#!/usr/bin/env python """ Debug script for lead_agent. Run this file directly in VS Code with breakpoints. Requirements: Run with `uv run` from the backend/ directory so that the uv workspace resolves deerflow-harness and app packages correctly: cd backend && PYTHONPATH=. uv run python debug.py Usage: 1. Set breakpoints in agent.py or other files 2. Press F5 or use "Run and Debug" panel 3. Input messages in the terminal to interact with the agent """ import asyncio import logging from dotenv import load_dotenv from langchain_core.messages import HumanMessage from deerflow.agents import make_lead_agent load_dotenv() logging.basicConfig( level=logging.INFO, format="%(asctime)s - %(name)s - %(levelname)s - %(message)s", datefmt="%Y-%m-%d %H:%M:%S", ) async def main(): # Initialize MCP tools at startup try: from deerflow.mcp import initialize_mcp_tools await initialize_mcp_tools() except Exception as e: print(f"Warning: Failed to initialize MCP tools: {e}") # Create agent with default config config = { "configurable": { "thread_id": "debug-thread-001", "thinking_enabled": True, "is_plan_mode": True, # Uncomment to use a specific model "model_name": "kimi-k2.5", } } agent = make_lead_agent(config) print("=" * 50) print("Lead Agent Debug Mode") print("Type 'quit' or 'exit' to stop") print("=" * 50) while True: try: user_input = input("\nYou: ").strip() if not user_input: continue if user_input.lower() in ("quit", "exit"): print("Goodbye!") break # Invoke the agent state = {"messages": [HumanMessage(content=user_input)]} result = await agent.ainvoke(state, config=config, context={"thread_id": "debug-thread-001"}) # Print the response if result.get("messages"): last_message = result["messages"][-1] print(f"\nAgent: {last_message.content}") except KeyboardInterrupt: print("\nInterrupted. Goodbye!") break except Exception as e: print(f"\nError: {e}") import traceback traceback.print_exc() if __name__ == "__main__": asyncio.run(main())