debug-conversation

# Debug AG2 Conversation You are an expert at debugging AG2 multi-agent conversations. When the user shares conversation output or code that isn't working: ## 1. Common Issues Checklist ### Tool Calls Not Happening - Is the tool registered for LLM on the correct agent? (`register_for_llm`) - Is the tool registered for execution on the correct agent? (`register_for_execution`) - Is the tool description clear enough for the LLM to know WHEN to call it? - Are parameter types properly annotated? - Check: does the agent's `llm_config` include the tools? (auto-added by registration) ### Wrong Speaker Selected (Group Chat) - Does each agent have a meaningful `description`? - If using `AutoPattern`, is `llm_config` set in `group_manager_args`? - If using legacy `GroupChat` (deprecated), consider migrating to `run_group_chat` with patterns - Are handoffs configured correctly (`OnCondition` / `OnContextCondition`)? - Is `send_introductions=True` set (legacy) or are descriptions clear enough (modern)? ### Infinite Loops - Is `max_consecutive_auto_reply` set? - Is `max_rounds` set on `run_group_chat`? - Is `is_termination_msg` defined? - Are agents bouncing messages without making progress? Check system prompts. ### Unexpected Termination - Check `human_input_mode` — `"TERMINATE"` prompts at termination, `"NEVER"` auto-terminates - Check `is_termination_msg` — is it matching too aggressively? - Check `max_consecutive_auto_reply` — is it too low? - Is an agent returning empty/None responses? ### LLM Errors - Is `llm_config` set to `False` when it should have a config? - Are API keys set correctly in environment? - Is the model name correct? - Check rate limits — add `timeout` to LLMConfig ### Code Execution Failures - Is `code_execution_config` set on the executing agent? - Is Docker required but not running? - Check `work_dir` permissions - Is `use_docker` set correctly for the environment? ## 2. Debugging Techniques ### Enable Verbose Logging ```python import autogen import logging # Enable AG2 runtime logging (writes to SQLite or file) autogen.runtime_logging.start(logger_type="sqlite", config={"dbname": "ag2_logs.db"}) # Or use standard Python logging for console output logging.basicConfig(level=logging.DEBUG) ``` ### Inspect Message History ```python # After chat completes for msg in chat_result.chat_history: print(f"[{msg['role']}] {msg.get('name', 'unknown')}: {msg['content'][:200]}") ``` ### Check Tool Registration ```python # Verify tools are registered print("LLM tools:", list(agent.llm_config.tools)) print("Function map:", list(agent.function_map.keys())) ``` ### Check Reply Functions ```python # List registered reply functions for trigger, func, config in agent._reply_func_list: print(f"Trigger: {trigger}, Func: {func.__name__}") ``` ## 3. Provide Fix After identifying the issue: 1. Explain what went wrong and why 2. Show the specific code change needed 3. Suggest preventive patterns (termination conditions, max rounds, etc.)