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, CompositeBackend

# LLM configuration using OpenRouter
llm = ChatOpenAI(
    model="openai/gpt-oss-20b:free",
    base_url="https://openrouter.ai/api/v1",
    api_key=os.getenv("OPENAI_API_KEY"),
    temperature=0.0,
)

# Backend: real filesystem in current directory
backend = CompositeBackend([
    FilesystemBackend(),
])

@tool
async def web_search(query: str) -> str:
    """Search the web for information using DuckDuckGo."""
    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}"

@tool
def write_file(path: str, content: str) -> str:
    """Write a file to the local filesystem."""
    try:
        with open(path, 'w', encoding='utf-8') as f:
            f.write(content)
        return f"File written to {path}"
    except Exception as e:
        return f"Error writing file: {e}"

agent = create_deep_agent(
    llm=llm,
    tools=[web_search, write_file],
    backend=backend,
    system_prompt="You are a helpful research assistant. Your task is to search the web for information on a given topic and then create virtual files with the results. At the end of the conversation, ensure all generated files are written to disk.",
)

async def main():
    # Example interaction: ask about Python best practices
    result = await agent.ainvoke(
        {"messages": [HumanMessage(content="Search for Python best practices and save to results.txt")]},
        {"configurable": {"thread_id": "session-1"}},
    )
    print(result["messages"][-1].content)

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