""" 主脑Agent - 简化版（无意图分类） 职责： 1. 输入处理：图片、音频、文本提取 2. 直接路由：根据外部传入的 route_flag 决定调用哪个工作流 工作流列表（来自 workflow_registry）： - 故障排查与修理 - 舰船百科 - 操作使用 """ from typing import TypedDict, Literal, Optional, Dict, Any, List from langgraph.graph import StateGraph, START, END from tools.function_tool import ( vlm_image_to_text, asr_audio_to_text, detect_input_type ) from modelsAPI.model_api import OpenaiAPI from utils.function_tracker import track_function_calls from workflow_registry import VALID_ROUTE_FLAGS import json import re class MainAgentState(TypedDict): """主脑Agent状态""" raw_input: Dict[str, Any] has_image: bool has_audio: bool has_query: bool has_file_text: bool input_type: str history_message: str extracted_text: str image_description: str asr_text: str file_text: str combined_query: str workflow_result: Optional[Dict[str, Any]] final_response: str error_message: str route_flag: str route_params: Dict[str, Any] def detect_input_type_node(state: MainAgentState) -> Dict[str, Any]: """检测输入类型""" raw = state["raw_input"] result = detect_input_type.invoke({"raw_input": raw}) has_image = result.get("has_image", False) has_audio = result.get("has_audio", False) has_query = result.get("has_query", False) has_file_text = False file_text_v = raw.get("file_text") if isinstance(file_text_v, str) and file_text_v.strip(): has_file_text = True input_type = "mixed" count = sum([has_image, has_audio, has_query, has_file_text]) if count == 1: if has_image: input_type = "image" elif has_audio: input_type = "audio" elif has_query: input_type = "text" elif has_file_text: input_type = "file" return { "has_image": has_image, "has_audio": has_audio, "has_query": has_query, "has_file_text": has_file_text, "input_type": input_type, } async def process_multimodal_input(state: MainAgentState) -> Dict[str, Any]: """处理多模态输入""" has_image = state.get("has_image", False) has_audio = state.get("has_audio", False) has_query = state.get("has_query", False) has_file_text = state.get("has_file_text", False) raw = state["raw_input"] image_description = "" asr_text = "" extracted_text = "" try: if has_image: image_path = raw.get("image", "") if image_path: try: image_description = await vlm_image_to_text.ainvoke({ "image_path": image_path }) if not image_description or image_description.startswith("VLM 调用失败"): image_description = "" except Exception: image_description = "" if has_audio: audio_path = raw.get("audio", "") if audio_path: try: asr_text = await asr_audio_to_text.ainvoke({ "audio_path": audio_path }) if not asr_text or asr_text.startswith("ASR 调用失败"): asr_text = "" except Exception: asr_text = "" text_parts = [] if raw.get("query"): text_parts.append(raw["query"]) if image_description: text_parts.append(f"[图片描述] {image_description}") if asr_text: text_parts.append(f"[语音转文字] {asr_text}") if raw.get("file_text"): text_parts.append(f"[文件内容] {raw['file_text']}") extracted_text = "\n".join(text_parts) if text_parts else "" combined_query = raw.get("query", "") or extracted_text return { "extracted_text": extracted_text, "image_description": image_description, "asr_text": asr_text, "combined_query": combined_query, "file_text": raw.get("file_text", ""), } except Exception as e: return { "error_message": f"输入处理失败: {str(e)}", "extracted_text": "", } # @track_function_calls def route_to_workflow(state: MainAgentState) -> Dict[str, Any]: """ 🤖分析意图，调用相关智能体 """ route_flag = state.get("route_flag", "故障排查与修理") if route_flag not in VALID_ROUTE_FLAGS: route_flag = "故障排查与修理" query_text = state.get("extracted_text", "") combined_query = state.get("combined_query", "") or query_text raw_input = state.get("raw_input", {}) history_message = raw_input.get("history_message", "") route_params = { "extracted_text": query_text, "combined_query": combined_query, "history_message": history_message, } if raw_input.get("file_text"): route_params["file_text"] = raw_input["file_text"] print(f"[主脑Agent] 路由到: {route_flag}") print(f"[主脑Agent] 参数: combined_query={combined_query[:100]}...") if route_flag == "故障排查与修理": detail = "正在调用故障排查与修理智能体" elif route_flag == "舰船百科": detail = "正在调用舰船百科智能体" elif route_flag == "操作使用": detail = "正在调用操作使用智能体" elif route_flag == "统计": detail = "正在调用统计智能体" else: detail = "正在调用通用智能体" return { "route_flag": route_flag, "route_params": route_params, "__detail__": detail, } def create_main_agent(): """创建主脑Agent""" workflow = StateGraph(MainAgentState) workflow.add_node("detect_input_type", detect_input_type_node) workflow.add_node("process_input", process_multimodal_input) workflow.add_node("route", route_to_workflow) workflow.add_edge(START, "detect_input_type") workflow.add_edge("detect_input_type", "process_input") workflow.add_edge("process_input", "route") workflow.add_edge("route", END) return workflow.compile() from workflows.history_manager import filter_image_urls async def extract_conversation_title(content: str) -> str: """提取对话标题""" try: prompt = f"请从以下对话内容中提取一个简短的标题（不超过20字）：\n\n{content[:500]}" response = await OpenaiAPI.open_api_chat_without_thinking( query=prompt, model=None, system_prompt="你是一个标题提取助手，请从对话内容中提取一个简短的标题。", messages=[] ) title = response.strip() if response else "新对话" if len(title) > 30: title = title[:30] + "..." return title except Exception: return "新对话" if __name__ == "__main__": import asyncio async def test(): print("测试主脑Agent") agent = create_main_agent() result = await agent.ainvoke({ "raw_input": {"query": "101舰主机发生异响"}, "route_flag": "故障排查与修理" }) print(f"结果: {result}") asyncio.run(test())