' len=395\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:59] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: For each department, present location, budget, and the number of employees in that department. Then provide a summary and thorough an...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:52:59] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:53:02] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The table 'employees' has columns like id, name, department_id, role, salary, and hire_date. From this information, we should focus on the columns 'id' and 'name' for identifying employees. Now, let's...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:53:02] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT e.id, e.name, p.project_id, p.project_name FROM employees e JOIN projects p ON e.id = p.employee_id\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50836 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50840 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50850 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50862 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50868 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50870 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:53:02] Tool result | name='run_query' len=41\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:53:02] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The 'employees' table has the following columns:\\n- id: A unique identifier for each employee, auto-incremented, not null, and serves as the primary key.\\n- name: The name of the employee, not null.\\n- d...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:53:02] Tool call received | name='describe_table' raw_args='{\"table_name\": \"projects\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50882 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50884 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50900 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50902 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50908 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50914 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:53:02] Tool result | name='describe_table' len=603\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:53:03] LLM response parsed | finish_reason='stop' has_tool_calls=False content_preview=\"The database contains three tables: 'departments', 'employees', and 'projects'. It seems the 'departments' table includes details about departments such as location, budget, and possibly an ID or key ...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:53:03] LLM returned no tool_calls; skipping tool execution | turn=2\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:53:03] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: For each department, present location, budget, and the number of employees in that department. Then provide a summary and thorough an...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:53:03] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 5,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:53:08] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='The database contains three tables: `departments`, `employees`, and `projects`. To fulfill your request, we will mainly look into the `departments` table for department IDs, and then join it with the ...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:53:08] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT departments.department_id, departments.location, departments.budget, COUNT(employees.id) as employee_count FROM departments LEFT JOIN employees ON departments.department_id = employees.department_id GROUP BY departments.department_id, departments.location, departments.budget ORDER BY departments.department_id\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50928 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50934 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50912 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50930 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50932 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50938 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:53:08] Tool result | name='run_query' len=54\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:53:08] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: For each department, present location, budget, and the number of employees in that department. Then provide a summary and thorough an...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:53:08] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 7,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:53:09] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='None'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:53:09] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT d.location, d.budget, COUNT(e.employee_id) AS employee_count FROM departments d JOIN employees e ON d.department_id = e.department_id GROUP BY d.department_id, d.location, d.budget\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50940 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50946 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50958 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50970 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50982 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50994 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:53:09] Tool result | name='run_query' len=42\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:53:10] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='The `departments` table includes columns such as `id`, `name`, `location`, `budget`, and `primary_key` set to both `id` and `name`. These columns seem relevant for constructing the required summary an...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:53:10] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT d.name, d.location, d.budget, COUNT(e.id) as employee_count FROM departments d JOIN employees e ON d.id = e.department_id GROUP BY d.name, d.location, d.budget\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50000 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50002 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50018 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50028 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50040 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50042 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:53:10] Tool result | name='run_query' len=662\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:53:15] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='The `employees` table has the following columns: \\n- `id`: An integer, nullable, and primary key.\\n- `name`: A text, not nullable, and not a primary key.\\n- `department_id`: An integer, nullable, and not...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:53:15] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT project_id FROM projects WHERE lead_id IN (SELECT id FROM employees)\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50048 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50064 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50078 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50088 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50090 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50104 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:53:15] Tool result | name='run_query' len=39\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:53:15] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='The descriptive information for each table is as follows:\\n- **departments**: The table contains columns for `id`, `name`, `location`, and `budget`.\\n- **employees**: The table contains columns for `id`...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:53:15] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT e.name AS employee_name, p.name AS project_name FROM employees e JOIN projects p ON e.id = p.lead_id;\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50118 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50134 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50146 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50158 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50170 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50178 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:53:15] Tool result | name='run_query' len=775\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:53:22] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='The `departments` table includes the following columns that are relevant to our request:\\n- `id` (an INTEGER, primary key with a non-null constraint)\\n- `name` (a TEXT, primary key with a non-null const...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:53:22] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT d.name AS department_name, d.location, d.budget, COUNT(e.id) AS employee_count FROM departments d LEFT JOIN employee_department ed ON d.id = ed.department_id LEFT JOIN employees e ON ed.employee_id = e.id GROUP BY d.name, d.location, d.budget\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50794 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50796 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50800 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50806 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50816 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50828 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:53:22] Tool result | name='run_query' len=47\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:53:26] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"It appears there is an issue as the column `department_id` does not exist in the `departments` table. However, there seems to be a similar column in the `employees` table. Let's retry the query using ...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:53:26] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT departments.department_id, departments.location, departments.budget, COUNT(employees.employee_id) as employee_count FROM departments LEFT JOIN employees ON departments.department_id = employees.department_id GROUP BY departments.department_id, departments.location, departments.budget ORDER BY departments.department_id\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50834 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50840 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50856 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50860 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50870 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50884 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:53:26] Tool result | name='run_query' len=54\n"
]
},
{
"data": {
"text/html": [
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"<span style=\"font-weight: bold\">[</span>RULER<span style=\"font-weight: bold\">]</span> Pretty-printed LLM choice JSON:\n",
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"\u001b[1m[\u001b[0mRULER\u001b[1m]\u001b[0m Pretty-printed LLM choice JSON:\n"
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"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'scores'</span>: <span style=\"font-weight: bold\">[</span>\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'1'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">\"The trajectory listed the tables and described the 'employees' table, but an error </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">occurred when attempting to run the query due to incorrect column references. It did not successfully complete the </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">task, but advanced somewhat in understanding the schema.\"</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.3</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'2'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">\"This trajectory listed the tables correctly, described the 'employees' table, and began</span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">to investigate the 'projects' table but did not proceed to fetch any results. Although it gathered relevant schema </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">information, it did not lead to a successful query execution.\"</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.4</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'3'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">\"This trajectory identified the tables and described the 'employees' table, but unlike </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">trajectory 2, it ran an incorrect SQL query which resulted in an error. It progressed towards task completion but </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">ultimately failed to yield useful results.\"</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.3</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'4'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'This trajectory correctly identified, described, and comprehensively understood the </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">necessary tables. It successfully executed a query that produced a full result set of employees and their </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">respective projects, effectively completing the task as required.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span>\n",
" <span style=\"font-weight: bold\">}</span>\n",
" <span style=\"font-weight: bold\">]</span>\n",
"<span style=\"font-weight: bold\">}</span>\n",
"</pre>\n"
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" \u001b[32m'scores'\u001b[0m: \u001b[1m[\u001b[0m\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'1'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m\"The trajectory listed the tables and described the 'employees' table, but an error \u001b[0m\n",
"\u001b[32moccurred when attempting to run the query due to incorrect column references. It did not successfully complete the \u001b[0m\n",
"\u001b[32mtask, but advanced somewhat in understanding the schema.\"\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.3\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'2'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m\"This trajectory listed the tables correctly, described the 'employees' table, and began\u001b[0m\n",
"\u001b[32mto investigate the 'projects' table but did not proceed to fetch any results. Although it gathered relevant schema \u001b[0m\n",
"\u001b[32minformation, it did not lead to a successful query execution.\"\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.4\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'3'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m\"This trajectory identified the tables and described the 'employees' table, but unlike \u001b[0m\n",
"\u001b[32mtrajectory 2, it ran an incorrect SQL query which resulted in an error. It progressed towards task completion but \u001b[0m\n",
"\u001b[32multimately failed to yield useful results.\"\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.3\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'4'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'This trajectory correctly identified, described, and comprehensively understood the \u001b[0m\n",
"\u001b[32mnecessary tables. It successfully executed a query that produced a full result set of employees and their \u001b[0m\n",
"\u001b[32mrespective projects, effectively completing the task as required.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m1.0\u001b[0m\n",
" \u001b[1m}\u001b[0m\n",
" \u001b[1m]\u001b[0m\n",
"\u001b[1m}\u001b[0m\n"
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"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
"<span style=\"font-weight: bold\">[</span>RULER<span style=\"font-weight: bold\">]</span> Pretty-printed LLM choice JSON:\n",
"</pre>\n"
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"\n",
"\u001b[1m[\u001b[0mRULER\u001b[1m]\u001b[0m Pretty-printed LLM choice JSON:\n"
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"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'scores'</span>: <span style=\"font-weight: bold\">[</span>\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'1'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">\"This trajectory starts the process but encounters an error when querying because it </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">uses an incorrect column name for employee IDs from the 'employees' table. As a result, it does not complete the </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">task successfully.\"</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.2</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'2'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">\"This trajectory successfully describes the departments table and formulates a correct </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">query syntax to retrieve the necessary information, avoiding errors and achieving the task's goal. It delivers </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">meaningful results, including department locations, budgets, and employee counts.\"</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'3'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">\"This trajectory outlines the process correctly but fails at the query stage due to an </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">assumption about a non-existent 'employee_department' table. It does not complete the task effectively as no </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">results are returned.\"</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.3</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'4'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'This trajectory attempts to gather necessary data, but it encounters continuous errors </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">related to non-existent columns. It shows a lack of clarity regarding table and column names, preventing it from </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">completing the task effectively.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.4</span>\n",
" <span style=\"font-weight: bold\">}</span>\n",
" <span style=\"font-weight: bold\">]</span>\n",
"<span style=\"font-weight: bold\">}</span>\n",
"</pre>\n"
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"\u001b[1m{\u001b[0m\n",
" \u001b[32m'scores'\u001b[0m: \u001b[1m[\u001b[0m\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'1'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m\"This trajectory starts the process but encounters an error when querying because it \u001b[0m\n",
"\u001b[32muses an incorrect column name for employee IDs from the 'employees' table. As a result, it does not complete the \u001b[0m\n",
"\u001b[32mtask successfully.\"\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.2\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'2'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m\"This trajectory successfully describes the departments table and formulates a correct \u001b[0m\n",
"\u001b[32mquery syntax to retrieve the necessary information, avoiding errors and achieving the task's goal. It delivers \u001b[0m\n",
"\u001b[32mmeaningful results, including department locations, budgets, and employee counts.\"\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m1.0\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'3'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m\"This trajectory outlines the process correctly but fails at the query stage due to an \u001b[0m\n",
"\u001b[32massumption about a non-existent 'employee_department' table. It does not complete the task effectively as no \u001b[0m\n",
"\u001b[32mresults are returned.\"\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.3\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'4'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'This trajectory attempts to gather necessary data, but it encounters continuous errors \u001b[0m\n",
"\u001b[32mrelated to non-existent columns. It shows a lack of clarity regarding table and column names, preventing it from \u001b[0m\n",
"\u001b[32mcompleting the task effectively.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.4\u001b[0m\n",
" \u001b[1m}\u001b[0m\n",
" \u001b[1m]\u001b[0m\n",
"\u001b[1m}\u001b[0m\n"
]
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"text": [
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m starting train\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Packed 8 trajectories into 4 sequences of length 2048\n"
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"train: 0%| | 0/4 [00:00<?, ?it/s]"
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"text": [
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Gathering trajectory groups with RULER scoring...\n"
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"model_id": "8863623622b34006804002a7ac03c703",
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"text/plain": [
"train gather step 3: 0%| | 0/8 [00:00<?, ?it/s]"
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"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50506 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50522 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50526 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50538 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50546 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50556 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50570 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50574 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50586 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50588 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50594 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50610 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50616 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50618 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50620 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50634 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50650 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50666 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50670 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50676 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50686 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50702 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50712 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50718 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50724 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50732 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50738 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50744 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50746 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50762 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50772 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50788 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50794 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50806 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50816 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50822 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50836 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50844 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50860 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50852 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50884 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50876 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:06] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:06] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: In the Marketing department, count hires after 2020 and report the average salary of those hires. Then generate a summary and a thoro...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:06] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:06] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:06] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: In the Marketing department, count hires after 2020 and report the average salary of those hires. Then generate a summary and a thoro...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50890 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:06] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50896 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50898 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:06] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:06] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: In the Marketing department, count hires after 2020 and report the average salary of those hires. Then generate a summary and a thoro...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:06] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50904 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:06] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:06] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: In the Marketing department, count hires after 2020 and report the average salary of those hires. Then generate a summary and a thoro...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:06] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50920 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:06] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:06] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List employees whose salary exceeds the average salary for their own department. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50924 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:06] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:06] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:06] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List employees whose salary exceeds the average salary for their own department. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:06] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:06] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:06] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List employees whose salary exceeds the average salary for their own department. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:06] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:06] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:06] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List employees whose salary exceeds the average salary for their own department. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:06] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:08] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='None'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:08] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:08] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='None'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:08] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:08] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='None'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:08] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50576 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50584 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50588 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50604 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50620 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50628 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50632 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50644 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50650 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50662 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50674 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50684 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50686 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50702 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50712 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50720 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50730 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:08] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:08] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List employees whose salary exceeds the average salary for their own department. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:08] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:08] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:08] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List employees whose salary exceeds the average salary for their own department. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:08] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50740 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:08] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:08] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List employees whose salary exceeds the average salary for their own department. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:08] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:11] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"To proceed with your request, I first need to identify the table containing the hiring information and the salary details relevant to the Marketing department. Let's start by listing available tables....\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:11] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50746 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50756 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50772 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50776 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50790 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50806 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:11] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:11] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: In the Marketing department, count hires after 2020 and report the average salary of those hires. Then generate a summary and a thoro...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:11] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:12] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"To proceed with your request, I need to first list the tables in the database to identify the ones that might contain employee data and department information. Let's start by listing the tables.\\n...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:12] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50812 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50828 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50844 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50854 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50866 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50876 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:12] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:12] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List employees whose salary exceeds the average salary for their own department. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:12] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:12] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"To accomplish the task, we first need to identify the relevant table where hiring data and salaries are stored. Let's start by listing the tables in the database to find the most suitable table.\\n\\n...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:12] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50892 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50908 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50924 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50928 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50938 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50942 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:12] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:12] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: In the Marketing department, count hires after 2020 and report the average salary of those hires. Then generate a summary and a thoro...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:12] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:14] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The database contains the following tables: 'departments', 'employees', 'projects'. I will now proceed to analyze the 'employees' table to find those whose salary exceeds the average salary for their ...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:14] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50950 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50954 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50956 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50966 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50974 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50982 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:14] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:14] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List employees whose salary exceeds the average salary for their own department. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:14] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:14] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='None'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:14] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50996 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50006 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50008 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50022 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50034 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50046 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:14] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:14] Tool call received | name='describe_table' raw_args='{\"table_name\": \"departments\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50056 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50072 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50074 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50082 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50098 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50104 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:14] Tool result | name='describe_table' len=395\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:14] Tool call received | name='describe_table' raw_args='{\"table_name\": \"projects\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50110 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50126 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50138 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50140 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50152 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50160 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:14] Tool result | name='describe_table' len=603\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:14] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List employees whose salary exceeds the average salary for their own department. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:14] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 8,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:15] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"We have three tables: 'departments', 'employees', and 'projects'. Let's first proceed with fetching the necessary data to determine the average salary for each department and identify employees who ea...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:15] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT AVG(salary) FROM employees;\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50164 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50176 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50186 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50188 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50192 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50206 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:15] Tool result | name='run_query' len=92\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:15] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List employees whose salary exceeds the average salary for their own department. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:15] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:19] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='To accomplish the task of counting hires after 2020 and then calculating the average salary for those hires, we first need to know the table where the hiring information is stored. Since the detailed ...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:19] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50386 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50396 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50410 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50426 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50430 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50446 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:19] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:19] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: In the Marketing department, count hires after 2020 and report the average salary of those hires. Then generate a summary and a thoro...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:19] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:20] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The available tables in the database are 'departments', 'employees', and 'projects'. Next, I will check the 'employees' table to find out which department it contains information about, as well as any...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:20] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:20] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The database contains three tables: 'departments', 'employees', and 'projects'. We need to find the 'employees' table, which should have the necessary hiring information and salaries.\\n\\nNext, I will de...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:20] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50462 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50476 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50488 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50502 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50514 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50516 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50526 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50536 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50546 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50562 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50576 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:20] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:20] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: In the Marketing department, count hires after 2020 and report the average salary of those hires. Then generate a summary and a thoro...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:20] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50584 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:20] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:20] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: In the Marketing department, count hires after 2020 and report the average salary of those hires. Then generate a summary and a thoro...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:20] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:22] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='To proceed with the task of counting hires in the Marketing department that occurred after 2020 and reporting the average salary of these hires, I need to follow these steps:\\n\\n1. List all tables in th...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:22] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50592 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50596 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50612 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50620 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50630 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50638 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:22] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:22] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: In the Marketing department, count hires after 2020 and report the average salary of those hires. Then generate a summary and a thoro...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:22] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:24] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The database contains three tables: 'departments', 'employees', and 'projects'. Now, we will focus on 'employees' and 'departments' to determine the relevant columns and perform the query.\\n\\nFirst, I w...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:24] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50652 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50666 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50672 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50688 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50692 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50700 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:24] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:24] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List employees whose salary exceeds the average salary for their own department. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:24] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:28] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='The table `employees` has the following columns: \\n- `id`: Integer, not nullable, serves as the primary key.\\n- `name`: Text, not nullable.\\n- `department_id`: Integer, nullable.\\n- `role`: Text, not null...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:28] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT AVG(salary) OVER (PARTITION BY department_id) AS avg_dept_salary, department_id FROM employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50368 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50370 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50382 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50390 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50404 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50406 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:28] Tool result | name='run_query' len=1193\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:29] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The database contains the following tables: 'departments', 'employees', and 'projects'. \\n\\nNext, I will describe the 'employees' table to check its columns and find out if it includes relevant data suc...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:29] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50410 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50422 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50436 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50446 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50460 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:29] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:29] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: In the Marketing department, count hires after 2020 and report the average salary of those hires. Then generate a summary and a thoro...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50476 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:29] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:31] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"Based on the descriptions we fetched, here's what we know about our tables:\\n1. **Employees**: Contains employee information including ID, name, department ID, role, salary, and hire date.\\n2. **Departm...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:31] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT AVG(salary), d.id AS department_id FROM employees e JOIN departments d ON e.department_id = d.id GROUP BY d.id;\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50482 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50498 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50512 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50528 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50538 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50548 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:31] Tool result | name='run_query' len=403\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:33] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='The database contains three tables: `departments`, `employees`, and `projects`. Given these tables, we assume that `employees` table would contain columns relevant to hiring information including `hir...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:33] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50558 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50574 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50586 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50600 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50608 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50610 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:33] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:33] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: In the Marketing department, count hires after 2020 and report the average salary of those hires. Then generate a summary and a thoro...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:33] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:34] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='The average salary for all employees is approximately 123,866.67. Next, to find employees who earn more than this average salary, we will use the following SQL query:\\n\\n```sql\\nSELECT e.* \\nFROM employee...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:34] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT e.* FROM employees e JOIN (SELECT department_id, AVG(salary) AS avg_salary FROM employees GROUP BY department_id) dept_avg_salary ON e.department_id = dept_avg_salary.department_id WHERE e.salary > dept_avg_salary.avg_salary;\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50624 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50638 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50644 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50648 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50664 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50678 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:34] Tool result | name='run_query' len=1266\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:34] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The 'employees' table has columns such as 'id', 'name', 'department_id', 'role', 'salary', and 'hire_date'. We can see that the 'department_id' column seems to indicate the department where each emplo...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:34] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT AVG(salary) as average_salary FROM employees WHERE department_id = (SELECT id FROM departments WHERE name = \\'Marketing\\') AND hire_date > \\'2020-12-31\\';\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50680 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50694 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50702 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50716 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50726 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50742 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:34] Tool result | name='run_query' len=85\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:38] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The 'employees' table has the following columns:\\n- id: An integer that serves as a Primary Key.\\n- name: A text field that won't be null.\\n- department_id: An integer field that can be null.\\n- role: A t...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:38] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT AVG(salary) FROM employees WHERE hire_date > \\'2020-12-31\\'\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50224 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50234 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50236 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50244 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50254 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50264 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:38] Tool result | name='run_query' len=92\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:40] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The 'employees' table has the following relevant columns:\\n\\n- `id`: This is likely the auto-incrementing primary key.\\n- `name`: The employee's name.\\n- `department_id`: This presumably holds the departm...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:40] Tool call received | name='describe_table' raw_args='{\"table_name\": \"departments\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50280 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50284 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50298 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50312 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50324 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50336 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:40] Tool result | name='describe_table' len=395\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:45] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='The `employees` table contains the necessary columns: `id`, `name`, `department_id`, `role`, `salary`, and `hire_date`. We can now proceed with counting hires after 2020 and determining the average sa...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:45] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT COUNT(*) as hire_count, AVG(salary) as average_salary FROM employees WHERE hire_date > \\'2020-01-01\\';\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50352 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50354 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50366 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50382 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50394 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50400 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:54:45] Tool result | name='run_query' len=109\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:04] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The 'employees' table contains the following relevant fields: \\n\\n- id: The employee's unique identifier (integer, primary key, non-null).\\n- name: The employee's name (text, non-null).\\n- department_id: ...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:04] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT COUNT(*) AS hire_count, AVG(salary) AS avg_salary FROM employees WHERE department_id = (SELECT id FROM departments WHERE name = \\'Marketing\\') AND YEAR(hire_date) > 2020\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50296 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50306 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50312 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50316 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50318 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50328 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:04] Tool result | name='run_query' len=35\n"
]
},
{
"data": {
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"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
"<span style=\"font-weight: bold\">[</span>RULER<span style=\"font-weight: bold\">]</span> Pretty-printed LLM choice JSON:\n",
"</pre>\n"
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"text/plain": [
"\n",
"\u001b[1m[\u001b[0mRULER\u001b[1m]\u001b[0m Pretty-printed LLM choice JSON:\n"
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"data": {
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'scores'</span>: <span style=\"font-weight: bold\">[</span>\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'1'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'Successfully counted hires in the Marketing department after 2020 and calculated the </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">average salary, returning a salary figure. Only the average salary was produced, missing the actual count.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.8</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'2'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'Counted all hires after 2020 without specifying the department, yielding an average </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">salary that does not meet the user requirement focused on Marketing hires. This makes it less aligned with the </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">goal.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'3'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">\"Attempted to work with estimates and assumptions but lacked specificity on counting by </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">department. Did not provide direct results relevant to the user's specific request about Marketing hires after </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">2020.\"</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.4</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'4'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'Advanced through understanding and building up the response but failed to execute the </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">query accurately due to a syntax issue. Did not fulfill the request to report the average salary as required, </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">affecting overall effectiveness.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.3</span>\n",
" <span style=\"font-weight: bold\">}</span>\n",
" <span style=\"font-weight: bold\">]</span>\n",
"<span style=\"font-weight: bold\">}</span>\n",
"</pre>\n"
],
"text/plain": [
"\u001b[1m{\u001b[0m\n",
" \u001b[32m'scores'\u001b[0m: \u001b[1m[\u001b[0m\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'1'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'Successfully counted hires in the Marketing department after 2020 and calculated the \u001b[0m\n",
"\u001b[32maverage salary, returning a salary figure. Only the average salary was produced, missing the actual count.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.8\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'2'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'Counted all hires after 2020 without specifying the department, yielding an average \u001b[0m\n",
"\u001b[32msalary that does not meet the user requirement focused on Marketing hires. This makes it less aligned with the \u001b[0m\n",
"\u001b[32mgoal.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.5\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'3'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m\"Attempted to work with estimates and assumptions but lacked specificity on counting by \u001b[0m\n",
"\u001b[32mdepartment. Did not provide direct results relevant to the user's specific request about Marketing hires after \u001b[0m\n",
"\u001b[32m2020.\"\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.4\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'4'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'Advanced through understanding and building up the response but failed to execute the \u001b[0m\n",
"\u001b[32mquery accurately due to a syntax issue. Did not fulfill the request to report the average salary as required, \u001b[0m\n",
"\u001b[32maffecting overall effectiveness.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.3\u001b[0m\n",
" \u001b[1m}\u001b[0m\n",
" \u001b[1m]\u001b[0m\n",
"\u001b[1m}\u001b[0m\n"
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"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
"<span style=\"font-weight: bold\">[</span>RULER<span style=\"font-weight: bold\">]</span> Pretty-printed LLM choice JSON:\n",
"</pre>\n"
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"\n",
"\u001b[1m[\u001b[0mRULER\u001b[1m]\u001b[0m Pretty-printed LLM choice JSON:\n"
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"data": {
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'scores'</span>: <span style=\"font-weight: bold\">[</span>\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'1'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">\"This trajectory correctly starts by listing the tables and then describes the </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">'employees' table. However, it fails to run the final query to actually retrieve the employees exceeding the </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">departmental average salary. It only reaches the average salary computation step. Similar to others but it stops </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">short of completing the task.\"</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'2'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">\"This trajectory lists tables and describes the 'employees' and 'departments' tables but</span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">doesn't run the final queries needed to meet the user's goal of finding employees whose salary exceeds the average </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">salary in their department. It is incomplete, similar to trajectory 1, but had more steps.\"</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.4</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'3'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">\"This trajectory successfully lists the tables, describes the 'employees' table, </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">computes the overall average salary first (less efficient), and finally runs the necessary query to find employees </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">who make more than the departmental average salary, achieving the goal. It completes the task efficiently and </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">correctly.\"</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'4'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">\"This trajectory begins by listing the tables and describing the relevant 'employees' </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">and 'departments' tables, but it fails to run any queries afterward to actually find employees whose salary exceeds</span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">the average in their departments. It shows a clear understanding of the necessary steps but falls short in </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">execution.\"</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.4</span>\n",
" <span style=\"font-weight: bold\">}</span>\n",
" <span style=\"font-weight: bold\">]</span>\n",
"<span style=\"font-weight: bold\">}</span>\n",
"</pre>\n"
],
"text/plain": [
"\u001b[1m{\u001b[0m\n",
" \u001b[32m'scores'\u001b[0m: \u001b[1m[\u001b[0m\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'1'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m\"This trajectory correctly starts by listing the tables and then describes the \u001b[0m\n",
"\u001b[32m'employees' table. However, it fails to run the final query to actually retrieve the employees exceeding the \u001b[0m\n",
"\u001b[32mdepartmental average salary. It only reaches the average salary computation step. Similar to others but it stops \u001b[0m\n",
"\u001b[32mshort of completing the task.\"\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.5\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'2'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m\"This trajectory lists tables and describes the 'employees' and 'departments' tables but\u001b[0m\n",
"\u001b[32mdoesn't run the final queries needed to meet the user's goal of finding employees whose salary exceeds the average \u001b[0m\n",
"\u001b[32msalary in their department. It is incomplete, similar to trajectory 1, but had more steps.\"\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.4\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'3'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m\"This trajectory successfully lists the tables, describes the 'employees' table, \u001b[0m\n",
"\u001b[32mcomputes the overall average salary first \u001b[0m\u001b[32m(\u001b[0m\u001b[32mless efficient\u001b[0m\u001b[32m)\u001b[0m\u001b[32m, and finally runs the necessary query to find employees \u001b[0m\n",
"\u001b[32mwho make more than the departmental average salary, achieving the goal. It completes the task efficiently and \u001b[0m\n",
"\u001b[32mcorrectly.\"\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m1.0\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'4'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m\"This trajectory begins by listing the tables and describing the relevant 'employees' \u001b[0m\n",
"\u001b[32mand 'departments' tables, but it fails to run any queries afterward to actually find employees whose salary exceeds\u001b[0m\n",
"\u001b[32mthe average in their departments. It shows a clear understanding of the necessary steps but falls short in \u001b[0m\n",
"\u001b[32mexecution.\"\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.4\u001b[0m\n",
" \u001b[1m}\u001b[0m\n",
" \u001b[1m]\u001b[0m\n",
"\u001b[1m}\u001b[0m\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m starting train\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Packed 7 trajectories into 4 sequences of length 2048\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "60752d2af0a245de9d5dd90fa8f8b72c",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"train: 0%| | 0/4 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Gathering trajectory groups with RULER scoring...\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "681437f942ba4348a986b852d4cf49b2",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"train gather step 4: 0%| | 0/8 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50034 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50046 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50060 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50066 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50082 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50090 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50098 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50102 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50114 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50126 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50130 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50146 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50156 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50170 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50184 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50186 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50200 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50210 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50216 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50218 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50226 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50240 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50256 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50266 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50278 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50294 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50302 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50318 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50326 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50336 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50352 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50356 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50372 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50384 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50400 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50412 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50416 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50418 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50440 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50424 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50428 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:49] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:49] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Describe the departments table (column names, data types, and constraints) and provide a concise interpretation of how the table supp...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:49] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50444 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50448 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50462 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:49] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:49] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Describe the departments table (column names, data types, and constraints) and provide a concise interpretation of how the table supp...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:49] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:49] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:49] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Describe the departments table (column names, data types, and constraints) and provide a concise interpretation of how the table supp...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:49] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:49] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:49] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Describe the departments table (column names, data types, and constraints) and provide a concise interpretation of how the table supp...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:49] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50464 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50466 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50472 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50482 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:49] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:49] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List all tables in the database and then generate a summary of what was found, perform a basic data-usage analysis, and produce a fin...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:49] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:49] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:49] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List all tables in the database and then generate a summary of what was found, perform a basic data-usage analysis, and produce a fin...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:49] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:49] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:49] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List all tables in the database and then generate a summary of what was found, perform a basic data-usage analysis, and produce a fin...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:49] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:49] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:49] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List all tables in the database and then generate a summary of what was found, perform a basic data-usage analysis, and produce a fin...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:49] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:51] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='None'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:51] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50492 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50506 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50516 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50522 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50526 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50534 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:51] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:51] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Describe the departments table (column names, data types, and constraints) and provide a concise interpretation of how the table supp...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:51] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:51] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='None'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:51] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:51] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='None'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:51] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:51] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='None'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:51] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:51] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='None'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:51] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:51] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='None'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:51] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:51] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='None'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:51] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:51] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='None'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:51] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50536 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50542 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50550 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50554 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50560 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50572 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50582 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50584 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50586 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50592 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50604 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50608 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50614 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50622 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50632 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50646 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50656 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50672 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50680 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50690 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50694 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50710 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50724 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50726 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50730 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50740 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50748 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50760 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50776 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50792 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50800 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50808 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50822 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50848 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50852 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50832 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:52] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:52] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Describe the departments table (column names, data types, and constraints) and provide a concise interpretation of how the table supp...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:52] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:52] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:52] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Describe the departments table (column names, data types, and constraints) and provide a concise interpretation of how the table supp...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:52] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50856 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50864 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50880 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:52] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:52] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Describe the departments table (column names, data types, and constraints) and provide a concise interpretation of how the table supp...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:52] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:52] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:52] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List all tables in the database and then generate a summary of what was found, perform a basic data-usage analysis, and produce a fin...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:52] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50894 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50900 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:52] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:52] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List all tables in the database and then generate a summary of what was found, perform a basic data-usage analysis, and produce a fin...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:52] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:52] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:52] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List all tables in the database and then generate a summary of what was found, perform a basic data-usage analysis, and produce a fin...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:52] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:52] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:52] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List all tables in the database and then generate a summary of what was found, perform a basic data-usage analysis, and produce a fin...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:52] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:53] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='None'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:53] Tool call received | name='describe_table' raw_args='{\"table_name\": \"departments\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50904 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50906 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50918 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50934 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50936 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50946 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:53] Tool result | name='describe_table' len=395\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:53] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Describe the departments table (column names, data types, and constraints) and provide a concise interpretation of how the table supp...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:53] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:54] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='None'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:54] Tool call received | name='describe_table' raw_args='{\"table_name\": \"departments\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:54] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='None'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:54] Tool call received | name='describe_table' raw_args='{\"table_name\": \"departments\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50954 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50966 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50968 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50976 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50988 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50996 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50000 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50014 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50016 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50020 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50028 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50032 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:54] Tool result | name='describe_table' len=395\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:54] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Describe the departments table (column names, data types, and constraints) and provide a concise interpretation of how the table supp...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:54] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:54] Tool result | name='describe_table' len=395\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:54] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Describe the departments table (column names, data types, and constraints) and provide a concise interpretation of how the table supp...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:54] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:55] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='None'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:55] Tool call received | name='complete_task' raw_args='{\"summary\": \"Found the following tables in the database: departments, employees, and projects.\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:55] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='None'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:55] Tool call received | name='complete_task' raw_args='{\"summary\": \"The following tables were found in the database: departments, employees, and projects.\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:55] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='None'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:55] Tool call received | name='complete_task' raw_args='{\"summary\": \"The following tables were listed in the database: departments, employees, and projects.\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:56] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='None'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:56] Tool call received | name='complete_task' raw_args='{\"summary\": \"I have listed the following tables in the database: \\'departments\\', \\'employees\\', and \\'projects\\'.\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:57] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"Based on the list of tables, we have 'departments', 'employees', and 'projects'. We will start with 'departments' as requested.\\n\\n...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:57] Tool call received | name='describe_table' raw_args='{\"table_name\": \"departments\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50042 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50048 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50060 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50076 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50084 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50092 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:57] Tool result | name='describe_table' len=395\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:57] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Describe the departments table (column names, data types, and constraints) and provide a concise interpretation of how the table supp...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:55:57] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:00] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='None'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:00] Tool call received | name='complete_task' raw_args='{\"summary\": \"The departments table has been described including its columns (id, name, location, and budget) with their data types and constraints. The table supports budget planning by organizing departments hierarchically, allowing for allocation of budgets across different divisions.\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:05] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='None'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:05] Tool call received | name='complete_task' raw_args='{\"summary\": \"The departments table has been described with column names, data types, and constraints. The table has four columns: id, name, location, and budget. \\'id\\' is an integer that uniquely identifies each department. \\'name\\' and \\'location\\' are both text fields that cannot be null, storing the name and location information of each department, respectively. \\'budget\\' holds a real number (rounded to two decimal places) representing the budget allocated to the department.\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:16] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='The departments table contains information about each department in the organization including an id, name, location, and budget. \\n- id: An integer that uniquely identifies each department in the tabl...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:16] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT name, budget FROM departments WHERE id = 1 AND budget > 0.0;\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50884 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50890 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50900 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50916 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50928 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50934 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:16] Tool result | name='run_query' len=107\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:24] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The 'departments' table contains the following columns:\\n\\n- **id**: An INTEGER, with a primary key constraint and not null, used to uniquely identify each department.\\n- **name**: A TEXT type field whic...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:24] Tool call received | name='complete_task' raw_args='{\"summary\": \"I have identified and described the \\'departments\\' table. The table contains an INTEGER column \\'id\\' which acts as the primary key and is not null, a TEXT column \\'name\\' which again is the primary key and not null, a TEXT column \\'location\\' which is also not null, and a REAL column \\'budget\\' representing the budget allocated to each department which can\\'t be null. This table supports budget planning by structuring and recording the budget for each department.\"}'\n"
]
},
{
"data": {
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"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
"<span style=\"font-weight: bold\">[</span>RULER<span style=\"font-weight: bold\">]</span> Pretty-printed LLM choice JSON:\n",
"</pre>\n"
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"\u001b[1m[\u001b[0mRULER\u001b[1m]\u001b[0m Pretty-printed LLM choice JSON:\n"
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"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'scores'</span>: <span style=\"font-weight: bold\">[</span>\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'1'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">\"The agent effectively described the 'departments' table and provided insights on how </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">the table supports budget planning. The summary was clear and concise, and the task was completed efficiently.\"</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.9</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'2'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">\"The agent described the 'departments' table adequately, although the interpretation </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">regarding budget planning lacked depth compared to the first trajectory. However, the explanation was still clear </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">and acceptable.\"</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.75</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'3'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">\"The agent provided a detailed description of the 'departments' table and included a </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">thought process for running further queries. However, the trajectory was less efficient as it included unnecessary </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">steps and did not focus primarily on summarizing the table's implications for budget planning.\"</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.65</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'4'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">\"The agent provided a thorough description of the 'departments' table with clear details</span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">on each column. The analysis of how the table supports budget planning was somewhat comprehensive, though it </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">repeated similar points without offering new insights compared to the first.\"</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.7</span>\n",
" <span style=\"font-weight: bold\">}</span>\n",
" <span style=\"font-weight: bold\">]</span>\n",
"<span style=\"font-weight: bold\">}</span>\n",
"</pre>\n"
],
"text/plain": [
"\u001b[1m{\u001b[0m\n",
" \u001b[32m'scores'\u001b[0m: \u001b[1m[\u001b[0m\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'1'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m\"The agent effectively described the 'departments' table and provided insights on how \u001b[0m\n",
"\u001b[32mthe table supports budget planning. The summary was clear and concise, and the task was completed efficiently.\"\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.9\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'2'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m\"The agent described the 'departments' table adequately, although the interpretation \u001b[0m\n",
"\u001b[32mregarding budget planning lacked depth compared to the first trajectory. However, the explanation was still clear \u001b[0m\n",
"\u001b[32mand acceptable.\"\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.75\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'3'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m\"The agent provided a detailed description of the 'departments' table and included a \u001b[0m\n",
"\u001b[32mthought process for running further queries. However, the trajectory was less efficient as it included unnecessary \u001b[0m\n",
"\u001b[32msteps and did not focus primarily on summarizing the table's implications for budget planning.\"\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.65\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'4'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m\"The agent provided a thorough description of the 'departments' table with clear details\u001b[0m\n",
"\u001b[32mon each column. The analysis of how the table supports budget planning was somewhat comprehensive, though it \u001b[0m\n",
"\u001b[32mrepeated similar points without offering new insights compared to the first.\"\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.7\u001b[0m\n",
" \u001b[1m}\u001b[0m\n",
" \u001b[1m]\u001b[0m\n",
"\u001b[1m}\u001b[0m\n"
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{
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"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
"<span style=\"font-weight: bold\">[</span>RULER<span style=\"font-weight: bold\">]</span> Pretty-printed LLM choice JSON:\n",
"</pre>\n"
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"\n",
"\u001b[1m[\u001b[0mRULER\u001b[1m]\u001b[0m Pretty-printed LLM choice JSON:\n"
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{
"data": {
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'scores'</span>: <span style=\"font-weight: bold\">[</span>\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'1'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'The trajectory successfully listed the tables and provided a summary of the results. It</span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">was straightforward and efficient.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'2'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'This trajectory also successfully listed the tables and provided a summary, similar to </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">trajectory 1. There is no significant difference between them.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'3'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'This trajectory performed identically to the first two, successfully listing tables and</span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">summarizing them effectively. No differences in efficiency observed.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'4'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'Like the previous trajectories, this one listed the tables and provided a summary. </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">Chose to use slightly more verbose language but was equally effective.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>\n",
" <span style=\"font-weight: bold\">}</span>\n",
" <span style=\"font-weight: bold\">]</span>\n",
"<span style=\"font-weight: bold\">}</span>\n",
"</pre>\n"
],
"text/plain": [
"\u001b[1m{\u001b[0m\n",
" \u001b[32m'scores'\u001b[0m: \u001b[1m[\u001b[0m\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'1'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'The trajectory successfully listed the tables and provided a summary of the results. It\u001b[0m\n",
"\u001b[32mwas straightforward and efficient.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m1\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'2'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'This trajectory also successfully listed the tables and provided a summary, similar to \u001b[0m\n",
"\u001b[32mtrajectory 1. There is no significant difference between them.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m1\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'3'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'This trajectory performed identically to the first two, successfully listing tables and\u001b[0m\n",
"\u001b[32msummarizing them effectively. No differences in efficiency observed.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m1\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'4'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'Like the previous trajectories, this one listed the tables and provided a summary. \u001b[0m\n",
"\u001b[32mChose to use slightly more verbose language but was equally effective.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m1\u001b[0m\n",
" \u001b[1m}\u001b[0m\n",
" \u001b[1m]\u001b[0m\n",
"\u001b[1m}\u001b[0m\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m starting train\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Packed 3 trajectories into 1 sequences of length 2048\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "66700f1bc60445fe990d18f9dcaa011a",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"train: 0%| | 0/1 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Gathering trajectory groups with RULER scoring...\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "d8bf2d7fc26745aca21a360c79aea5c0",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"train gather step 5: 0%| | 0/8 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50910 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50918 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50924 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50938 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50942 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50944 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50966 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50970 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50946 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50950 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50984 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50000 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50010 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50026 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50032 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50046 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50050 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50068 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50062 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50078 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50084 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50086 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50100 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50108 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50122 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50136 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50138 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50150 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50160 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50164 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50172 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50182 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50188 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50196 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50208 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50212 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50218 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50226 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50230 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50248 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50234 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50262 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50270 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:49] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:49] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Calculate the total budget across all departments and the average department budget. Then provide a summary and a thorough report of ...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:49] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:49] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:49] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Calculate the total budget across all departments and the average department budget. Then provide a summary and a thorough report of ...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:49] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:49] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:49] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Calculate the total budget across all departments and the average department budget. Then provide a summary and a thorough report of ...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:49] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50276 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50278 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50294 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50302 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:49] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:49] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Find the most senior engineer (earliest hire_date) and show their name, role, and hire date. Then produce a summary and thorough anal...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50308 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:49] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:49] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:49] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Find the most senior engineer (earliest hire_date) and show their name, role, and hire date. Then produce a summary and thorough anal...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:49] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:49] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:49] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Calculate the total budget across all departments and the average department budget. Then provide a summary and a thorough report of ...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:49] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:49] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:49] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Find the most senior engineer (earliest hire_date) and show their name, role, and hire date. Then produce a summary and thorough anal...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:49] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:49] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:49] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Find the most senior engineer (earliest hire_date) and show their name, role, and hire date. Then produce a summary and thorough anal...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:49] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:55] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='Complete_task {\\n \"summary\": \"Executed SQL query to calculate total budget across all departments and average department budget. Provided the results in a detailed report.\"\\n}\\n...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:55] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50322 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50324 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50340 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50348 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50358 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50364 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:55] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:55] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Calculate the total budget across all departments and the average department budget. Then provide a summary and a thorough report of ...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:55] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:55] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='To proceed with your request, we first need to identify a table in the database that contains budget information for departments. I will start by listing all the tables in the database.\\n\\n...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:55] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50368 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50374 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50376 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50392 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50408 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50414 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:55] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:55] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Calculate the total budget across all departments and the average department budget. Then provide a summary and a thorough report of ...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:55] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:55] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"To calculate the total budget across all departments and the average department budget, we first need to identify the table that contains the budget information for each department. Let's start by lis...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:55] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50424 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50436 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50452 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50460 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50472 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50484 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:55] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:55] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Calculate the total budget across all departments and the average department budget. Then provide a summary and a thorough report of ...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:56] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:58] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='To proceed with finding the most senior engineer based on their hire date, I first need to list the tables in the database to identify the relevant ones that might contain information about engineers ...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:58] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50880 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50890 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50900 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50910 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50912 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50926 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:58] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:58] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50936 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50948 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50950 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50954 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50964 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50976 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:58] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:58] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Find the most senior engineer (earliest hire_date) and show their name, role, and hire date. Then produce a summary and thorough anal...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:56:58] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 5,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:00] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='To find the most senior engineer based on the earliest hire date, we need to follow these steps:\\n\\n1. List all the tables in the database.\\n2. Determine which table contains the roles and hire dates for...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:00] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50988 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50990 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50994 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50998 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50006 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50018 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:00] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:00] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Find the most senior engineer (earliest hire_date) and show their name, role, and hire date. Then produce a summary and thorough anal...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:00] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:01] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"We have identified the following tables in the database: 'departments', 'employees', and 'projects'. Now, we need to proceed with the analysis starting from the 'departments' table.\\n...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:01] Tool call received | name='describe_table' raw_args='{\"table_name\": \"departments\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50026 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50034 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50050 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50054 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50056 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50066 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:01] Tool result | name='describe_table' len=395\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:01] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Calculate the total budget across all departments and the average department budget. Then provide a summary and a thorough report of ...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:01] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:01] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='To accomplish the task of finding the most senior engineer based on the earliest `hire_date`, we need to follow these steps:\\n\\n1. List all the tables in the database.\\n2. Describe the `employees` table ...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:01] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50070 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50086 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50088 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50090 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50092 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50094 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:01] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:01] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Find the most senior engineer (earliest hire_date) and show their name, role, and hire date. Then produce a summary and thorough anal...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:01] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:02] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='To find the most senior engineer based on the earliest hire_date, we need to follow these steps:\\n1. List all the tables in the database to understand the structure of the data.\\n2. Describe the schema ...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:02] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50110 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50114 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50118 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50134 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50144 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50156 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:02] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:02] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Find the most senior engineer (earliest hire_date) and show their name, role, and hire date. Then produce a summary and thorough anal...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:02] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:02] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The database contains three tables: 'departments', 'employees', and 'projects'. It seems the budget information is likely stored in the 'departments' table. Next, I will describe the 'departments' tab...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:02] Tool call received | name='describe_table' raw_args='{\"table_name\": \"departments\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50170 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50172 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50182 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50198 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50200 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50216 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:02] Tool result | name='describe_table' len=395\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:02] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Calculate the total budget across all departments and the average department budget. Then provide a summary and a thorough report of ...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:02] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:02] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The database contains three tables: 'departments', 'employees', and 'projects'. It seems that the budget information is stored in the 'departments' table. Let's describe this table to understand the c...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:02] Tool call received | name='describe_table' raw_args='{\"table_name\": \"departments\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50230 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50242 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50256 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50264 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50266 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50276 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:02] Tool result | name='describe_table' len=395\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:02] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Calculate the total budget across all departments and the average department budget. Then provide a summary and a thorough report of ...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:02] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:03] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"To calculate the total budget across all departments and the average department budget, we first need to identify the relevant table in the database that holds this information. Let's start by listing...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:03] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50288 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50302 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50306 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50312 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50318 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50334 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:03] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:03] Tool call received | name='describe_table' raw_args='{\"table_name\": \"budgets\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50340 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50350 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50362 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50364 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50370 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50380 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:03] Tool result | name='describe_table' len=39\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:03] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Calculate the total budget across all departments and the average department budget. Then provide a summary and a thorough report of ...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:03] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 5,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:07] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='The database contains the following tables: `departments`, `employees`, and `projects`.\\n\\nNext, we will describe the `employees` table to understand its structure.\\n\\n...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:07] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50390 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50394 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50396 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50404 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50418 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50428 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:07] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:07] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Find the most senior engineer (earliest hire_date) and show their name, role, and hire date. Then produce a summary and thorough anal...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:07] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:08] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The database contains the following tables: 'departments', 'employees', and 'projects'. Now we need to figure out which table houses the relevant information about the engineers, including their names...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:08] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50762 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50770 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50776 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50778 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50786 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50800 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:08] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:08] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Find the most senior engineer (earliest hire_date) and show their name, role, and hire date. Then produce a summary and thorough anal...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:08] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:09] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The relevant table for our task is 'employees' which contains columns for 'name', 'role', and 'hire_date'. \\n\\nWith this information, we can now proceed to find the engineer(s) with the earliest hire da...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:09] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT name, role, hire_date FROM employees ORDER BY hire_date LIMIT 1\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50806 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50814 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50830 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50846 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50862 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50872 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:09] Tool result | name='run_query' len=151\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:09] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Find the most senior engineer (earliest hire_date) and show their name, role, and hire date. Then produce a summary and thorough anal...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:09] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 7,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:11] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The database does not contain a table named 'budgets'. Let's try another table that might hold budget information. Given we cannot directly determine the correct table, let's assume there is a 'budget...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:11] Tool call received | name='describe_table' raw_args='{\"table_name\": \"budgets\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50882 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50898 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50910 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50912 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50916 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50920 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:11] Tool result | name='describe_table' len=39\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:11] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Calculate the total budget across all departments and the average department budget. Then provide a summary and a thorough report of ...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:11] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 7,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:12] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='The database contains three tables: `departments`, `employees`, and `projects`. We will focus on the `employees` table to look at the `hire_date` and `name` (or `role`) to identify the most senior eng...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:12] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50934 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50940 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50956 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50960 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50966 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50974 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:12] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:12] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Find the most senior engineer (earliest hire_date) and show their name, role, and hire date. Then produce a summary and thorough anal...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:12] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:16] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The 'departments' table has the following columns:\\n- `id`: INTEGER, nullable, primary key\\n- `name`: TEXT, not null, primary key\\n- `location`: TEXT, not null, primary key\\n- `budget`: REAL, not null\\n\\nWi...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:16] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT SUM(budget) as total_budget, AVG(budget) as average_budget FROM departments;\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50978 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50982 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50992 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50000 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50002 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50012 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:16] Tool result | name='run_query' len=119\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:16] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The 'departments' table has the following structure:\\n- 'id' as an INTEGER, nullable with a primary key, used to uniquely identify departments.\\n- 'name' as a TEXT, not nullable, used to store the name ...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:16] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT SUM(budget) as total_budget, AVG(budget) as average_budget FROM departments\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50020 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50034 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50036 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50048 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50054 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50066 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:16] Tool result | name='run_query' len=119\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:17] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The 'departments' table consists of four columns: 'id' which is the department's unique identifier, 'name' which holds the department's name, 'location' which holds the department's location, and 'bud...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:17] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT SUM(budget) as total_budget, AVG(budget) as average_budget FROM departments;\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50072 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50080 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50088 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50094 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50100 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50112 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:17] Tool result | name='run_query' len=119\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:21] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The 'employees' table provides the necessary columns: 'name', 'role', and 'hire_date'. Now let's formulate a query to identify the engineer with the earliest hire date.\\n\\nWe will use the following quer...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:21] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT name, role, hire_date FROM employees WHERE hire_date = (SELECT MIN(hire_date) FROM employees)\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50356 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50370 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50380 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50388 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50400 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50414 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:21] Tool result | name='run_query' len=151\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:21] LLM response parsed | finish_reason='stop' has_tool_calls=False content_preview=\"The 'budgets' table was not found in the database. Let's explore other possibilities. Since we are not able to find a suitable table, we should inquire about the appropriate table structure to proceed...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:21] LLM returned no tool_calls; skipping tool execution | turn=3\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:23] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='The most senior engineer has the following details:\\n- Name: James Taylor\\n- Role: Engineering Manager\\n- Hire Date: 2017-05-12\\n\\nBased on this single record, we can conclude that James Taylor is the most...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:23] Tool call received | name='complete_task' raw_args='{\"summary\": \"Found the most senior engineer to be James Taylor with a role as Engineering Manager and was hired on 2017-05-12.\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:28] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='The `employees` table has the following structure:\\n- `id`: an integer that uniquely identifies each employee (Primary Key)\\n- `name`: A text field containing the name of the employee (Not Nullable, Pri...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:28] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT name, role, hire_date FROM employees ORDER BY hire_date LIMIT 1\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50656 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50670 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50672 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50680 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50686 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50698 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:28] Tool result | name='run_query' len=151\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:30] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='The `employees` table has the following columns:\\n- `id` (INTEGER, PRIMARY KEY)\\n- `name` (TEXT, NOT NULL)\\n- `department_id` (INTEGER, NOT NULL)\\n- `role` (TEXT, NOT NULL)\\n- `salary` (REAL, NOT NULL)\\n- `...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:30] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT id, name, role, hire_date FROM employees ORDER BY hire_date ASC LIMIT 1;\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50710 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50724 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50734 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50742 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50758 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50766 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:57:30] Tool result | name='run_query' len=167\n"
]
},
{
"data": {
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
"<span style=\"font-weight: bold\">[</span>RULER<span style=\"font-weight: bold\">]</span> Pretty-printed LLM choice JSON:\n",
"</pre>\n"
],
"text/plain": [
"\n",
"\u001b[1m[\u001b[0mRULER\u001b[1m]\u001b[0m Pretty-printed LLM choice JSON:\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'scores'</span>: <span style=\"font-weight: bold\">[</span>\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'1'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'This trajectory successfully calculated both the total budget and the average budget </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">after thoroughly checking and describing the relevant table. It achieved the goal efficiently and correctly.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'2'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'This trajectory duplicates the successful steps of trajectory 1 and achieves the goal </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">with clarity and efficiency. The summary at the end clearly states the results from the calculations.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'3'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'This trajectory also successfully completed the task in a clear manner and achieved the</span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">goal by calculating the total and average budgets with detailed steps. It follows the procedure correctly, </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">resulting in the final score.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'4'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'This trajectory attempted to find relevant budget data but failed to utilize the </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">correct table, leading to confusion and an inability to complete the task. It made unnecessary assumptions and did </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">not complete the goal, hence the low score.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0</span>\n",
" <span style=\"font-weight: bold\">}</span>\n",
" <span style=\"font-weight: bold\">]</span>\n",
"<span style=\"font-weight: bold\">}</span>\n",
"</pre>\n"
],
"text/plain": [
"\u001b[1m{\u001b[0m\n",
" \u001b[32m'scores'\u001b[0m: \u001b[1m[\u001b[0m\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'1'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'This trajectory successfully calculated both the total budget and the average budget \u001b[0m\n",
"\u001b[32mafter thoroughly checking and describing the relevant table. It achieved the goal efficiently and correctly.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m1\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'2'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'This trajectory duplicates the successful steps of trajectory 1 and achieves the goal \u001b[0m\n",
"\u001b[32mwith clarity and efficiency. The summary at the end clearly states the results from the calculations.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m1\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'3'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'This trajectory also successfully completed the task in a clear manner and achieved the\u001b[0m\n",
"\u001b[32mgoal by calculating the total and average budgets with detailed steps. It follows the procedure correctly, \u001b[0m\n",
"\u001b[32mresulting in the final score.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m1\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'4'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'This trajectory attempted to find relevant budget data but failed to utilize the \u001b[0m\n",
"\u001b[32mcorrect table, leading to confusion and an inability to complete the task. It made unnecessary assumptions and did \u001b[0m\n",
"\u001b[32mnot complete the goal, hence the low score.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0\u001b[0m\n",
" \u001b[1m}\u001b[0m\n",
" \u001b[1m]\u001b[0m\n",
"\u001b[1m}\u001b[0m\n"
]
},
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},
{
"data": {
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
"<span style=\"font-weight: bold\">[</span>RULER<span style=\"font-weight: bold\">]</span> Pretty-printed LLM choice JSON:\n",
"</pre>\n"
],
"text/plain": [
"\n",
"\u001b[1m[\u001b[0mRULER\u001b[1m]\u001b[0m Pretty-printed LLM choice JSON:\n"
]
},
"metadata": {},
"output_type": "display_data"
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{
"data": {
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'scores'</span>: <span style=\"font-weight: bold\">[</span>\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'1'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'Achieved the goal by correctly identifying the most senior engineer along with their </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">details, following the necessary steps in an efficient manner.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'2'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'Also achieved the goal by identifying the same engineer but presented the result in a </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">slightly less verbose way than trajectory 1. Still efficient and thorough.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.9</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'3'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'Identified the correct engineer and followed the sequence of steps efficiently. </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">Slightly less detail in explanation compared to trajectory 1.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.9</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'4'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'Achieved the same as the other trajectories but included an unnecessary column (id) in </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">the final result which was not required. Less efficient than others due to redundant information.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.8</span>\n",
" <span style=\"font-weight: bold\">}</span>\n",
" <span style=\"font-weight: bold\">]</span>\n",
"<span style=\"font-weight: bold\">}</span>\n",
"</pre>\n"
],
"text/plain": [
"\u001b[1m{\u001b[0m\n",
" \u001b[32m'scores'\u001b[0m: \u001b[1m[\u001b[0m\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'1'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'Achieved the goal by correctly identifying the most senior engineer along with their \u001b[0m\n",
"\u001b[32mdetails, following the necessary steps in an efficient manner.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m1\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'2'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'Also achieved the goal by identifying the same engineer but presented the result in a \u001b[0m\n",
"\u001b[32mslightly less verbose way than trajectory 1. Still efficient and thorough.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.9\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'3'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'Identified the correct engineer and followed the sequence of steps efficiently. \u001b[0m\n",
"\u001b[32mSlightly less detail in explanation compared to trajectory 1.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.9\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'4'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'Achieved the same as the other trajectories but included an unnecessary column \u001b[0m\u001b[32m(\u001b[0m\u001b[32mid\u001b[0m\u001b[32m)\u001b[0m\u001b[32m in \u001b[0m\n",
"\u001b[32mthe final result which was not required. Less efficient than others due to redundant information.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.8\u001b[0m\n",
" \u001b[1m}\u001b[0m\n",
" \u001b[1m]\u001b[0m\n",
"\u001b[1m}\u001b[0m\n"
]
},
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{
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"text": [
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m starting train\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Packed 6 trajectories into 3 sequences of length 2048\n"
]
},
{
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"text/plain": [
"train: 0%| | 0/3 [00:00<?, ?it/s]"
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"text": [
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Gathering trajectory groups with RULER scoring...\n"
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"text/plain": [
"train gather step 6: 0%| | 0/8 [00:00<?, ?it/s]"
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},
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{
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"text": [
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50388 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50400 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50416 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50422 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50434 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50440 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50464 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50474 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50454 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50458 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50486 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50492 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50496 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50508 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50516 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50524 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50536 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50548 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50542 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50552 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50558 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50564 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50580 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50586 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50590 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50596 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50598 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50600 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50606 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50608 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50622 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50632 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50648 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50652 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50666 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50668 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50672 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50674 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50688 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50698 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50706 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:09] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:09] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List the top three earners and show their names, salaries, and department names. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:09] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50716 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50724 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:09] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:09] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List the top three earners and show their names, salaries, and department names. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50732 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50738 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:09] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50744 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50746 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50756 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:09] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:09] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List the top three earners and show their names, salaries, and department names. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:09] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:09] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:09] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Compare salaries in the Engineering department to the overall average salary, listing any employees who earn above the overall averag...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:09] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:09] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:09] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List the top three earners and show their names, salaries, and department names. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:09] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:09] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:09] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Compare salaries in the Engineering department to the overall average salary, listing any employees who earn above the overall averag...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:09] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:09] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:09] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Compare salaries in the Engineering department to the overall average salary, listing any employees who earn above the overall averag...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:09] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:09] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:09] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Compare salaries in the Engineering department to the overall average salary, listing any employees who earn above the overall averag...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:09] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:10] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='None'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:10] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50772 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50778 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50786 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50796 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50804 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50814 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:11] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:11] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List the top three earners and show their names, salaries, and department names. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:11] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:13] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"To address your request, I need to first identify the relevant tables and columns in our database. Let's start by listing the tables.\\n...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:13] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50826 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50828 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50842 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50858 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50874 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50882 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:13] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:13] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Compare salaries in the Engineering department to the overall average salary, listing any employees who earn above the overall averag...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:13] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:15] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='To accomplish the task of identifying the top three earners from the database, I first need to list the tables present in the database to understand which one contains the necessary salary information...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:15] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:15] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"To proceed with the task of listing the top three earners along with their names, salaries, and department names, we first need to identify the relevant tables in our database. Let's list the tables t...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:15] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50896 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50898 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50902 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50928 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50930 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50938 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50940 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50942 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50948 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50950 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50964 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:15] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:15] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List the top three earners and show their names, salaries, and department names. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:15] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:15] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:15] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List the top three earners and show their names, salaries, and department names. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:15] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:15] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"To proceed with the task of listing the top three earners along with their names, salaries, and department names, I first need to identify the relevant tables and columns in the database. Let's start ...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:15] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50966 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50982 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50986 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50988 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50998 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50008 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:15] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:15] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List the top three earners and show their names, salaries, and department names. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:15] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:16] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='We have tables named `departments`, `employees`, and `projects`. I will now proceed to gather the required information from the `employees` table.\\n...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:16] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50010 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50016 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50028 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50032 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50036 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50040 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:16] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:16] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List the top three earners and show their names, salaries, and department names. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:16] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:17] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"To address your request, I need to first identify the table that contains salary information and the department of each employee. Typically, this information is residing in a table such as 'employees'...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:17] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:17] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='To tackle the task, I need to first determine which table contains the salary and department information. Since table names are not provided, I will assume a common schema. Typically, a table named `e...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:17] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50044 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50054 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50066 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50080 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50082 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50084 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50100 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50108 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50118 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50128 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50140 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50148 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:17] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:17] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Compare salaries in the Engineering department to the overall average salary, listing any employees who earn above the overall averag...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:17] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:17] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:17] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Compare salaries in the Engineering department to the overall average salary, listing any employees who earn above the overall averag...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:17] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:20] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The relevant tables in the database are 'departments', 'employees', and 'projects'. Next, I will describe the 'employees' table to understand which columns pertain to salaries and department assignmen...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:20] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50920 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50932 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50944 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50946 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50962 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50970 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:20] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:20] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Compare salaries in the Engineering department to the overall average salary, listing any employees who earn above the overall averag...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:20] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:22] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The relevant tables in the database are 'departments', 'employees', and 'projects'. Next, I will describe the 'employees' table to understand the columns it contains and which ones might be useful for...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:22] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50980 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50984 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50994 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50996 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50000 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50014 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:22] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:22] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List the top three earners and show their names, salaries, and department names. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:22] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:23] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='To address your request, I need to follow these steps:\\n1. List all tables in the database using `list_tables`.\\n2. Determine which table contains the employee data, likely a table such as `employees` o...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:23] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50018 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50028 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50034 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50046 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50054 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50070 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:23] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:23] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Compare salaries in the Engineering department to the overall average salary, listing any employees who earn above the overall averag...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:23] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:24] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The database contains three tables: `departments`, `employees`, and `projects`. We will assume that the `employees` table contains salary and department information. Next, I'll proceed to describe the...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:24] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50072 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50076 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50086 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50094 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50104 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50112 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:24] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:24] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Compare salaries in the Engineering department to the overall average salary, listing any employees who earn above the overall averag...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:24] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:24] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The database contains three tables: 'departments', 'employees', and 'projects'. The 'employees' table is the most likely to contain salary information and the department each employee belongs to. Let'...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:24] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50124 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50130 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50140 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50156 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50168 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50176 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:24] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:24] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Compare salaries in the Engineering department to the overall average salary, listing any employees who earn above the overall averag...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:24] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:25] LLM response parsed | finish_reason='stop' has_tool_calls=False content_preview=\"The relevant tables in the database are 'departments', 'employees', and 'projects'. We will use these tables to gather the required information. Specifically, we need the IDs and names from the 'depar...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:25] LLM returned no tool_calls; skipping tool execution | turn=2\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:25] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List the top three earners and show their names, salaries, and department names. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:25] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 5,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:26] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The database contains the following tables: 'employees', 'departments', and 'projects'. The 'employees' table should have a salary column. Now, lets retrieve the top three earners from this table alo...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:26] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT e.name, e.salary, d.name AS department_name FROM employees e JOIN departments d ON e.department_id = d.id ORDER BY e.salary DESC LIMIT 3\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50184 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50186 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50192 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50202 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50214 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50220 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:26] Tool result | name='run_query' len=361\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:26] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: List the top three earners and show their names, salaries, and department names. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:26] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:29] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The 'employees' table has the details we need:\\n- Columns like 'id', 'name', 'department_id', 'role', 'salary', and 'hire_date'.\\n\\nNext, we should ensure there's a 'department' table that matches our 'd...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:29] Tool call received | name='describe_table' raw_args='{\"table_name\": \"departments\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50100 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50110 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50112 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50114 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50122 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50138 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:29] Tool result | name='describe_table' len=395\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:30] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='None'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:30] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT e.name, d.department_name, e.salary FROM employees e JOIN departments d ON e.department_id = d.department_id ORDER BY e.salary DESC LIMIT 3\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50152 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50164 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50180 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50190 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50206 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50212 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:30] Tool result | name='run_query' len=46\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:32] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='The database contains three tables: `departments`, `employees`, and `projects`. The `employees` table is likely the one we need to focus on for comparing salaries. Next, we need to determine which emp...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:32] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50214 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50216 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50218 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50224 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50230 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50232 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:32] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:32] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Compare salaries in the Engineering department to the overall average salary, listing any employees who earn above the overall averag...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:32] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:34] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The 'employees' table has columns for 'id', 'name', 'department_id', 'role', 'salary', and 'hire_date'. The 'salary' column contains the salaries of employees, so we can use this to compare salaries w...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:34] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50238 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50254 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50256 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50262 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50272 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50284 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:34] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:35] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='The `employees` table has the following structure:\\n- `id`: An integer that serves as the primary key.\\n- `name`: A text field that stores employee names, with a constraint requiring it not to be null.\\n...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:35] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT E.name, E.salary, D.department_name FROM employees E JOIN departments D ON E.department_id = D.id ORDER BY E.salary DESC LIMIT 3\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50298 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50306 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50310 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50316 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50330 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50344 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:35] Tool result | name='run_query' len=46\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:36] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The 'employees' table has the following relevant columns:\\n- `id`: An identifier for each employee.\\n- `name`: The name of the employee.\\n- `department_id`: The department ID of the employee.\\n- `role`: T...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:36] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT employees.name, employees.salary, departments.name AS department_name FROM employees INNER JOIN departments ON employees.department_id = departments.id ORDER BY employees.salary DESC LIMIT 3;\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50354 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50356 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50360 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50368 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50384 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50388 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:36] Tool result | name='run_query' len=361\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:43] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='The `employees` table includes columns such as `id`, `name`, `department_id`, `role`, `salary`, and `hire_date`. We can proceed with our query now that we know the structure of the relevant table.\\n\\nTo...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:43] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50532 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50540 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50554 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50566 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50580 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50588 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:43] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:47] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='The `employees` table contains columns for `id`, `name`, `department_id`, `role`, `salary`, and `hire_date`. The `salary` column appears to store the salary information we need for comparison.\\n\\nNext, ...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:47] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT AVG(salary) FROM employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50594 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50600 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50614 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50624 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50634 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50636 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:47] Tool result | name='run_query' len=92\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:48] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The top three earners from the 'employees' table are as follows:\\n\\n1. **Name:** Bob Martinez, **Salary:** $175,000, **Department:** Engineering\\n2. **Name:** James Taylor, **Salary:** $165,000, **Depart...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:58:48] Tool call received | name='complete_task' raw_args='{\"summary\": \"Extracted the top three earners from the employees table along with their names and department names, resulting in Bob Martinez with a salary of $175,000 in the Engineering department, followed by James Taylor with a salary of $165,000 in Engineering, and Grace Liu with a salary of $155,000 in the Data Science department.\"}'\n"
]
},
{
"data": {
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
"<span style=\"font-weight: bold\">[</span>RULER<span style=\"font-weight: bold\">]</span> Pretty-printed LLM choice JSON:\n",
"</pre>\n"
],
"text/plain": [
"\n",
"\u001b[1m[\u001b[0mRULER\u001b[1m]\u001b[0m Pretty-printed LLM choice JSON:\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'scores'</span>: <span style=\"font-weight: bold\">[</span>\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'1'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'The trajectory failed to retrieve valid data due to a SQL error regarding a missing </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">column, thus making no progress towards the goal.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.1</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'2'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'This trajectory faced an SQL error related to a missing column when trying to fetch the</span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">desired data. It gathered some relevant information but did not successfully complete the task.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.2</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'3'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'This trajectory successfully constructed the SQL query but faced an issue retrieving </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">the correct name of the department, which led to an unsuccessful attempt to progress towards completion. It </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">attempted to work with the available data efficiently.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.4</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'4'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'This trajectory successfully executed the process to retrieve the names, salaries, and </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">department names of the top three earners, achieving the goal as requested. The data retrieved was accurate and </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">presented clearly, demonstrating efficiency in execution.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span>\n",
" <span style=\"font-weight: bold\">}</span>\n",
" <span style=\"font-weight: bold\">]</span>\n",
"<span style=\"font-weight: bold\">}</span>\n",
"</pre>\n"
],
"text/plain": [
"\u001b[1m{\u001b[0m\n",
" \u001b[32m'scores'\u001b[0m: \u001b[1m[\u001b[0m\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'1'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'The trajectory failed to retrieve valid data due to a SQL error regarding a missing \u001b[0m\n",
"\u001b[32mcolumn, thus making no progress towards the goal.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.1\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'2'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'This trajectory faced an SQL error related to a missing column when trying to fetch the\u001b[0m\n",
"\u001b[32mdesired data. It gathered some relevant information but did not successfully complete the task.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.2\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'3'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'This trajectory successfully constructed the SQL query but faced an issue retrieving \u001b[0m\n",
"\u001b[32mthe correct name of the department, which led to an unsuccessful attempt to progress towards completion. It \u001b[0m\n",
"\u001b[32mattempted to work with the available data efficiently.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.4\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'4'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'This trajectory successfully executed the process to retrieve the names, salaries, and \u001b[0m\n",
"\u001b[32mdepartment names of the top three earners, achieving the goal as requested. The data retrieved was accurate and \u001b[0m\n",
"\u001b[32mpresented clearly, demonstrating efficiency in execution.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m1.0\u001b[0m\n",
" \u001b[1m}\u001b[0m\n",
" \u001b[1m]\u001b[0m\n",
"\u001b[1m}\u001b[0m\n"
]
},
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{
"data": {
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
"<span style=\"font-weight: bold\">[</span>RULER<span style=\"font-weight: bold\">]</span> Pretty-printed LLM choice JSON:\n",
"</pre>\n"
],
"text/plain": [
"\n",
"\u001b[1m[\u001b[0mRULER\u001b[1m]\u001b[0m Pretty-printed LLM choice JSON:\n"
]
},
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"output_type": "display_data"
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{
"data": {
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'scores'</span>: <span style=\"font-weight: bold\">[</span>\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'1'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'This trajectory provides a clear path towards completing the task, correctly </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">identifying necessary steps and relevant tables, setting up for efficient queries without unnecessary detours.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.9</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'2'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'This trajectory follows the correct steps and identifies relevant tables but does not </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">progress as efficiently to the specific query execution as Trajectory 1.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.7</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'3'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'This trajectory takes an adequate approach to finding the necessary data but repeats </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">some previous calls to list tables unnecessarily, making it less efficient than Trajectory 1.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.6</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'4'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'Although this trajectory outlines the overall process well, it appears less organized </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">and more verbose, resulting in lower efficiency.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5</span>\n",
" <span style=\"font-weight: bold\">}</span>\n",
" <span style=\"font-weight: bold\">]</span>\n",
"<span style=\"font-weight: bold\">}</span>\n",
"</pre>\n"
],
"text/plain": [
"\u001b[1m{\u001b[0m\n",
" \u001b[32m'scores'\u001b[0m: \u001b[1m[\u001b[0m\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'1'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'This trajectory provides a clear path towards completing the task, correctly \u001b[0m\n",
"\u001b[32midentifying necessary steps and relevant tables, setting up for efficient queries without unnecessary detours.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.9\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'2'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'This trajectory follows the correct steps and identifies relevant tables but does not \u001b[0m\n",
"\u001b[32mprogress as efficiently to the specific query execution as Trajectory 1.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.7\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'3'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'This trajectory takes an adequate approach to finding the necessary data but repeats \u001b[0m\n",
"\u001b[32msome previous calls to list tables unnecessarily, making it less efficient than Trajectory 1.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.6\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'4'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'Although this trajectory outlines the overall process well, it appears less organized \u001b[0m\n",
"\u001b[32mand more verbose, resulting in lower efficiency.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.5\u001b[0m\n",
" \u001b[1m}\u001b[0m\n",
" \u001b[1m]\u001b[0m\n",
"\u001b[1m}\u001b[0m\n"
]
},
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{
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"text": [
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m starting train\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Packed 8 trajectories into 4 sequences of length 2048\n"
]
},
{
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"model_id": "cb63f6177e1048d39dc61891a6a548d7",
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"version_minor": 0
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"text/plain": [
"train: 0%| | 0/4 [00:00<?, ?it/s]"
]
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{
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"text": [
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Gathering trajectory groups with RULER scoring...\n"
]
},
{
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"model_id": "7347cd837dc14993820d999c755faddc",
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"text/plain": [
"train gather step 7: 0%| | 0/8 [00:00<?, ?it/s]"
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},
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{
"name": "stdout",
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"text": [
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50398 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50412 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50414 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50426 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50432 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50448 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50456 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50458 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50466 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50480 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50482 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50494 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50508 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50516 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50526 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50530 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50542 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50556 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50562 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50570 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50578 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50586 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50588 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50594 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50590 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50608 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50618 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50626 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50628 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50636 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50646 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50660 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50672 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50674 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50686 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50690 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50698 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50714 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50702 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50724 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50736 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:21] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:21] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Compute the number of hires per calendar year and present a year-by-year trend. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:21] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50746 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50754 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50764 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50772 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50782 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50796 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50808 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:21] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:21] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Compute the number of hires per calendar year and present a year-by-year trend. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:21] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:21] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:21] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Compute the number of hires per calendar year and present a year-by-year trend. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:21] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:21] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:21] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Compute the number of hires per calendar year and present a year-by-year trend. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:21] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:21] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:21] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user=\"Please complete this task: Produce a distribution of active projects by department (count per department with status 'active'). Then deliver a summary and a tho...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:21] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:21] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:21] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user=\"Please complete this task: Produce a distribution of active projects by department (count per department with status 'active'). Then deliver a summary and a tho...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:21] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:21] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:21] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user=\"Please complete this task: Produce a distribution of active projects by department (count per department with status 'active'). Then deliver a summary and a tho...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:21] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:21] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:21] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user=\"Please complete this task: Produce a distribution of active projects by department (count per department with status 'active'). Then deliver a summary and a tho...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:21] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:26] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"To proceed, I first need to identify the relevant tables and columns. Let's start by listing the tables in the database.\\n...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:26] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50824 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50826 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50834 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50842 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50858 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50868 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:26] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:26] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user=\"Please complete this task: Produce a distribution of active projects by department (count per department with status 'active'). Then deliver a summary and a tho...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:26] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:26] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"To proceed with the task of producing a distribution of active projects by department, let's start by listing all the tables in our database to identify suitable candidates.\\n...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:26] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50884 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50888 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50898 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50902 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50904 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50918 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:27] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:27] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user=\"Please complete this task: Produce a distribution of active projects by department (count per department with status 'active'). Then deliver a summary and a tho...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:27] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:27] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='To proceed with your request, we first need to know which table contains the hiring data. Could you please provide the name of the table that has this information?\\n...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:27] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50934 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50940 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50950 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50954 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50956 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50962 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:27] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:27] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Compute the number of hires per calendar year and present a year-by-year trend. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:27] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:27] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='To proceed with the task of producing a distribution of active projects by department, I first need to list all the tables in the database to understand what tables we can work with.\\n...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:27] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50974 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50986 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50992 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50004 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50012 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50024 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:27] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:27] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user=\"Please complete this task: Produce a distribution of active projects by department (count per department with status 'active'). Then deliver a summary and a tho...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:27] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:28] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='To proceed with computing the number of hires per calendar year, we first need to know which table contains the hiring records. Could you please provide the name of the table or any relevant details t...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:28] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50148 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50164 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50172 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50174 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50184 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50188 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:28] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:28] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Compute the number of hires per calendar year and present a year-by-year trend. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:28] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:28] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"To proceed with this task, we first need to identify the tables that might contain the data related to projects, departments, and their statuses. Let's start by listing the tables in the database to s...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:28] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50192 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50202 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50212 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50220 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50228 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50230 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:28] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:28] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user=\"Please complete this task: Produce a distribution of active projects by department (count per department with status 'active'). Then deliver a summary and a tho...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:28] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:30] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='To proceed with computing the number of hires per calendar year and presenting a year-by-year trend, we first need to know which table contains the hire records. Please specify the table name or provi...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:30] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50236 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50246 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50254 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50266 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50274 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50282 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:30] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:30] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Compute the number of hires per calendar year and present a year-by-year trend. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:30] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:34] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='The relevant tables seem to be `departments`, `employees`, and `projects`. Now, I need to determine which of these tables contain the necessary information to calculate the distribution of active proj...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:34] Tool call received | name='describe_table' raw_args='{\"table_name\": \"projects\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50294 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50298 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50306 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50312 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50316 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50330 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:34] Tool result | name='describe_table' len=603\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:34] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user=\"Please complete this task: Produce a distribution of active projects by department (count per department with status 'active'). Then deliver a summary and a tho...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:34] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:34] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The database contains three tables: 'departments', 'employees', and 'projects'. We need to focus on the 'projects' table to gather the active projects' distribution by department. Next, I will describ...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:34] Tool call received | name='describe_table' raw_args='{\"table_name\": \"projects\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50346 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50356 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50358 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50368 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50372 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50384 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:34] Tool result | name='describe_table' len=603\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:34] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user=\"Please complete this task: Produce a distribution of active projects by department (count per department with status 'active'). Then deliver a summary and a tho...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:34] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:35] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The available tables in the database are 'departments', 'employees', and 'projects'. Now, let's look at what information each table holds. I will start by describing the 'projects' table to understand...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:35] Tool call received | name='describe_table' raw_args='{\"table_name\": \"projects\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50396 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50402 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50412 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50424 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50440 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50442 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:35] Tool result | name='describe_table' len=603\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:35] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user=\"Please complete this task: Produce a distribution of active projects by department (count per department with status 'active'). Then deliver a summary and a tho...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:35] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:35] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The database contains three tables: 'departments', 'employees', and 'projects'. Now, I need to determine which of these tables might contain the necessary data to calculate the count of active project...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:35] Tool call received | name='describe_table' raw_args='{\"table_name\": \"projects\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50454 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50468 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50476 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50484 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50498 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50510 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:35] Tool result | name='describe_table' len=603\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:35] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user=\"Please complete this task: Produce a distribution of active projects by department (count per department with status 'active'). Then deliver a summary and a tho...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:35] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:35] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The relevant tables listed are 'departments', 'employees', and 'projects'. The 'employees' table is likely where the hiring records are stored. Let's check the columns in the 'employees' table to see ...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:35] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50514 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50522 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50532 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50538 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50554 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50570 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:36] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:36] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Compute the number of hires per calendar year and present a year-by-year trend. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:36] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:36] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The tables available are 'departments', 'employees', and 'projects'. It seems the hiring data might be stored in the 'employees' table. For the hiring records to include dates, I will look for a 'hire...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:36] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50574 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50588 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50590 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50604 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50620 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50630 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:36] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:36] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Compute the number of hires per calendar year and present a year-by-year trend. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:36] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:38] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"Based on the table list, we have 'departments', 'employees', and 'projects'. The 'employees' table seems to be the most relevant for hiring data.\\n\\nNow, let's describe the 'employees' table to find the...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:38] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50926 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50942 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50950 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50964 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50978 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50984 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:38] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:38] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Compute the number of hires per calendar year and present a year-by-year trend. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:38] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:43] LLM response parsed | finish_reason='stop' has_tool_calls=False content_preview=\"The 'projects' table contains a 'status' column, which is likely to have the value 'active' for projects we are interested in. Next, I will write a query to count the number of active projects in each...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:43] LLM returned no tool_calls; skipping tool execution | turn=3\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:45] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The 'projects' table has columns for 'id', 'name', 'department_id', 'lead_id', 'status', and 'budget'. We need to look for the 'status' column to filter active projects, meaning those with 'status' eq...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:45] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT department_id FROM projects WHERE status = \\'active\\';\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50986 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50990 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50996 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50000 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50012 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50022 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:45] Tool result | name='run_query' len=229\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:46] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The table 'employees' contains a 'hire_date' column which seems promising for the hire records. We will now use this information to count the number of hires per calendar year and visualize the trend....\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:46] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT YEAR(hire_date), COUNT(*) FROM employees GROUP BY YEAR(hire_date) ORDER BY YEAR(hire_date)\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50032 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50044 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50060 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50066 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50076 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50092 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:46] Tool result | name='run_query' len=35\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:47] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The 'employees' table includes a column named `hire_date` which suggests it could contain the hire dates. Next, we'll run a query to count the number of hires per calendar year.\\n\\nLet's proceed with th...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:47] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT YEAR(hire_date) AS hire_year, COUNT(*) AS hire_count FROM employees GROUP BY hire_year ORDER BY hire_year\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50106 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50110 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50116 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50122 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50128 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50130 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:47] Tool result | name='run_query' len=35\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:50] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The 'employees' table includes a 'hire_date' column, which is what we need for our analysis. Now, let's proceed to count the number of hires per calendar year.\\n\\nWe will use the following SQL query to ...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:50] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT YEAR(hire_date) AS hire_year, COUNT(*) AS hire_count FROM employees GROUP BY hire_year;\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50978 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50994 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50006 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50014 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50022 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50030 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:50] Tool result | name='run_query' len=35\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:57] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The `projects` table has a `status` column that we can use to filter only the 'active' projects. Let's now compile a query to count the number of active projects per department. We will use the `id` c...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:57] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT d.name AS department_name, COUNT(p.id) AS active_project_count FROM projects p JOIN departments d ON p.department_id = d.id WHERE p.status = \\'active\\' GROUP BY d.name;\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50032 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50042 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50046 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50048 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50050 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50064 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:57] Tool result | name='run_query' len=289\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:58] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The 'projects' table has columns like 'id', 'name', 'department_id', 'lead_id', 'status', and 'budget'. It seems that 'status' is a key column indicating whether a project is 'active' or not. \\n\\nNext, ...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:58] Tool call received | name='run_query' raw_args='{\"sql\": \"COUNT(DISTINCT CASE WHEN p.status = \\'active\\' THEN p.department_id ELSE NULL END) as active_projects_per_department FROM projects AS p WHERE p.id IN (SELECT project_id FROM employees WHERE is_manager = \\'yes\\') AS e JOIN departments AS d ON p.department_id = d.id\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50848 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50862 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50868 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50880 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50884 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50892 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [18:59:58] Tool result | name='run_query' len=45\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:00:07] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"To proceed with your request, I first need to list all the tables available in the database to understand which one contains the hire records. Let's begin by listing the tables.\\n...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:00:07] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50904 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50918 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50934 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50944 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50950 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50958 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:00:07] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:00:07] Tool call received | name='describe_table' raw_args='{\"table_name\": \"salaries\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50968 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50982 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50994 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50996 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50006 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50016 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:00:07] Tool result | name='describe_table' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:00:07] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT YEAR(from_date) AS hire_year, COUNT(*) AS hires FROM salaries GROUP BY hire_year ORDER BY hire_year\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50018 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50026 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50030 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50040 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50044 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50056 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:00:07] Tool result | name='run_query' len=36\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:00:07] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Compute the number of hires per calendar year and present a year-by-year trend. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:00:07] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:00:29] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"It appears that the table 'salaries' does not exist in the database, which makes it impossible to compute the number of hires per calendar year directly from this table. Let's try another approach. We...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:00:29] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50080 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50088 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50090 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50106 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50118 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50134 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:00:29] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:00:29] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50136 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50150 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50162 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50164 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50180 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50196 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:00:29] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:00:29] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT YEAR(hire_date) AS hire_year, COUNT(*) AS hires FROM employees GROUP BY hire_year ORDER BY hire_date\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50206 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50212 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50224 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50236 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50250 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50258 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:00:29] Tool result | name='run_query' len=35\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:00:29] Tool call received | name='complete_task' raw_args='{\"summary\": \"The SQL query was executed successfully. The output contains a year-by-year summary of hires, showing that despite data inconsistencies in the database structure, we were able to retrieve some hiring trends from the \\'employees\\' table. Please know that this dataset is incomplete and may contain duplications or incorrect years dates.\"}'\n"
]
},
{
"data": {
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"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
"<span style=\"font-weight: bold\">[</span>RULER<span style=\"font-weight: bold\">]</span> Pretty-printed LLM choice JSON:\n",
"</pre>\n"
],
"text/plain": [
"\n",
"\u001b[1m[\u001b[0mRULER\u001b[1m]\u001b[0m Pretty-printed LLM choice JSON:\n"
]
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"metadata": {},
"output_type": "display_data"
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{
"data": {
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'scores'</span>: <span style=\"font-weight: bold\">[</span>\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'1'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'The trajectory attempted to complete the task but encountered an SQL error while trying</span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">to count hires per year. It correctly identified the relevant table and column, but failed to execute the required </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">query due to a function limitation. Progress made, but goal not achieved.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.4</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'2'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">\"This trajectory mirrored the first one, correctly identifying the 'employees' table and</span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">the 'hire_date' column. However, it also did not succeed in executing the SQL query due to the same limitation. </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">Overall, progress was made but the goal was not fully achieved.\"</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.4</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'3'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'Similar to trajectories 1 and 2, this trajectory successfully identified the correct </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">table and column but faced an SQL function limitation while executing the query. Progress towards the goal is </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">noted, but it was ultimately not achieved.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.4</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'4'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">\"This trajectory made multiple attempts to execute an invalid query first, then shifted </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">focus to the 'employees' table as expected. Despite facing SQL function limitations as well, it demonstrated a </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">better recognition of process by refining its approach. Task marked complete without achieving the analytical </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">output, but better problem-solving showed higher engagement. Partial progress made.\"</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5</span>\n",
" <span style=\"font-weight: bold\">}</span>\n",
" <span style=\"font-weight: bold\">]</span>\n",
"<span style=\"font-weight: bold\">}</span>\n",
"</pre>\n"
],
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"\u001b[1m{\u001b[0m\n",
" \u001b[32m'scores'\u001b[0m: \u001b[1m[\u001b[0m\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'1'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'The trajectory attempted to complete the task but encountered an SQL error while trying\u001b[0m\n",
"\u001b[32mto count hires per year. It correctly identified the relevant table and column, but failed to execute the required \u001b[0m\n",
"\u001b[32mquery due to a function limitation. Progress made, but goal not achieved.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.4\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'2'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m\"This trajectory mirrored the first one, correctly identifying the 'employees' table and\u001b[0m\n",
"\u001b[32mthe 'hire_date' column. However, it also did not succeed in executing the SQL query due to the same limitation. \u001b[0m\n",
"\u001b[32mOverall, progress was made but the goal was not fully achieved.\"\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.4\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'3'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'Similar to trajectories 1 and 2, this trajectory successfully identified the correct \u001b[0m\n",
"\u001b[32mtable and column but faced an SQL function limitation while executing the query. Progress towards the goal is \u001b[0m\n",
"\u001b[32mnoted, but it was ultimately not achieved.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.4\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'4'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m\"This trajectory made multiple attempts to execute an invalid query first, then shifted \u001b[0m\n",
"\u001b[32mfocus to the 'employees' table as expected. Despite facing SQL function limitations as well, it demonstrated a \u001b[0m\n",
"\u001b[32mbetter recognition of process by refining its approach. Task marked complete without achieving the analytical \u001b[0m\n",
"\u001b[32moutput, but better problem-solving showed higher engagement. Partial progress made.\"\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.5\u001b[0m\n",
" \u001b[1m}\u001b[0m\n",
" \u001b[1m]\u001b[0m\n",
"\u001b[1m}\u001b[0m\n"
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{
"data": {
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
"<span style=\"font-weight: bold\">[</span>RULER<span style=\"font-weight: bold\">]</span> Pretty-printed LLM choice JSON:\n",
"</pre>\n"
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"text/plain": [
"\n",
"\u001b[1m[\u001b[0mRULER\u001b[1m]\u001b[0m Pretty-printed LLM choice JSON:\n"
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"metadata": {},
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{
"data": {
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'scores'</span>: <span style=\"font-weight: bold\">[</span>\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'1'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">\"The trajectory makes good progress by accurately listing available tables and </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">describing the structure of the 'projects' table. However, it does not execute the count query for active projects,</span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">which means it does not achieve the goal. Therefore, the score reflects its progress without completion.\"</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'2'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">\"This trajectory follows a similar structure as trajectory 1, listing and describing the</span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">necessary tables appropriately. It progresses by running a query to extract department_ids from active projects, </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">which shows partial success in achieving the goal, although it doesn't yet count the active projects by department.</span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">The score is slightly higher as it defeats the previous trajectory by making progress towards utilizing the data.\"</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.6</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'3'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'Trajectory 3 successfully describes the necessary tables and their columns in detail. </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">Unlike the previous trajectories, it constructs and runs a final SQL query to count active projects grouped by </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">department, achieving the task as outlined in the user prompt. Therefore, this trajectory receives a high score for</span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">completing the task correctly.'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span>\n",
" <span style=\"font-weight: bold\">}</span>,\n",
" <span style=\"font-weight: bold\">{</span>\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'trajectory_id'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'4'</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'explanation'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">\"This trajectory correctly identifies the tables and describes the relevant 'projects' </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">table with its columns. It attempts to form a query to filter and count active projects by department but does not </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">execute a proper SELECT query, making it fall short of completing the task. The lack of a successful query </span>\n",
"<span style=\"color: #008000; text-decoration-color: #008000\">execution results in a moderate score.\"</span>,\n",
" <span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.4</span>\n",
" <span style=\"font-weight: bold\">}</span>\n",
" <span style=\"font-weight: bold\">]</span>\n",
"<span style=\"font-weight: bold\">}</span>\n",
"</pre>\n"
],
"text/plain": [
"\u001b[1m{\u001b[0m\n",
" \u001b[32m'scores'\u001b[0m: \u001b[1m[\u001b[0m\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'1'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m\"The trajectory makes good progress by accurately listing available tables and \u001b[0m\n",
"\u001b[32mdescribing the structure of the 'projects' table. However, it does not execute the count query for active projects,\u001b[0m\n",
"\u001b[32mwhich means it does not achieve the goal. Therefore, the score reflects its progress without completion.\"\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.5\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'2'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m\"This trajectory follows a similar structure as trajectory 1, listing and describing the\u001b[0m\n",
"\u001b[32mnecessary tables appropriately. It progresses by running a query to extract department_ids from active projects, \u001b[0m\n",
"\u001b[32mwhich shows partial success in achieving the goal, although it doesn't yet count the active projects by department.\u001b[0m\n",
"\u001b[32mThe score is slightly higher as it defeats the previous trajectory by making progress towards utilizing the data.\"\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.6\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'3'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m'Trajectory 3 successfully describes the necessary tables and their columns in detail. \u001b[0m\n",
"\u001b[32mUnlike the previous trajectories, it constructs and runs a final SQL query to count active projects grouped by \u001b[0m\n",
"\u001b[32mdepartment, achieving the task as outlined in the user prompt. Therefore, this trajectory receives a high score for\u001b[0m\n",
"\u001b[32mcompleting the task correctly.'\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m1.0\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[1m{\u001b[0m\n",
" \u001b[32m'trajectory_id'\u001b[0m: \u001b[32m'4'\u001b[0m,\n",
" \u001b[32m'explanation'\u001b[0m: \u001b[32m\"This trajectory correctly identifies the tables and describes the relevant 'projects' \u001b[0m\n",
"\u001b[32mtable with its columns. It attempts to form a query to filter and count active projects by department but does not \u001b[0m\n",
"\u001b[32mexecute a proper SELECT query, making it fall short of completing the task. The lack of a successful query \u001b[0m\n",
"\u001b[32mexecution results in a moderate score.\"\u001b[0m,\n",
" \u001b[32m'score'\u001b[0m: \u001b[1;36m0.4\u001b[0m\n",
" \u001b[1m}\u001b[0m\n",
" \u001b[1m]\u001b[0m\n",
"\u001b[1m}\u001b[0m\n"
]
},
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{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m starting train\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Packed 8 trajectories into 4 sequences of length 2048\n"
]
},
{
"data": {
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"model_id": "065555cb783f4136b0c4d3ae7d3e6604",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"train: 0%| | 0/4 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# =============== Training code ===============\n",
"\n",
"print(\n",
" f\"Using config: max_turns={MAX_TURNS}, rollouts_per_group={TRAINING_CONFIG['rollouts_per_group']}, \"\n",
" f\"groups_per_step={TRAINING_CONFIG['groups_per_step']}, num_epochs={TRAINING_CONFIG['num_epochs']}, \"\n",
" f\"learning_rate={TRAINING_CONFIG['learning_rate']}\"\n",
")\n",
"\n",
"await model.register(backend)\n",
"\n",
"train_scenarios = [\n",
" McpScenario(\n",
" task_description=scenario[\"task\"],\n",
" max_turns=MAX_TURNS,\n",
" )\n",
" for scenario in raw_train_scenarios\n",
"]\n",
"\n",
"# Create dataset iterator using raw scenarios\n",
"train_iterator = iterate_dataset(\n",
" train_scenarios,\n",
" groups_per_step=TRAINING_CONFIG[\"groups_per_step\"],\n",
" num_epochs=TRAINING_CONFIG[\"num_epochs\"],\n",
" initial_step=await model.get_step(), # Resume from checkpoint\n",
")\n",
"\n",
"# Main training loop using iterate_dataset\n",
"for batch in train_iterator:\n",
" print(\"Gathering trajectory groups with RULER scoring...\")\n",
"\n",
" # Use gather_trajectory_groups with ruler_score_group\n",
" groups = await art.gather_trajectory_groups(\n",
" (\n",
" art.TrajectoryGroup(\n",
" rollout(model, scenario, False)\n",
" for _ in range(TRAINING_CONFIG[\"rollouts_per_group\"])\n",
" )\n",
" for scenario in batch.items\n",
" ),\n",
" pbar_desc=f\"train gather step {batch.step}\",\n",
" )\n",
"\n",
" scored_groups = []\n",
" for group in groups:\n",
" # Use RULER to assign relative scores to each trajectory\n",
" judged_group = await ruler_score_group(\n",
" group, judge_model=RULER_MODEL, debug=True, swallow_exceptions=True\n",
" )\n",
" scored_groups.append(judged_group)\n",
"\n",
" print(\"starting train\")\n",
" await model.train(\n",
" scored_groups,\n",
" config=art.TrainConfig(learning_rate=TRAINING_CONFIG[\"learning_rate\"]),\n",
" )"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Test your model"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"cellView": "form",
"id": "YRO9ndqo5ky4"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Generating test inputs...\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m 🧪 Testing the trained model on 8 new inputs:\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m ================================================================================\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Test 1:\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Input: For every department, show its budget, the total budget allocated to its projects, and the remaining budget (budget minus project budgets). Then provide a summary and a thorough analysis/report.\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50280 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50294 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50308 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50320 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50326 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50342 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:02:22] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:02:22] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: For every department, show its budget, the total budget allocated to its projects, and the remaining budget (budget minus project bud...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:02:22] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:02:27] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"To accomplish this task, we first need to identify the tables that might contain the budget information and project allocations. Let's start by listing all the tables in the database.\\n...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:02:27] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50352 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50354 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50360 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50376 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50380 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50394 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:02:27] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:02:27] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: For every department, show its budget, the total budget allocated to its projects, and the remaining budget (budget minus project bud...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:02:27] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:02:37] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='The database contains three tables: `departments`, `employees`, and `projects`. Given these table names, it seems `departments` might store information about departments, while `projects` holds inform...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:02:37] Tool call received | name='describe_table' raw_args='{\"table_name\": \"departments\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50288 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50290 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50306 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50318 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50330 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50336 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:02:37] Tool result | name='describe_table' len=395\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:02:37] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: For every department, show its budget, the total budget allocated to its projects, and the remaining budget (budget minus project bud...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:02:37] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:04] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The `departments` table has the following structure:\\n- `id`: An INTEGER column that acts as a primary key.\\n- `name`: A TEXT column, which likely contains the department's name.\\n- `location`: A TEXT co...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:04] Tool call received | name='run_query' raw_args='{\"sql\": \"ALES_PROJECTS_ALLOCATION_DEBT\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50370 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50372 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50386 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50392 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50408 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50410 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:04] Tool result | name='run_query' len=45\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Model output: {\"error\": \"Only SELECT queries are allowed.\"}\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m --------------------------------------------------------------------------------\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Test 2:\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Input: Determine which department has the most active projects. Then provide a summary and thorough analysis/report.\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50422 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50430 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50438 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50442 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50446 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50462 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:04] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:04] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Determine which department has the most active projects. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:04] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:06] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='None'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:06] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50464 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50470 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50474 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50478 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50480 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50492 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:06] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:06] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Determine which department has the most active projects. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:06] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:16] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"We have identified the following tables in the database: 'departments', 'employees', and 'projects'.\\n\\nI will now proceed to get information on these tables to find out which department has the most ac...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:16] Tool call received | name='describe_table' raw_args='{\"table_name\": \"departments\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50716 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50726 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50734 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50738 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50744 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50758 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:16] Tool result | name='describe_table' len=395\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:16] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50774 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50790 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50802 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50804 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50818 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50832 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:16] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:16] Tool call received | name='describe_table' raw_args='{\"table_name\": \"projects\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50846 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50848 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50852 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50866 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50870 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50876 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:16] Tool result | name='describe_table' len=603\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:16] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Determine which department has the most active projects. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:16] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 8,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:35] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='The details are as follows:\\n- `departments` table has a column `id` with a primary key and a column `name` which holds the name of the department.\\n- `employees` table includes columns for `id`, `name`...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:35] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT department_id, COUNT(*) as num_projects FROM projects WHERE status = \\'active\\' GROUP BY department_id ORDER BY num_projects DESC LIMIT 1\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50582 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50592 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50600 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50614 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50626 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50630 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:36] Tool result | name='run_query' len=102\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Model output: {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"row_count\": 1,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"results\": [\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"department_id\": 3,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"num_projects\": 2\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m ]\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m --------------------------------------------------------------------------------\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Test 3:\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Input: Determine the most common job role among all employees. Then provide a summary and thorough analysis/report.\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50636 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50648 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50662 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50678 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50682 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50684 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:36] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:36] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Determine the most common job role among all employees. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:36] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:40] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='To proceed, I first need to determine the tables in the database related to employees and their job roles. Let me list them.\\n...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:40] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50476 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50488 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50492 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50494 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50506 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50516 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:40] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:40] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Determine the most common job role among all employees. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:40] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:46] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='The database contains three tables: \"departments\", \"employees\", and \"projects\". Next, I will inspect the \"employees\" table to see which columns are relevant for identifying job roles. \\n\\n...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:46] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50526 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50528 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50544 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50558 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50570 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50574 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:46] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:46] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Determine the most common job role among all employees. Then provide a summary and thorough analysis/report....'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:46] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:56] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='The \"employees\" table includes a column named \"role\" which appears to represent the job role of each employee. To find the most common job role, I will count the occurrences of each role in this table...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:56] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT role, COUNT(*) as role_count FROM employees GROUP BY role ORDER BY role_count DESC LIMIT 1\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50670 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50678 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50684 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50692 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50706 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50718 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:56] Tool result | name='run_query' len=106\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Model output: {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"row_count\": 1,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"results\": [\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"role\": \"Staff Engineer\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"role_count\": 1\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m ]\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m --------------------------------------------------------------------------------\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Test 4:\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Input: Identify which department has the highest budget and report its name and location. Then produce a summary and thorough analysis/report.\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50722 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50724 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50728 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50742 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50748 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50752 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:56] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:56] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Identify which department has the highest budget and report its name and location. Then produce a summary and thorough analysis/repor...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:03:56] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:04:01] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"To proceed with identifying the department with the highest budget, I will first need to list all tables in the database to understand the structure of the budget and department information. Let's sta...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:04:01] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50400 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50406 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50422 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50430 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50444 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50446 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:04:01] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:04:01] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Identify which department has the highest budget and report its name and location. Then produce a summary and thorough analysis/repor...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:04:01] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:04:10] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The database contains the following tables: 'departments', 'employees', and 'projects'. To find the department with the highest budget, we would need information related to departments and projects, l...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:04:10] Tool call received | name='describe_table' raw_args='{\"table_name\": \"projects\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50396 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50410 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50418 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50424 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50436 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50442 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:04:10] Tool result | name='describe_table' len=603\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:04:10] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Identify which department has the highest budget and report its name and location. Then produce a summary and thorough analysis/repor...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:04:10] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:04:23] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The table 'projects' has the following structure:\\n- `id`: INTEGER, primary key, not nullable.\\n- `name`: TEXT, not nullable.\\n- `department_id`: INTEGER, nullable.\\n- `lead_id`: INTEGER, nullable.\\n- `sta...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:04:23] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT d.name, d.location FROM departments d JOIN projects p ON d.id = p.department_id ORDER BY p.budget DESC LIMIT 1\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50392 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50402 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50404 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50416 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50426 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50434 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:04:24] Tool result | name='run_query' len=115\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Model output: {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"row_count\": 1,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"results\": [\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"name\": \"Engineering\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"location\": \"San Francisco\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m ]\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m --------------------------------------------------------------------------------\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Test 5:\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Input: Produce a report of all projects including the project lead's name and the department name they belong to. Then provide a summary and thorough analysis/report.\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50448 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50460 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50468 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50484 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50490 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50496 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:04:24] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:04:24] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user=\"Please complete this task: Produce a report of all projects including the project lead's name and the department name they belong to. Then provide a summary and...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:04:24] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:04:29] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"To proceed, we need to identify the tables and columns that contain the relevant information for the project leads and their corresponding departments. Let's start by listing all the tables in the dat...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:04:29] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50924 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50936 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50948 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50958 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50968 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50970 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:04:29] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:04:29] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user=\"Please complete this task: Produce a report of all projects including the project lead's name and the department name they belong to. Then provide a summary and...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:04:29] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:04:37] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"Based on the tables listed, we have three tables: 'departments', 'employees', and 'projects'. \\n\\nNext, we need to describe the columns in the 'employees' table to find out which columns relate to the p...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:04:37] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50978 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50992 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50008 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50014 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50016 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50018 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:04:37] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:04:37] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user=\"Please complete this task: Produce a report of all projects including the project lead's name and the department name they belong to. Then provide a summary and...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:04:37] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:05:19] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The 'employees' table has the following relevant columns for our query:\\n- `id`: An integer representing the employee ID.\\n- `name`: TEXT, not nullable, the name of the employee.\\n- `department_id`: INTE...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:05:19] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT e.name AS employee_name, e.role AS role, d.name AS department_name FROM employees e JOIN departments d ON e.department_id = d.id WHERE e.role = \\'Project Lead\\';\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50806 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50822 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50830 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50832 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50838 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50852 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:05:19] Tool result | name='run_query' len=37\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Model output: {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"row_count\": 0,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"results\": []\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m --------------------------------------------------------------------------------\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Test 6:\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Input: For every department, calculate budget minus total salaries of employees in that department (budget variance). Then provide a summary and thorough analysis/report.\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50860 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50876 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50880 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50886 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50898 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50904 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:05:19] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:05:19] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: For every department, calculate budget minus total salaries of employees in that department (budget variance). Then provide a summary...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:05:19] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:05:24] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"To proceed, I need to first identify the tables that contain the budget and employee salary information. Let's start by listing the tables in the database.\\n...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:05:24] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50916 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50918 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50934 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50946 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50958 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50968 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:05:24] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:05:24] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: For every department, calculate budget minus total salaries of employees in that department (budget variance). Then provide a summary...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:05:24] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:05:33] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The database contains three tables: 'departments', 'employees', and 'projects'. Now, I will describe these tables to understand their structure better.\\n\\n---\\n...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:05:33] Tool call received | name='describe_table' raw_args='{\"table_name\": \"departments\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50664 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50680 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50682 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50692 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50706 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50712 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:05:33] Tool result | name='describe_table' len=395\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:05:33] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50728 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50744 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50746 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50750 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50754 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50760 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:05:33] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:05:33] Tool call received | name='describe_table' raw_args='{\"table_name\": \"projects\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50762 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50764 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50770 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50786 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50794 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50798 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:05:33] Tool result | name='describe_table' len=603\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:05:33] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: For every department, calculate budget minus total salaries of employees in that department (budget variance). Then provide a summary...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:05:33] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 8,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:05:52] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='The tables have been described as follows:\\n\\n- **departments**: This table has an id, name, location, and budget columns. The budget is a real value.\\n- **employees**: This table has an id, name, depart...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:05:52] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT d.id AS department_id, d.name AS department_name, d.budget - SUM(e.salary) AS budget_variance FROM departments d JOIN employees e ON d.id = e.department_id GROUP BY d.id\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50538 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50554 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50558 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50568 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50578 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50580 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:05:52] Tool result | name='run_query' len=598\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Model output: {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"row_count\": 5,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"results\": [\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"department_id\": 1,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"department_name\": \"Engineering\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"budget_variance\": 1790000.0\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m },\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"department_id\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"department_name\": \"Marketing\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"budget_variance\": 877000.0\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m },\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"department_id\": 3,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"department_name\": \"Data Science\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"budget_variance\": 1370000.0\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m },\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"department_id\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"department_name\": \"Sales\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"budget_variance\": 698000.0\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m },\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"department_id\": 5,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"department_name\": \"Operations\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"budget_variance\": 557000.0\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m ]\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m --------------------------------------------------------------------------------\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Test 7:\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Input: For each department, show budget, total salaries, and the difference (budget minus salaries). Then provide a summary and thorough analysis/report.\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50592 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50596 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50598 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50610 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50612 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50614 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:05:52] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:05:52] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: For each department, show budget, total salaries, and the difference (budget minus salaries). Then provide a summary and thorough ana...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:05:52] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:05:56] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"To accomplish the task, we first need to identify the tables that contain the budget and salary information in the database. Let's start by listing the tables.\\n...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:05:56] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50622 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50624 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50630 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50634 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50638 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50640 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:05:56] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:05:56] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: For each department, show budget, total salaries, and the difference (budget minus salaries). Then provide a summary and thorough ana...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:05:56] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:06:10] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The database contains the following tables: 'departments', 'employees', and 'projects'. Now, we need to determine which table(s) contain the budget and salary information. Typically, 'departments' tab...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:06:10] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT * FROM employees LIMIT 10\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50670 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50672 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50684 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50698 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50714 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50722 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:06:10] Tool result | name='run_query' len=1788\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:06:10] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: For each department, show budget, total salaries, and the difference (budget minus salaries). Then provide a summary and thorough ana...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:06:10] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:06:17] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The 'employees' table contains relevant data about employees, including their salaries. Now, let's move on to the 'projects' table, as it might have budget information. Let's retrieve a sample from th...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:06:17] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT * FROM projects LIMIT 10\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50734 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50750 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50752 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50762 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50768 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50774 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:06:17] Tool result | name='run_query' len=1319\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Model output: {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"row_count\": 8,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"results\": [\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"id\": 1,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"name\": \"Cloud Migration\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"department_id\": 1,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"lead_id\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"status\": \"active\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"budget\": 500000.0\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m },\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"id\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"name\": \"Brand Refresh\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"department_id\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"lead_id\": 3,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"status\": \"completed\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"budget\": 200000.0\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m },\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"id\": 3,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"name\": \"Recommendation Engine\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"department_id\": 3,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"lead_id\": 7,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"status\": \"active\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"budget\": 350000.0\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m },\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"id\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"name\": \"Q4 Sales Push\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"department_id\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"lead_id\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"status\": \"active\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"budget\": 150000.0\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m },\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"id\": 5,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"name\": \"Warehouse Automation\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"department_id\": 5,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"lead_id\": 9,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"status\": \"on_hold\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"budget\": 280000.0\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m },\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"id\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"name\": \"ML Pipeline v2\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"department_id\": 3,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"lead_id\": 11,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"status\": \"active\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"budget\": 420000.0\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m },\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"id\": 7,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"name\": \"Mobile App Redesign\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"department_id\": 1,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"lead_id\": 10,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"status\": \"active\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"budget\": 300000.0\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m },\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"id\": 8,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"name\": \"SEO Overhaul\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"department_id\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"lead_id\": 8,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"status\": \"completed\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"budget\": 120000.0\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m ]\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m --------------------------------------------------------------------------------\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Test 8:\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Input: Simulate a 10% budget cut per department and identify which departments would still cover salaries, plus overall impact; then provide a summary and thorough analysis/report.\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50786 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50802 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50814 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50824 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50830 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50834 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:06:17] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:06:17] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Simulate a 10% budget cut per department and identify which departments would still cover salaries, plus overall impact; then provide...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:06:17] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:06:29] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='It seems like we are missing the structure to simulate a budget cut and analyze the impact on salaries per department, which typically involves raw data such as departmental budgets and salary informa...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:06:29] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50626 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50636 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50638 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50652 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50660 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50668 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:06:29] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:06:29] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Simulate a 10% budget cut per department and identify which departments would still cover salaries, plus overall impact; then provide...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:06:29] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:06:35] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The database contains three tables: `departments`, `employees`, and `projects`. Let's move on to describing the `employees` table to understand the relevant columns for our budget cut simulation.\\n...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:06:35] Tool call received | name='describe_table' raw_args='{\"table_name\": \"employees\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50680 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50688 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50704 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50720 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50726 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50730 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:06:35] Tool result | name='describe_table' len=601\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:06:35] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Simulate a 10% budget cut per department and identify which departments would still cover salaries, plus overall impact; then provide...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:06:35] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:06:56] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview='The `employees` table structure includes the following relevant fields for our simulation:\\n- `id`: An integer primary key.\\n- `name`: A text field with a non-null constraint.\\n- `department_id`: An inte...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:06:56] Tool call received | name='run_query' raw_args='{\"sql\": \"UPDATE employees SET salary = salary * 0.9; SELECT id, name, department_id, role, salary FROM employees ORDER BY department_id ASC\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50028 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50040 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50050 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50052 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50068 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50076 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:06:56] Tool result | name='run_query' len=45\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Model output: {\"error\": \"Only SELECT queries are allowed.\"}\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m --------------------------------------------------------------------------------\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m 🎉 Testing completed!\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Your model 'sql-agent-3b' has been trained to use the MCP server at:\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m http://0.0.0.0:8903/mcp\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m To use this model in production:\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m 1. The model checkpoint is saved in ./.art/\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m 2. You can load it using the vLLM library\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m 3. Or continue training with more examples by adjusting the configuration at the top\n"
]
}
],
"source": [
"# @title Test Your Model!\n",
"\n",
"# Generate test inputs\n",
"print(\"Generating test inputs...\")\n",
"val_scenarios = [\n",
" McpScenario(\n",
" task_description=scenario[\"task\"],\n",
" max_turns=MAX_TURNS,\n",
" )\n",
" for scenario in raw_val_scenarios\n",
"]\n",
"\n",
"print(f\"\\n🧪 Testing the trained model on {len(val_scenarios)} new inputs:\\n\")\n",
"print(\"=\" * 80)\n",
"\n",
"for i, scenario in enumerate(val_scenarios):\n",
" print(f\"\\nTest {i + 1}:\")\n",
" print(f\"Input: {scenario.task_description}\")\n",
"\n",
" # Run the model\n",
" result_trajectory = await rollout(model, scenario)\n",
"\n",
" # Extract the model's response\n",
" messages = result_trajectory.messages()\n",
" model_response = messages[-1][\"content\"] if messages else \"No response\"\n",
"\n",
" print(f\"Model output: {model_response}\")\n",
" print(\"-\" * 80)\n",
"\n",
"print(\"\\n🎉 Testing completed!\")\n",
"print(\n",
" f\"\\nYour model '{MODEL_NAME}' has been trained to use the MCP server at:\"\n",
")\n",
"print(MCP_SERVER_URL)\n",
"print(\"\\nTo use this model in production:\")\n",
"print(\"1. The model checkpoint is saved in ./.art/\")\n",
"print(\"2. You can load it using the vLLM library\")\n",
"print(\n",
" \"3. Or continue training with more examples by adjusting the configuration at the top\"\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[{'task': 'For every department, show its budget, the total budget allocated to its projects, and the remaining budget (budget minus project budgets). Then provide a summary and a thorough analysis/report.',\n",
" 'difficulty': 4},\n",
" {'task': 'Determine which department has the most active projects. Then provide a summary and thorough analysis/report.',\n",
" 'difficulty': 4},\n",
" {'task': 'Determine the most common job role among all employees. Then provide a summary and thorough analysis/report.',\n",
" 'difficulty': 3},\n",
" {'task': 'Identify which department has the highest budget and report its name and location. Then produce a summary and thorough analysis/report.',\n",
" 'difficulty': 2},\n",
" {'task': \"Produce a report of all projects including the project lead's name and the department name they belong to. Then provide a summary and thorough analysis/report.\",\n",
" 'difficulty': 3},\n",
" {'task': 'For every department, calculate budget minus total salaries of employees in that department (budget variance). Then provide a summary and thorough analysis/report.',\n",
" 'difficulty': 3},\n",
" {'task': 'For each department, show budget, total salaries, and the difference (budget minus salaries). Then provide a summary and thorough analysis/report.',\n",
" 'difficulty': 4},\n",
" {'task': 'Simulate a 10% budget cut per department and identify which departments would still cover salaries, plus overall impact; then provide a summary and thorough analysis/report.',\n",
" 'difficulty': 5}]"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"raw_val_scenarios"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50168 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50176 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50184 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50186 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50198 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50206 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:19:13] rollout: discovered tools | count=3 names=['list_tables', 'describe_table', 'run_query']\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:19:13] LLM request | step=1 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Which department has the most active projects?...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:19:13] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 2,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:19:21] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"To determine which department has the most active projects, we need to first identify a suitable metric for project activity. Since no specific activity metric is provided, I'll assume that the number...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:19:21] Tool call received | name='list_tables' raw_args='{}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50092 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50098 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50112 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50118 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50128 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50138 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:19:21] Tool result | name='list_tables' len=40\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:19:21] LLM request | step=2 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Which department has the most active projects?...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:19:21] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 4,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:19:28] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The database contains three tables: 'departments', 'employees', and 'projects'. We need to focus on the 'projects' table to count the number of projects in each department. \\n\\nNext, I will describe the...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:19:28] Tool call received | name='describe_table' raw_args='{\"table_name\": \"projects\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50712 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50718 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50732 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50736 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50752 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50762 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:19:28] Tool result | name='describe_table' len=603\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:19:28] LLM request | step=3 model='sql-agent-3b@0' tools=4 last_user='Please complete this task: Which department has the most active projects?...'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:19:28] LLM request (preview):\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"model\": \"sql-agent-3b@0\",\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"messages_len\": 6,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"tools_len\": 4\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:19:44] LLM response parsed | finish_reason='tool_calls' has_tool_calls=True content_preview=\"The 'projects' table has the following structure:\\n- An auto-incremented ID for each project.\\n- A project name.\\n- A department ID that references the 'departments' table.\\n- A lead ID that references th...\"\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:19:44] Tool call received | name='run_query' raw_args='{\"sql\": \"SELECT department_id, COUNT(*) AS project_count FROM projects GROUP BY department_id ORDER BY project_count DESC LIMIT 1\"}'\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50506 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50518 - \"POST /mcp HTTP/1.1\" 202 Accepted\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50522 - \"GET /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50528 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50544 - \"POST /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m INFO: 127.0.0.1:50546 - \"DELETE /mcp HTTP/1.1\" 200 OK\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m [19:19:44] Tool result | name='run_query' len=103\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m Model output: {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"row_count\": 1,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"results\": [\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m {\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"department_id\": 3,\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m \"project_count\": 2\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m ]\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m }\n",
"\u001b[0;36m(APIServer pid=75472)\u001b[0;0m \u001b[0;36m(APIServer pid=75472)\u001b[0;0m --------------------------------------------------------------------------------\n"
]
}
],
"source": [
"scenario = McpScenario(\n",
" task_description=\"Which department has the most active projects?\",\n",
" max_turns=MAX_TURNS,\n",
")\n",
"\n",
"# Run the model\n",
"result_trajectory = await rollout(model, scenario)\n",
"\n",
"# Extract the model's response\n",
"messages = result_trajectory.messages()\n",
"model_response = messages[-1][\"content\"] if messages else \"No response\"\n",
"\n",
"print(f\"Model output: {model_response}\")\n",
"print(\"-\" * 80)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cellView": "form",
"id": "utI-VYM8s5lo"
},
"outputs": [],
"source": [
"# @title Upload to Hugging Face 🤗\n",
"\n",
"# Adapted from Unsloth Notebooks (https://github.com/unslothai/notebooks), licensed under GNU LGPL v3.0.\n",
"# © Unsloth contributors. Modifications © 2025 OpenPipe, Inc.\n",
"# See THIRD-PARTY-NOTICES and licenses/LGPL-3.0.txt for details.\n",
"\n",
"import torch\n",
"from unsloth import FastLanguageModel\n",
"\n",
"lora_model_path = (\n",
" f\".art/{model.project}/models/{model.name}/checkpoints/{await model.get_step():04d}\"\n",
")\n",
"\n",
"peft_model, peft_tokenizer = FastLanguageModel.from_pretrained(\n",
" model_name=lora_model_path,\n",
" max_seq_length=16384,\n",
" dtype=torch.bfloat16,\n",
" load_in_4bit=True,\n",
")\n",
"\n",
"UPLOAD_MODEL = False # Set True when you're ready to upload your model to Hugging Face\n",
"HF_ACCOUNT = \"your_hf_account\"\n",
"HF_TOKEN = \"your_hf_token\"\n",
"\n",
"if UPLOAD_MODEL:\n",
" peft_model.push_to_hub_merged(\n",
" f\"{HF_ACCOUNT}/{model.name}\", peft_tokenizer, token=HF_TOKEN\n",
" )"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "FuevYgXT-I1h"
},
"source": [
"### Next Steps\n",
"\n",
"Congratulations! You've successfully trained a custom model for your task using only:\n",
"- A pre-built MCP server\n",
"- Example inputs (no outputs needed!)\n",
"- RULER's automatic evaluation\n",
"\n",
"Here are some ways to improve results:\n",
"\n",
"1. **More diverse inputs**: Generate more varied input examples\n",
"2. **Longer training**: Increase the number of training steps\n",
"3. **More comparisons**: Increase `rollouts_per_group` for better RULER comparisons\n",
"4. **MCP server refinement**: Add better tools and resources to the server\n",
"5. **Hyperparameter tuning**: Adjust learning rate, batch size, etc.\n",
"\n",
"Remember: RULER learns what \"good\" means from your MCP server alone - no labeled data required!\n",
"\n",
"For more advanced use cases, check out the [ART documentation](https://art.openpipe.ai)."
]
}
],
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