DATA
6de0bf9f5b
Vendored deer-flow upstream (bytedance/deer-flow) plus prompt-injection hardening: - New deerflow.security package: content_delimiter, html_cleaner, sanitizer (8 layers — invisible chars, control chars, symbols, NFC, PUA, tag chars, horizontal whitespace collapse with newline/tab preservation, length cap) - New deerflow.community.searx package: web_search, web_fetch, image_search backed by a private SearX instance, every external string sanitized and wrapped in <<<EXTERNAL_UNTRUSTED_CONTENT>>> delimiters - All native community web providers (ddg_search, tavily, exa, firecrawl, jina_ai, infoquest, image_search) replaced with hard-fail stubs that raise NativeWebToolDisabledError at import time, so a misconfigured tool.use path fails loud rather than silently falling back to unsanitized output - Native client back-doors (jina_client.py, infoquest_client.py) stubbed too - Native-tool tests quarantined under tests/_disabled_native/ (collect_ignore_glob via local conftest.py) - Sanitizer Layer 7 fix: only collapse horizontal whitespace, preserve newlines and tabs so list/table structure survives - Hardened runtime config.yaml references only the searx-backed tools - Factory overlay (backend/) kept in sync with deer-flow tree as a reference / source See HARDENING.md for the full audit trail and verification steps.
92 lines
2.4 KiB
Python
92 lines
2.4 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 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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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, context={"thread_id": "debug-thread-001"})
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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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