124 lines
5.2 KiB
Python
124 lines
5.2 KiB
Python
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# -*- coding: utf-8 -*-
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"""
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飞书机器人蓝图
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处理来自飞书机器人的事件回调
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"""
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import logging
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import json
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import threading
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from flask import Blueprint, request, jsonify
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from src.integrations.feishu_service import FeishuService
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from src.web.service_manager import service_manager
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# 初始化日志
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logger = logging.getLogger(__name__)
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# 创建蓝图
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feishu_bot_bp = Blueprint('feishu_bot', __name__, url_prefix='/api/feishu/bot')
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# 在模块级别实例化飞书服务，以便复用
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# 注意：这假设配置在启动时是固定的。如果配置可热更新，则需要调整。
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feishu_service = FeishuService()
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def _process_message_in_background(app_context, event_data: dict):
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"""
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在后台线程中处理消息，避免阻塞飞书的回调请求。
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"""
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with app_context:
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try:
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# 1. 解析事件数据
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message_id = event_data['event']['message']['message_id']
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chat_id = event_data['event']['message']['chat_id']
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# 内容是一个JSON字符串，需要再次解析
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content_json = json.loads(event_data['event']['message']['content'])
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text_content = content_json.get('text', '').strip()
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logger.info(f"[Feishu Bot] 后台开始处理消息ID: {message_id}, 内容: '{text_content}'")
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# 2. 移除@机器人的部分
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# 飞书的@消息格式通常是 "@机器人名 实际内容"
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if event_data['event']['message'].get('mentions'):
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for mention in event_data['event']['message']['mentions']:
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# mention['key']是@内容，例如"@_user_1"
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# mention['name']是显示的名字
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bot_mention_text = f"@{mention['name']}"
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if text_content.startswith(bot_mention_text):
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text_content = text_content[len(bot_mention_text):].strip()
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break
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if not text_content:
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logger.warning(f"[Feishu Bot] 移除@后内容为空，不处理。消息ID: {message_id}")
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return
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logger.info(f"[Feishu Bot] 清理后的消息内容: '{text_content}'")
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# 3. 调用核心服务获取回复
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assistant = service_manager.get_assistant()
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# 注意：process_message_agent 是一个异步方法，需要处理
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# 在同步线程中运行异步方法
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import asyncio
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try:
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loop = asyncio.get_running_loop()
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except RuntimeError: # 'RuntimeError: There is no current event loop...'
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loop = asyncio.new_event_loop()
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asyncio.set_event_loop(loop)
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# 调用对话服务
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logger.info(f"[Feishu Bot] 调用Agent服务处理消息...")
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response_data = loop.run_until_complete(
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assistant.process_message_agent(message=text_content, user_id=f"feishu_{chat_id}")
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)
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logger.info(f"[Feishu Bot] Agent服务返回结果: {response_data}")
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# 4. 提取回复并发送
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reply_text = response_data.get("message", "抱歉，我暂时无法回答这个问题。")
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if isinstance(reply_text, dict): # 有时候返回的可能是字典
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reply_text = reply_text.get('content', str(reply_text))
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logger.info(f"[Feishu Bot] 准备发送回复到飞书: '{reply_text}'")
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success = feishu_service.reply_to_message(message_id, reply_text)
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if success:
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logger.info(f"[Feishu Bot] 成功回复消息到飞书。消息ID: {message_id}")
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else:
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logger.error(f"[Feishu Bot] 回复消息到飞书失败。消息ID: {message_id}")
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except Exception as e:
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logger.error(f"[Feishu Bot] 后台处理消息时发生严重错误: {e}", exc_info=True)
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@feishu_bot_bp.route('/event', methods=['POST'])
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def handle_feishu_event():
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"""
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接收并处理飞书事件回调
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"""
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# 1. 解析请求
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data = request.json
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logger.info(f"[Feishu Bot] 收到飞书事件回调:\n{json.dumps(data, indent=2)}")
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# 2. 安全校验 (如果配置了)
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# 此处可以添加Verification Token的校验逻辑
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# headers = request.headers
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# ...
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# 3. 处理URL验证挑战
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if data and data.get("type") == "url_verification":
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challenge = data.get("challenge", "")
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logger.info(f"[Feishu Bot] 收到URL验证请求，返回challenge: {challenge}")
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return jsonify({"challenge": challenge})
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# 4. 处理事件回调
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if data and data.get("header", {}).get("event_type") == "im.message.receive_v1":
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# 立即响应飞书，防止超时重试
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threading.Thread(
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target=_process_message_in_background,
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args=(request.environ['werkzeug.request'].environ['flask.app'].app_context(), data)
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).start()
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logger.info("[Feishu Bot] 已将消息处理任务推送到后台线程，并立即响应200 OK")
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return jsonify({"status": "processing"})
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# 5. 对于其他未知事件，也返回成功，避免飞书重试
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logger.warning(f"[Feishu Bot] 收到未知类型的事件: {data.get('header', {}).get('event_type')}")
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return jsonify({"status": "ignored"})
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