"""灵犀飞书长连接 — 固定路由到灵犀学习助手 Agent（方案C：知识图谱+RAG）""" from __future__ import annotations import asyncio import json import logging from collections import deque from typing import Optional from app.core.config import settings logger = logging.getLogger(__name__) _processed_msg_ids: deque[str] = deque(maxlen=20) def _get_message_id(data) -> Optional[str]: try: ev = data.event msg = getattr(ev, "message", None) if msg: return getattr(msg, "message_id", None) except Exception: return None return None def _get_message_text(data) -> Optional[str]: try: ev = data.event msg = getattr(ev, "message", None) if not msg: return None content_str = getattr(msg, "content", None) msg_type = getattr(msg, "message_type", "") if not content_str: return None if msg_type == "text": parsed = json.loads(content_str) return parsed.get("text", "") return None except Exception as e: logger.warning("解析灵犀消息内容失败: %s", e) return None def _get_sender_open_id(data) -> Optional[str]: try: ev = data.event sender = getattr(ev, "sender", None) if not sender: return None sender_id = getattr(sender, "sender_id", None) if not sender_id: return None return getattr(sender_id, "open_id", None) except Exception: return None def _get_chat_type(data) -> str: try: ev = data.event msg = getattr(ev, "message", None) return getattr(msg, "chat_type", "") if msg else "" except Exception: return "" def _reply_to_feishu(open_id: str, text: str): try: from app.services.lingxi_app_service import send_plain_text send_plain_text(open_id, text) except Exception as e: logger.warning("灵犀回复消息失败: %s", e) def _reply_card(open_id: str, title: str, content: str, status: str = "info"): try: from app.services.lingxi_app_service import send_message_to_user send_message_to_user(open_id, title, content, status=status) except Exception as e: logger.warning("灵犀回复卡片失败: %s", e) def _make_llm_logger(db, agent_id: Optional[str] = None, user_id: Optional[str] = None): def _log(metrics: dict): try: from app.models.agent_llm_log import AgentLLMLog log = AgentLLMLog( agent_id=agent_id, session_id=metrics.get("session_id"), user_id=user_id, model=metrics.get("model", ""), provider=metrics.get("provider"), prompt_tokens=metrics.get("prompt_tokens", 0), completion_tokens=metrics.get("completion_tokens", 0), total_tokens=metrics.get("total_tokens", 0), latency_ms=metrics.get("latency_ms", 0), iteration_number=metrics.get("iteration_number", 0), step_type=metrics.get("step_type"), tool_name=metrics.get("tool_name"), status=metrics.get("status", "success"), error_message=metrics.get("error_message"), ) db.add(log) db.commit() except Exception as e: logger.warning("写入 AgentLLMLog 失败: %s", e) return _log async def _handle_message_async(data): open_id = _get_sender_open_id(data) chat_type = _get_chat_type(data) text = _get_message_text(data) if not open_id or chat_type != "p2p": return logger.info("灵犀收到消息: open_id=%s text=%s", open_id[:20], text[:50] if text else "(空)") if not text: return from sqlalchemy.orm import Session from app.core.database import SessionLocal from app.models.agent import Agent db: Optional[Session] = None try: db = SessionLocal() agent_id = settings.LINGXI_AGENT_ID if not agent_id: _reply_to_feishu(open_id, "灵犀尚未配置，请联系管理员。") return agent = db.query(Agent).filter(Agent.id == agent_id).first() if not agent: _reply_to_feishu(open_id, "灵犀 Agent 已不存在，请联系管理员。") return _reply_to_feishu(open_id, "正在思考，请稍候...") from app.agent_runtime import AgentRuntime, AgentConfig, AgentLLMConfig, AgentToolConfig, AgentMemoryConfig wc = agent.workflow_config or {} nodes = wc.get("nodes", []) system_prompt = agent.description or "" model = "deepseek-v4-flash" provider = "deepseek" temperature = 0.85 max_iterations = 30 tools_whitelist = [] for n in nodes: if n.get("type") not in ("agent", "llm", "template"): continue cfg = n.get("data", {}) if isinstance(n, dict) else getattr(n, "data", {}) system_prompt = cfg.get("system_prompt", "") or system_prompt model = cfg.get("model", model) provider = cfg.get("provider", provider) temperature = float(cfg.get("temperature", temperature)) max_iterations = int(cfg.get("max_iterations", max_iterations)) tools_whitelist = cfg.get("tools", tools_whitelist) break config = AgentConfig( name=agent.name or "灵犀", system_prompt=system_prompt, llm=AgentLLMConfig( model=model, provider=provider, temperature=temperature, max_iterations=max_iterations, ), tools=AgentToolConfig(include_tools=tools_whitelist), memory=AgentMemoryConfig( max_history_messages=int(cfg.get("memory_max_history", 20)), vector_memory_top_k=int(cfg.get("memory_vector_top_k", 5)), persist_to_db=bool(cfg.get("memory_persist", True)), vector_memory_enabled=bool(cfg.get("memory_vector_enabled", True)), learning_enabled=bool(cfg.get("memory_learning", True)), ), user_id=None, memory_scope_id=str(agent.id), ) on_llm_call = _make_llm_logger(db, agent_id=str(agent.id)) runtime = AgentRuntime(config=config, on_llm_call=on_llm_call) result = await runtime.run(text) if result.content: _reply_card(open_id, f"{agent.name}", result.content.strip(), status="success") else: _reply_to_feishu(open_id, "Agent 未返回有效回复，请重试。") logger.info( "灵犀 Agent 回复完成: open_id=%s agent=%s iterations=%d tools=%d", open_id[:20], agent.name, result.iterations_used, result.tool_calls_made, ) except Exception as e: logger.error("灵犀消息处理失败: %s", e) try: _reply_to_feishu(open_id, f"处理失败: {e!s}") except Exception: pass finally: if db: db.close() def _handle_message_internal(data): msg_id = _get_message_id(data) if msg_id: if msg_id in _processed_msg_ids: return _processed_msg_ids.append(msg_id) open_id = _get_sender_open_id(data) chat_type = _get_chat_type(data) text = _get_message_text(data) if not open_id or chat_type != "p2p" or not text: return try: loop = asyncio.get_event_loop() if loop.is_running(): asyncio.ensure_future(_handle_message_async(data)) else: loop.run_until_complete(_handle_message_async(data)) except Exception as e: logger.error("灵犀创建消息处理任务失败: %s", e) try: _reply_to_feishu(open_id, f"处理失败: {e!s}") except Exception: pass def _build_event_handler(): from lark_oapi.event.dispatcher_handler import EventDispatcherHandler def on_message_receive(data): _handle_message_internal(data) builder = EventDispatcherHandler.builder(encrypt_key="", verification_token="") builder.register_p2_im_message_receive_v1(on_message_receive) return builder.build() async def start_ws_client(): if not settings.LINGXI_APP_ID or not settings.LINGXI_APP_SECRET: logger.warning("灵犀应用未配置，跳过灵犀长连接启动") return from lark_oapi.ws import Client as WSClient handler = _build_event_handler() client = WSClient( app_id=settings.LINGXI_APP_ID, app_secret=settings.LINGXI_APP_SECRET, event_handler=handler, auto_reconnect=True, ) logger.info("灵犀长连接客户端启动中...") while True: try: await client._connect() logger.info("灵犀长连接已建立") asyncio.ensure_future(client._ping_loop()) while True: await asyncio.sleep(3600) except asyncio.CancelledError: break except Exception as e: logger.warning("灵犀长连接断开，3秒后重连: %s", e) await asyncio.sleep(3)