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146 lines
4.4 KiB
Python
146 lines
4.4 KiB
Python
from __future__ import annotations
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import json
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from scripts.prepare_native_tool_calling_data import (
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native_record_from_eliza,
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source_matrix,
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validate_native_record,
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)
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def _entry(slug: str = "hermes-fc-v1", normalizer: str = "hermes_fc") -> dict:
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return {
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"slug": slug,
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"repo_id": "example/source",
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"normalizer": normalizer,
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"license": "mit",
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"priority": "core",
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"weight": 1.0,
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"est_size_gb": 0.1,
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}
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def test_legacy_task_call_unwraps_to_native_planner_call() -> None:
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expected = {
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"thought": "Need weather data before replying.",
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"actions": [
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{
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"name": "TASK_CALL",
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"params": {
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"tool": "get_weather",
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"arguments": {"city": "Los Angeles"},
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},
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}
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],
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"providers": [],
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"text": "",
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"simple": False,
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}
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record = {
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"roomName": "room",
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"agentId": "agent",
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"memoryEntries": [],
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"currentMessage": {"role": "user", "content": "weather in LA?"},
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"expectedResponse": json.dumps(expected),
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"availableActions": ["REPLY", "TASK_CALL"],
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"metadata": {
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"task_type": "tool_call",
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"source_dataset": "hermes-fc-v1",
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"split": "train",
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"license": "mit",
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},
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}
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native, error = native_record_from_eliza(record, _entry(), decoder=None)
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assert error is None
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assert native is not None
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assert native["stage"] == "planner"
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call = native["output"]["planner"]["toolCalls"][0]
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assert call["name"] == "get_weather"
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assert call["args"] == {"city": "Los Angeles"}
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tool_names = {t["function"]["name"] for t in native["tools"]}
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assert "get_weather" in tool_names
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assert validate_native_record(native) == (True, "")
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def test_routing_row_converts_to_message_handler_schema() -> None:
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expected = {
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"name": "agent",
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"reasoning": "The user is asking for scheduling help.",
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"action": "RESPOND",
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"primaryContext": "calendar",
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"secondaryContexts": ["contacts"],
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"evidenceTurnIds": [],
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}
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record = {
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"roomName": "room",
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"agentId": "agent",
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"memoryEntries": [],
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"currentMessage": {"role": "user", "content": "schedule lunch with Sam"},
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"expectedResponse": json.dumps(expected),
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"availableActions": ["RESPOND", "IGNORE", "STOP"],
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"metadata": {
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"task_type": "should_respond",
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"source_dataset": "scambench",
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"split": "validation",
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"license": "mit",
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},
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}
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native, error = native_record_from_eliza(
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record,
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_entry("scambench", "scambench_passthrough"),
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decoder=None,
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)
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assert error is None
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assert native is not None
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assert native["stage"] == "message_handler"
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result = native["output"]["messageHandler"]
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assert result["action"] == "RESPOND"
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assert result["contexts"] == ["calendar", "contacts"]
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assert result["simple"] is False
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assert "evidenceTurnIds" not in result
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def test_legacy_non_json_tool_call_is_skipped_not_inferred_as_reply() -> None:
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record = {
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"roomName": "room",
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"agentId": "agent",
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"memoryEntries": [],
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"currentMessage": {"role": "user", "content": "weather in LA?"},
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"expectedResponse": "tool_calls[1]:\n name: get_weather\n arguments:\n city: Los Angeles",
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"availableActions": ["REPLY", "TASK_CALL"],
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"metadata": {
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"task_type": "tool_call",
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"source_dataset": "hermes-fc-v1",
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"split": "train",
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"license": "mit",
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},
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}
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native, error = native_record_from_eliza(record, _entry(), decoder=None)
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assert native is None
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assert error is not None
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assert "legacy non-JSON structured expectedResponse skipped" in error
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def test_source_matrix_marks_missing_local_path() -> None:
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rows = source_matrix([
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{
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"slug": "nubilio-trajectories",
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"local_path": "local-corpora/not-present",
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"normalizer": "nubilio_trajectories",
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"license": "proprietary",
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"priority": "core",
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"weight": 3.0,
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}
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])
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assert rows[0]["raw_status"] == "local_missing"
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assert rows[0]["default_include"] is False
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assert any("local_path is missing" in w for w in rows[0]["weaknesses"])
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