aiagent/backend/app/services/feishu_ws_handler.py

"""飞书长连接事件监听 — 通过 lark-oapi SDK 建立 WebSocket 接收事件"""
from __future__ import annotations

import asyncio
import json
import logging
import threading
from collections import deque
from typing import List, Optional

from app.core.config import settings

logger = logging.getLogger(__name__)

# 存储通过事件捕获的 open_id（与 HTTP 事件回调共用）
_pending_open_ids: List[str] = []

# 已处理消息 ID 去重（防止 WS 重连导致重复处理）
_processed_msg_ids: deque[str] = deque(maxlen=20)

_ws_thread: threading.Thread | None = None


def _get_message_id(data) -> Optional[str]:
    """从 Feishu 消息事件中提取 message_id。"""
    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]:
    """从 Feishu 消息事件中提取纯文本内容。"""
    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", "")
        # 其他消息类型暂不支持
        return None
    except Exception as e:
        logger.warning("解析飞书消息内容失败: %s", e)
        return None


def _get_sender_open_id(data) -> Optional[str]:
    """从 Feishu 消息事件中提取发送者 open_id。"""
    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_sender_union_id(data) -> Optional[str]:
    """从 Feishu 消息事件中提取发送者 union_id（跨应用唯一）。"""
    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, "union_id", None)
    except Exception:
        return None


def _get_chat_type(data) -> str:
    """获取聊天类型。"""
    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):
    """通过飞书 API 回复用户消息。"""
    try:
        from app.services.feishu_app_service import send_plain_text

        send_plain_text(open_id, text)
    except Exception as e:
        logger.warning("飞书回复消息失败: %s", e)


def _reply_card(open_id: str, title: str, content: str, status: str = "info"):
    """通过飞书 API 回复卡片消息。"""
    try:
        from app.services.feishu_app_service import send_message_to_user

        send_message_to_user(open_id, title, content, status=status)
    except Exception as e:
        logger.warning("飞书回复卡片失败: %s", e)


async def _handle_message_async(data):
    """异步处理飞书消息。"""
    open_id = _get_sender_open_id(data)
    union_id = _get_sender_union_id(data)
    chat_type = _get_chat_type(data)
    text = _get_message_text(data)

    if not open_id or chat_type != "p2p":
        return

    _pending_open_ids.append(open_id)
    if len(_pending_open_ids) > 5:
        _pending_open_ids.pop(0)

    logger.info("飞书收到消息: open_id=%s text=%s", open_id[:20], text[:50] if text else "(空)")

    try:
        with open("/tmp/feishu_open_id.txt", "w") as f:
            f.write(open_id)
    except Exception:
        pass

    if not text:
        return

    from sqlalchemy.orm import Session
    from app.core.database import SessionLocal
    from app.models.user import User
    from app.models.agent import Agent
    from app.services.feishu_open_id_service import resolve_user_and_save

    db: Optional[Session] = None
    try:
        db = SessionLocal()

        # 自动保存/关联此应用的 open_id（跨应用识别）
        resolved_uid = resolve_user_and_save(
            db, app_id=settings.FEISHU_APP_ID or "",
            open_id=open_id, union_id=union_id,
        )

        user = db.query(User).filter(User.feishu_open_id == open_id).first()
        if not user and resolved_uid:
            user = db.query(User).filter(User.id == resolved_uid).first()
        if not user:
            _reply_to_feishu(open_id, "你的账号未绑定平台用户，请先在平台绑定飞书。")
            return

        agent_id = user.feishu_default_agent_id
        if not agent_id:
            _reply_to_feishu(
                open_id,
                "你还没有设置飞书对话的默认 Agent。\n请先在平台设置：\n"
                "POST /api/v1/feishu/default-agent  {\"agent_id\": \"<你的AgentID>\"}",
            )
            return

        agent = db.query(Agent).filter(Agent.id == agent_id).first()
        if not agent:
            _reply_to_feishu(open_id, f"默认 Agent (id={agent_id}) 已不存在，请重新设置。")
            return

        _reply_to_feishu(open_id, f"🤔 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 = 0.7
        max_iterations = 10

        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))
            break

        config = AgentConfig(
            name=agent.name or "agent",
            system_prompt=system_prompt + (
                f"\n\n## 系统信息\n"
                f"你的 Agent ID 是: {agent.id}\n"
                f"在调用 schedule_list、schedule_delete 等工具时，使用此 ID 作为 agent_id 参数。"
            ),
            llm=AgentLLMConfig(
                model=model,
                provider=provider,
                temperature=temperature,
                max_iterations=max_iterations,
            ),
            tools=AgentToolConfig(),
            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=user.id,
            memory_scope_id=str(agent.id),
        )

        on_llm_call = _make_llm_logger(db, agent_id=str(agent.id), user_id=user.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(
            "飞书 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("飞书消息处理失败: %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):
    """同步入口 — 创建异步任务处理飞书消息。"""
    # 去重：WS 重连后可能重投已处理的消息
    msg_id = _get_message_id(data)
    if msg_id:
        if msg_id in _processed_msg_ids:
            logger.debug("跳过已处理消息: %s", msg_id)
            return
        _processed_msg_ids.append(msg_id)

    # 记录 pending open_id（用于绑定）
    open_id = _get_sender_open_id(data)
    chat_type = _get_chat_type(data)
    text = _get_message_text(data)

    if open_id:
        _pending_open_ids.append(open_id)
        if len(_pending_open_ids) > 5:
            _pending_open_ids.pop(0)
        try:
            with open("/tmp/feishu_open_id.txt", "w") as f:
                f.write(open_id)
        except Exception:
            pass

    if not open_id or chat_type != "p2p":
        return

    logger.info("飞书收到消息: open_id=%s text=%s", open_id[:20], text[:50] if text else "(空)")

    if not text:
        return

    # 将实际处理委托给异步函数
    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("创建飞书消息处理任务失败: %s", e)
        try:
            _reply_to_feishu(open_id, f"处理失败: {e!s}")
        except Exception:
            pass


def _make_llm_logger(db, agent_id: Optional[str] = None, user_id: Optional[str] = None):
    """创建 LLM 调用日志回调。"""
    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


def _build_event_handler():
    """构建事件处理器。"""
    from lark_oapi.event.dispatcher_handler import EventDispatcherHandler

    def on_message_receive(data):
        """处理 im.message.receive_v1 事件。"""
        _handle_message_internal(data)

    builder = EventDispatcherHandler.builder(
        encrypt_key="",
        verification_token=settings.FEISHU_VERIFICATION_TOKEN,
    )
    builder.register_p2_im_message_receive_v1(on_message_receive)
    return builder.build()


async def start_ws_client():
    """在 async 上下文中启动飞书长连接（在主事件循环运行）。"""
    if not settings.FEISHU_APP_ID or not settings.FEISHU_APP_SECRET:
        logger.warning("飞书应用未配置，跳过长连接启动")
        return

    from lark_oapi.ws import Client as WSClient

    handler = _build_event_handler()
    client = WSClient(
        app_id=settings.FEISHU_APP_ID,
        app_secret=settings.FEISHU_APP_SECRET,
        event_handler=handler,
        auto_reconnect=True,
    )

    logger.info("飞书长连接客户端启动中...")

    while True:
        try:
            await client._connect()
            logger.info("飞书长连接已建立")
            asyncio.ensure_future(client._ping_loop())
            while True:
                await asyncio.sleep(3600)
        except asyncio.CancelledError:
            break
        except Exception as e:
            logger.warning("飞书长连接断开，3秒后重连: %s", e)
            await asyncio.sleep(3)


def get_pending_open_ids() -> List[str]:
    """获取待绑定的 open_id 列表。"""
    return list(_pending_open_ids)


def clear_pending_open_ids():
    """清空待绑定的 open_id。"""
    _pending_open_ids.clear()