import os
import asyncio
from langchain_openai import ChatOpenAI
from langchain_core.messages import HumanMessage
from langchain.tools import tool
from deepagents import create_deep_agent
from deepagents.backends import FilesystemBackend, LocalShellBackend, CompositeBackend

# LLM via BroJS
llm = ChatOpenAI(
    model="openai/gpt-oss-20b:free",
    base_url="https://platform.brojs.ru/jrnl-bh/api/inference/v1",
    api_key=os.getenv("JOURNAL_MCP_PAT"),
    temperature=0.5,
)

# Backend: local shell + virtual FS
backend = CompositeBackend([
    LocalShellBackend(workspace_dir="./workspace"),
    FilesystemBackend(),
])

# Web search tool using duckduckgo-search
@tool
def web_search(query: str) -> str:
    """Search the web for information."""
    try:
        from duckduckgo_search import DDGS
        with DDGS() as ddgs:
            results = list(ddgs.text(query, max_results=5))
        return "\n".join(f"{r['title']}: {r['body']}" for r in results)
    except Exception as e:
        return f"Search error: {e}"

# Deep agent
agent = create_deep_agent(
    llm=llm,
    tools=[web_search],
    backend=backend,
    system_prompt="You are a helpful research agent that can search the web and create virtual files. At the end, export files to the real filesystem.",
)

async def main():
    # Example: ask agent to research "Python async" and create a file with results
    user_query = "Python async programming"  # can be replaced by user input
    result = await agent.ainvoke(
        {"messages": [HumanMessage(content=user_query)]},
        {"configurable": {"thread_id": "session-1"}},
    )
    # The agent will create virtual files during its execution.
    # After completion, export virtual FS to real FS
    await backend.export_to_real_fs("./exported_files")
    print("Exported virtual files to ./exported_files")

if __name__ == "__main__":
    asyncio.run(main())