1c83b6284f
- Add 灵犀学习助手 Feishu bot (lingxi_app_service + lingxi_ws_handler) - Fix agent_schedule_service missing AgentSchedule import (Celery Beat) - Fix scene_templates default enable_tools=False → True - Fix workflow_engine LLM node: empty tools list now = all tools (consistent with agent node) - Add 创建agent.md guide document Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
279 lines
9.1 KiB
Python
279 lines
9.1 KiB
Python
"""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）"""
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from __future__ import annotations
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import asyncio
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import json
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import logging
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from collections import deque
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from typing import Optional
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from app.core.config import settings
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logger = logging.getLogger(__name__)
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_processed_msg_ids: deque[str] = deque(maxlen=20)
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def _get_message_id(data) -> Optional[str]:
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try:
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ev = data.event
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msg = getattr(ev, "message", None)
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if msg:
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return getattr(msg, "message_id", None)
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except Exception:
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return None
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return None
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def _get_message_text(data) -> Optional[str]:
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try:
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ev = data.event
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msg = getattr(ev, "message", None)
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if not msg:
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return None
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content_str = getattr(msg, "content", None)
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msg_type = getattr(msg, "message_type", "")
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if not content_str:
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return None
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if msg_type == "text":
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parsed = json.loads(content_str)
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return parsed.get("text", "")
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return None
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except Exception as e:
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logger.warning("解析灵犀消息内容失败: %s", e)
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return None
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def _get_sender_open_id(data) -> Optional[str]:
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try:
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ev = data.event
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sender = getattr(ev, "sender", None)
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if not sender:
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return None
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sender_id = getattr(sender, "sender_id", None)
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if not sender_id:
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return None
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return getattr(sender_id, "open_id", None)
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except Exception:
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return None
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def _get_chat_type(data) -> str:
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try:
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ev = data.event
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msg = getattr(ev, "message", None)
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return getattr(msg, "chat_type", "") if msg else ""
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except Exception:
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return ""
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def _reply_to_feishu(open_id: str, text: str):
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try:
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from app.services.lingxi_app_service import send_plain_text
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send_plain_text(open_id, text)
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except Exception as e:
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logger.warning("灵犀回复消息失败: %s", e)
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def _reply_card(open_id: str, title: str, content: str, status: str = "info"):
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try:
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from app.services.lingxi_app_service import send_message_to_user
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send_message_to_user(open_id, title, content, status=status)
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except Exception as e:
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logger.warning("灵犀回复卡片失败: %s", e)
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def _make_llm_logger(db, agent_id: Optional[str] = None, user_id: Optional[str] = None):
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def _log(metrics: dict):
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try:
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from app.models.agent_llm_log import AgentLLMLog
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log = AgentLLMLog(
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agent_id=agent_id, session_id=metrics.get("session_id"),
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user_id=user_id, model=metrics.get("model", ""),
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provider=metrics.get("provider"),
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prompt_tokens=metrics.get("prompt_tokens", 0),
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completion_tokens=metrics.get("completion_tokens", 0),
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total_tokens=metrics.get("total_tokens", 0),
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latency_ms=metrics.get("latency_ms", 0),
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iteration_number=metrics.get("iteration_number", 0),
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step_type=metrics.get("step_type"),
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tool_name=metrics.get("tool_name"),
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status=metrics.get("status", "success"),
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error_message=metrics.get("error_message"),
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)
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db.add(log)
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db.commit()
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except Exception as e:
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logger.warning("写入 AgentLLMLog 失败: %s", e)
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return _log
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async def _handle_message_async(data):
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open_id = _get_sender_open_id(data)
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chat_type = _get_chat_type(data)
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text = _get_message_text(data)
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if not open_id or chat_type != "p2p":
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return
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logger.info("灵犀收到消息: open_id=%s text=%s", open_id[:20], text[:50] if text else "(空)")
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if not text:
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return
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from sqlalchemy.orm import Session
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from app.core.database import SessionLocal
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from app.models.agent import Agent
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db: Optional[Session] = None
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try:
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db = SessionLocal()
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agent_id = settings.LINGXI_AGENT_ID
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if not agent_id:
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_reply_to_feishu(open_id, "灵犀尚未配置，请联系管理员。")
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return
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agent = db.query(Agent).filter(Agent.id == agent_id).first()
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if not agent:
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_reply_to_feishu(open_id, "灵犀 Agent 已不存在，请联系管理员。")
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return
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_reply_to_feishu(open_id, "正在思考，请稍候...")
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from app.agent_runtime import AgentRuntime, AgentConfig, AgentLLMConfig, AgentToolConfig, AgentMemoryConfig
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wc = agent.workflow_config or {}
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nodes = wc.get("nodes", [])
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system_prompt = agent.description or ""
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model = "deepseek-v4-flash"
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provider = "deepseek"
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temperature = 0.85
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max_iterations = 30
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tools_whitelist = []
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for n in nodes:
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if n.get("type") not in ("agent", "llm", "template"):
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continue
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cfg = n.get("data", {}) if isinstance(n, dict) else getattr(n, "data", {})
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system_prompt = cfg.get("system_prompt", "") or system_prompt
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model = cfg.get("model", model)
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provider = cfg.get("provider", provider)
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temperature = float(cfg.get("temperature", temperature))
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max_iterations = int(cfg.get("max_iterations", max_iterations))
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tools_whitelist = cfg.get("tools", tools_whitelist)
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break
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config = AgentConfig(
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name=agent.name or "灵犀",
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system_prompt=system_prompt,
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llm=AgentLLMConfig(
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model=model, provider=provider,
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temperature=temperature, max_iterations=max_iterations,
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),
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tools=AgentToolConfig(include_tools=tools_whitelist),
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memory=AgentMemoryConfig(
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max_history_messages=int(cfg.get("memory_max_history", 20)),
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vector_memory_top_k=int(cfg.get("memory_vector_top_k", 5)),
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persist_to_db=bool(cfg.get("memory_persist", True)),
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vector_memory_enabled=bool(cfg.get("memory_vector_enabled", True)),
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learning_enabled=bool(cfg.get("memory_learning", True)),
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),
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user_id=None,
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memory_scope_id=str(agent.id),
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)
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on_llm_call = _make_llm_logger(db, agent_id=str(agent.id))
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runtime = AgentRuntime(config=config, on_llm_call=on_llm_call)
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result = await runtime.run(text)
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if result.content:
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_reply_card(open_id, f"{agent.name}", result.content.strip(), status="success")
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else:
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_reply_to_feishu(open_id, "Agent 未返回有效回复，请重试。")
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logger.info(
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"灵犀 Agent 回复完成: open_id=%s agent=%s iterations=%d tools=%d",
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open_id[:20], agent.name, result.iterations_used, result.tool_calls_made,
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)
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except Exception as e:
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logger.error("灵犀消息处理失败: %s", e)
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try:
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_reply_to_feishu(open_id, f"处理失败: {e!s}")
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except Exception:
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pass
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finally:
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if db:
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db.close()
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def _handle_message_internal(data):
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msg_id = _get_message_id(data)
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if msg_id:
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if msg_id in _processed_msg_ids:
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return
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_processed_msg_ids.append(msg_id)
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open_id = _get_sender_open_id(data)
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chat_type = _get_chat_type(data)
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text = _get_message_text(data)
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if not open_id or chat_type != "p2p" or not text:
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return
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try:
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loop = asyncio.get_event_loop()
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if loop.is_running():
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asyncio.ensure_future(_handle_message_async(data))
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else:
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loop.run_until_complete(_handle_message_async(data))
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except Exception as e:
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logger.error("灵犀创建消息处理任务失败: %s", e)
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try:
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_reply_to_feishu(open_id, f"处理失败: {e!s}")
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except Exception:
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pass
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def _build_event_handler():
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from lark_oapi.event.dispatcher_handler import EventDispatcherHandler
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def on_message_receive(data):
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_handle_message_internal(data)
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builder = EventDispatcherHandler.builder(encrypt_key="", verification_token="")
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builder.register_p2_im_message_receive_v1(on_message_receive)
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return builder.build()
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async def start_ws_client():
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if not settings.LINGXI_APP_ID or not settings.LINGXI_APP_SECRET:
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logger.warning("灵犀应用未配置，跳过灵犀长连接启动")
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return
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from lark_oapi.ws import Client as WSClient
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handler = _build_event_handler()
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client = WSClient(
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app_id=settings.LINGXI_APP_ID,
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app_secret=settings.LINGXI_APP_SECRET,
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event_handler=handler,
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auto_reconnect=True,
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)
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logger.info("灵犀长连接客户端启动中...")
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while True:
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try:
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await client._connect()
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logger.info("灵犀长连接已建立")
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asyncio.ensure_future(client._ping_loop())
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while True:
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await asyncio.sleep(3600)
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except asyncio.CancelledError:
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break
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except Exception as e:
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logger.warning("灵犀长连接断开，3秒后重连: %s", e)
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await asyncio.sleep(3)
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