# ========= Copyright 2026 @ Strukto.AI All Rights Reserved. ========= # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ========= Copyright 2026 @ Strukto.AI All Rights Reserved. ========= import os from deepagents import create_deep_agent from dotenv import load_dotenv from langchain_anthropic import ChatAnthropic from mirage import MountMode, Workspace from mirage.agents.langchain import (LangchainWorkspace, build_system_prompt, extract_text) from mirage.resource.s3 import S3Config, S3Resource load_dotenv(".env.development") config = S3Config( bucket=os.environ["AWS_S3_BUCKET"], region=os.environ.get("AWS_DEFAULT_REGION", "us-east-1"), aws_access_key_id=os.environ["AWS_ACCESS_KEY_ID"], aws_secret_access_key=os.environ["AWS_SECRET_ACCESS_KEY"], ) s3 = S3Resource(config) ws = Workspace({"/s3/": s3}, mode=MountMode.READ) agent = create_deep_agent( model=ChatAnthropic(model="claude-sonnet-4-20250514"), system_prompt=build_system_prompt( mount_info={"/s3/": "S3 bucket (CSV, Parquet, JSONL)"}, ), backend=LangchainWorkspace(ws), ) task = ("Explore and summarize the data in /s3/data/." " Use head command for large files.") result = agent.invoke({"messages": [{"role": "user", "content": task}]}) for text in extract_text(result["messages"]): print(text) task2 = ("How many rows are in the parquet, orc, and h5 files" " under /s3/data/? ") result2 = agent.invoke({"messages": [{"role": "user", "content": task2}]}) for text in extract_text(result2["messages"]): print(text) records = ws.ops.records if records: total = sum(r.bytes for r in records) print(f"\n--- {len(records)} ops, {total:,} bytes ---") for r in records: print(f" {r.op:<8} {r.source:<8} {r.bytes:>10,} B " f"{r.duration_ms:>5} ms {r.path}")