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https://gitee.com/wanwujie/deer-flow
synced 2026-04-16 11:24:45 +08:00
* feat: add comprehensive debug logging for issue #477 hanging/freezing diagnosis - Add debug logging to src/server/app.py for event streaming and message chunk processing - Track graph event flow with thread IDs for correlation - Add detailed logging in interrupt event processing - Add debug logging to src/agents/tool_interceptor.py for tool execution and interrupt handling - Log interrupt decision flow and user feedback processing - Add debug logging to src/graph/nodes.py for agent node execution - Track step execution progress and agent coordination in research_team_node - Add debug logging to src/agents/agents.py for agent creation and tool wrapping - Update server.py to enable debug logging when --log-level debug is specified - Add thread ID correlation throughout for better diagnostics - Helps diagnose hanging/freezing issues during workflow execution * Apply suggestions from code review Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
This commit is contained in:
Willem Jiang
@@ -36,20 +36,42 @@ def create_agent(
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Returns:
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A configured agent graph
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"""
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logger.debug(
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f"Creating agent '{agent_name}' of type '{agent_type}' "
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f"with {len(tools)} tools and template '{prompt_template}'"
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)
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# Wrap tools with interrupt logic if specified
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processed_tools = tools
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if interrupt_before_tools:
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logger.info(
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f"Creating agent '{agent_name}' with tool-specific interrupts: {interrupt_before_tools}"
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)
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logger.debug(f"Wrapping {len(tools)} tools for agent '{agent_name}'")
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processed_tools = wrap_tools_with_interceptor(tools, interrupt_before_tools)
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logger.debug(f"Agent '{agent_name}' tool wrapping completed")
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else:
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logger.debug(f"Agent '{agent_name}' has no interrupt-before-tools configured")
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return create_react_agent(
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if agent_type not in AGENT_LLM_MAP:
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logger.warning(
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f"Agent type '{agent_type}' not found in AGENT_LLM_MAP. "
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f"Falling back to default LLM type 'basic' for agent '{agent_name}'. "
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"This may indicate a configuration issue."
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)
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llm_type = AGENT_LLM_MAP.get(agent_type, "basic")
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logger.debug(f"Agent '{agent_name}' using LLM type: {llm_type}")
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logger.debug(f"Creating ReAct agent '{agent_name}'")
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agent = create_react_agent(
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name=agent_name,
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model=get_llm_by_type(AGENT_LLM_MAP[agent_type]),
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model=get_llm_by_type(llm_type),
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tools=processed_tools,
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prompt=lambda state: apply_prompt_template(
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prompt_template, state, locale=state.get("locale", "en-US")
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),
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pre_model_hook=pre_model_hook,
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)
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logger.info(f"Agent '{agent_name}' created successfully")
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return agent
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@@ -84,47 +84,69 @@ class ToolInterceptor:
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BaseTool: The wrapped tool with interrupt capability
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"""
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original_func = tool.func
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logger.debug(f"Wrapping tool '{tool.name}' with interrupt capability")
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def intercepted_func(*args: Any, **kwargs: Any) -> Any:
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"""Execute the tool with interrupt check."""
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tool_name = tool.name
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logger.debug(f"[ToolInterceptor] Executing tool: {tool_name}")
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# Format tool input for display
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tool_input = args[0] if args else kwargs
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tool_input_repr = ToolInterceptor._format_tool_input(tool_input)
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logger.debug(f"[ToolInterceptor] Tool input: {tool_input_repr[:200]}")
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if interceptor.should_interrupt(tool_name):
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should_interrupt = interceptor.should_interrupt(tool_name)
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logger.debug(f"[ToolInterceptor] should_interrupt={should_interrupt} for tool '{tool_name}'")
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if should_interrupt:
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logger.info(
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f"Interrupting before tool '{tool_name}' with input: {tool_input_repr}"
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f"[ToolInterceptor] Interrupting before tool '{tool_name}'"
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)
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logger.debug(
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f"[ToolInterceptor] Interrupt message: About to execute tool '{tool_name}' with input: {tool_input_repr[:100]}..."
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)
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# Trigger interrupt and wait for user feedback
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feedback = interrupt(
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f"About to execute tool: '{tool_name}'\n\nInput:\n{tool_input_repr}\n\nApprove execution?"
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)
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logger.info(f"Interrupt feedback for '{tool_name}': {feedback}")
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try:
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feedback = interrupt(
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f"About to execute tool: '{tool_name}'\n\nInput:\n{tool_input_repr}\n\nApprove execution?"
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)
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logger.debug(f"[ToolInterceptor] Interrupt returned with feedback: {f'{feedback[:100]}...' if feedback and len(feedback) > 100 else feedback if feedback else 'None'}")
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except Exception as e:
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logger.error(f"[ToolInterceptor] Error during interrupt: {str(e)}")
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raise
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logger.debug(f"[ToolInterceptor] Processing feedback approval for '{tool_name}'")
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# Check if user approved
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if not ToolInterceptor._parse_approval(feedback):
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logger.warning(f"User rejected execution of tool '{tool_name}'")
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is_approved = ToolInterceptor._parse_approval(feedback)
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logger.info(f"[ToolInterceptor] Tool '{tool_name}' approval decision: {is_approved}")
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if not is_approved:
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logger.warning(f"[ToolInterceptor] User rejected execution of tool '{tool_name}'")
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return {
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"error": f"Tool execution rejected by user",
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"tool": tool_name,
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"status": "rejected",
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}
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logger.info(f"User approved execution of tool '{tool_name}'")
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logger.info(f"[ToolInterceptor] User approved execution of tool '{tool_name}', proceeding")
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# Execute the original tool
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try:
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logger.debug(f"[ToolInterceptor] Calling original function for tool '{tool_name}'")
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result = original_func(*args, **kwargs)
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logger.debug(f"Tool '{tool_name}' execution completed")
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logger.info(f"[ToolInterceptor] Tool '{tool_name}' execution completed successfully")
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logger.debug(f"[ToolInterceptor] Tool result length: {len(str(result))}")
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return result
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except Exception as e:
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logger.error(f"Error executing tool '{tool_name}': {str(e)}")
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logger.error(f"[ToolInterceptor] Error executing tool '{tool_name}': {str(e)}")
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raise
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# Replace the function and update the tool
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# Use object.__setattr__ to bypass Pydantic validation
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logger.debug(f"Attaching intercepted function to tool '{tool.name}'")
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object.__setattr__(tool, "func", intercepted_func)
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return tool
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