deer-flow/backend/debug.py
He Wang 4063dd7157
feat(debug): print presented file paths with physical resolution (#2825)
Surface artifacts produced via the present_files tool in the CLI debug
REPL so headless clients without a frontend (VS Code launch configs,
etc.) can locate output files. Each turn prints newly added artifacts
plus their resolved host path. Works for any source that goes through
present_files — ACP agents, subagents, or sandbox writes.

Co-authored-by: Claude Opus 4 <noreply@anthropic.com>
2026-05-09 18:21:01 +08:00

169 lines
5.8 KiB
Python

#!/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
try:
from prompt_toolkit import PromptSession
from prompt_toolkit.history import InMemoryHistory
_HAS_PROMPT_TOOLKIT = True
except ImportError:
_HAS_PROMPT_TOOLKIT = False
load_dotenv()
_LOG_FMT = "%(asctime)s - %(name)s - %(levelname)s - %(message)s"
_LOG_DATEFMT = "%Y-%m-%d %H:%M:%S"
def _setup_logging(log_level: int = logging.INFO) -> None:
"""Route logs to ``debug.log`` using *log_level* for the initial root/file setup.
This configures the root logger and the ``debug.log`` file handler so logs do
not print on the interactive console. It is idempotent: any pre-existing
handlers on the root logger (e.g. installed by ``logging.basicConfig`` in
transitively imported modules) are removed so the debug session output only
lands in ``debug.log``.
Note: later config-driven logging adjustments may change named logger
verbosity without raising the root logger or file-handler thresholds set
here, so the eventual contents of ``debug.log`` may not be filtered solely by
this function's ``log_level`` argument.
"""
root = logging.root
for h in list(root.handlers):
root.removeHandler(h)
h.close()
root.setLevel(log_level)
file_handler = logging.FileHandler("debug.log", mode="a", encoding="utf-8")
file_handler.setLevel(log_level)
file_handler.setFormatter(logging.Formatter(_LOG_FMT, datefmt=_LOG_DATEFMT))
root.addHandler(file_handler)
async def main():
# Install file logging first so warnings emitted while loading config do not
# leak onto the interactive terminal via Python's lastResort handler.
_setup_logging()
from deerflow.config import get_app_config
from deerflow.config.app_config import apply_logging_level
app_config = get_app_config()
apply_logging_level(app_config.log_level)
# Delay the rest of the deerflow imports until *after* logging is installed
# so that any import-time side effects (e.g. deerflow.agents starts a
# background skill-loader thread on import) emit logs to debug.log instead
# of leaking onto the interactive terminal via Python's lastResort handler.
from langchain_core.messages import HumanMessage
from langgraph.runtime import Runtime
from deerflow.agents import make_lead_agent
from deerflow.config.paths import get_paths
from deerflow.mcp import initialize_mcp_tools
from deerflow.runtime.user_context import get_effective_user_id
# Initialize MCP tools at startup
try:
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",
}
}
runtime = Runtime(context={"thread_id": config["configurable"]["thread_id"]})
config["configurable"]["__pregel_runtime"] = runtime
agent = make_lead_agent(config)
session = PromptSession(history=InMemoryHistory()) if _HAS_PROMPT_TOOLKIT else None
print("=" * 50)
print("Lead Agent Debug Mode")
print("Type 'quit' or 'exit' to stop")
print(f"Logs: debug.log (log_level={app_config.log_level})")
if not _HAS_PROMPT_TOOLKIT:
print("Tip: `uv sync --group dev` to enable arrow-key & history support")
print("=" * 50)
seen_artifacts: set[str] = set()
while True:
try:
if session:
user_input = (await session.prompt_async("\nYou: ")).strip()
else:
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)
# Print the response
if result.get("messages"):
last_message = result["messages"][-1]
print(f"\nAgent: {last_message.content}")
# Show files presented to the user this turn (new artifacts only)
artifacts = result.get("artifacts") or []
new_artifacts = [p for p in artifacts if p not in seen_artifacts]
if new_artifacts:
thread_id = config["configurable"]["thread_id"]
user_id = get_effective_user_id()
paths = get_paths()
print("\n[Presented files]")
for virtual in new_artifacts:
try:
physical = paths.resolve_virtual_path(thread_id, virtual, user_id=user_id)
print(f" - {virtual}\n{physical}")
except ValueError as exc:
print(f" - {virtual} (failed to resolve physical path: {exc})")
seen_artifacts.update(new_artifacts)
except (KeyboardInterrupt, EOFError):
print("\nGoodbye!")
break
except Exception as e:
print(f"\nError: {e}")
import traceback
traceback.print_exc()
if __name__ == "__main__":
asyncio.run(main())