82 lines
2.4 KiB
Python
82 lines
2.4 KiB
Python
"""Deep agent: web search + virtual files → real filesystem export."""
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import os
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import asyncio
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from pathlib import Path
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from dotenv import load_dotenv
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from langchain_openai import ChatOpenAI
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from langchain_core.messages import HumanMessage
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from langchain.tools import tool
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from deepagents import create_deep_agent
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from deepagents.backends import LocalShellBackend, CompositeBackend
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load_dotenv()
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llm = ChatOpenAI(
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model="openai/gpt-oss-20b:free",
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base_url="https://openrouter.ai/api/v1",
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api_key=os.getenv("OPENAI_API_KEY"),
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temperature=0.0,
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)
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WORKSPACE = Path("./workspace")
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REAL_OUT = Path("./output")
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@tool
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def web_search(query: str) -> str:
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"""Search the web for information and return snippets."""
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try:
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from duckduckgo_search import DDGS
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with DDGS() as ddgs:
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results = list(ddgs.text(query, max_results=5))
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return "\n".join(f"{r['title']}: {r['body']}" for r in results)
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except Exception as exc:
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return f"Search error: {exc}"
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backend = CompositeBackend(
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default=LocalShellBackend(
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root_dir=str(WORKSPACE),
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virtual_mode=True,
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inherit_env=True,
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),
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)
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agent = create_deep_agent(
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model=llm,
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tools=[web_search],
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backend=backend,
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system_prompt=(
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"You are a research agent. "
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"Use web_search to find information, then create virtual files with write_file. "
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"When done, export all virtual files to real filesystem by calling execute with "
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"a shell command that copies /virtual/ contents to the output directory."
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),
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)
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async def main(query: str = "Python LangChain agent best practices 2024") -> None:
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WORKSPACE.mkdir(parents=True, exist_ok=True)
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REAL_OUT.mkdir(parents=True, exist_ok=True)
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config = {"configurable": {"thread_id": "research-session-1"}}
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result = await agent.ainvoke(
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{"messages": [HumanMessage(
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content=(
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f"Search the web for: {query}\n"
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"Save your findings to results.txt as a virtual file.\n"
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"Then export the virtual file results.txt to the real filesystem "
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f"at {REAL_OUT}/results.txt"
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)
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)]},
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config,
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)
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print(result["messages"][-1].content)
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if __name__ == "__main__":
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import sys
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q = " ".join(sys.argv[1:]) if len(sys.argv) > 1 else "Python LangChain agent best practices 2024"
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asyncio.run(main(q))
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