mirror of
https://github.com/bytedance/deer-flow.git
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c43c803f66
* fix: remove mismatched context param in debug.py to suppress Pydantic warning
The ainvoke call passed context={"thread_id": ...} but the agent graph
has no context_schema (ContextT defaults to None), causing a
PydanticSerializationUnexpectedValue warning on every invocation.
Align with the production run_agent path by injecting context via
Runtime into configurable["__pregel_runtime"] instead.
Closes #2445
Made-with: Cursor
* refactor: derive runtime thread_id from config to avoid duplication
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Made-with: Cursor
---------
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
96 lines
2.5 KiB
Python
96 lines
2.5 KiB
Python
#!/usr/bin/env python
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"""
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Debug script for lead_agent.
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Run this file directly in VS Code with breakpoints.
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Requirements:
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Run with `uv run` from the backend/ directory so that the uv workspace
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resolves deerflow-harness and app packages correctly:
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cd backend && PYTHONPATH=. uv run python debug.py
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Usage:
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1. Set breakpoints in agent.py or other files
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2. Press F5 or use "Run and Debug" panel
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3. Input messages in the terminal to interact with the agent
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"""
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import asyncio
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import logging
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from dotenv import load_dotenv
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from langchain_core.messages import HumanMessage
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from langgraph.runtime import Runtime
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from deerflow.agents import make_lead_agent
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load_dotenv()
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logging.basicConfig(
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level=logging.INFO,
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format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
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datefmt="%Y-%m-%d %H:%M:%S",
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)
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async def main():
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# Initialize MCP tools at startup
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try:
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from deerflow.mcp import initialize_mcp_tools
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await initialize_mcp_tools()
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except Exception as e:
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print(f"Warning: Failed to initialize MCP tools: {e}")
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# Create agent with default config
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config = {
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"configurable": {
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"thread_id": "debug-thread-001",
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"thinking_enabled": True,
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"is_plan_mode": True,
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# Uncomment to use a specific model
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"model_name": "kimi-k2.5",
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}
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}
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runtime = Runtime(context={"thread_id": config["configurable"]["thread_id"]})
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config["configurable"]["__pregel_runtime"] = runtime
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agent = make_lead_agent(config)
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print("=" * 50)
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print("Lead Agent Debug Mode")
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print("Type 'quit' or 'exit' to stop")
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print("=" * 50)
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while True:
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try:
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user_input = input("\nYou: ").strip()
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if not user_input:
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continue
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if user_input.lower() in ("quit", "exit"):
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print("Goodbye!")
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break
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# Invoke the agent
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state = {"messages": [HumanMessage(content=user_input)]}
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result = await agent.ainvoke(state, config=config)
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# Print the response
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if result.get("messages"):
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last_message = result["messages"][-1]
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print(f"\nAgent: {last_message.content}")
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except KeyboardInterrupt:
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print("\nInterrupted. Goodbye!")
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break
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except Exception as e:
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print(f"\nError: {e}")
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import traceback
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traceback.print_exc()
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if __name__ == "__main__":
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asyncio.run(main())
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