452 lines
18 KiB
Python
452 lines
18 KiB
Python
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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Screen2Feishu Web应用
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结合前端页面与后端功能
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"""
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import os
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import sys
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import json
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import time
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import base64
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import logging
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from pathlib import Path
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from datetime import datetime
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from typing import Dict, Optional, List
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# 添加项目根目录到Python路径
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project_root = Path(__file__).parent
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sys.path.insert(0, str(project_root))
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from flask import Flask, render_template, request, jsonify, send_from_directory
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from flask_cors import CORS
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from werkzeug.utils import secure_filename
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from services.ai_service import AIService
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from services.feishu_service import FeishuService
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from utils.config_loader import load_config, validate_config
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from utils.user_cache import UserCacheManager
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from utils.logger import setup_logger
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# 初始化Flask应用
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app = Flask(__name__,
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static_folder='static',
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template_folder='templates')
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CORS(app)
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# 配置上传文件大小限制
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app.config['MAX_CONTENT_LENGTH'] = 16 * 1024 * 1024 # 16MB
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# 全局变量
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config = None
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ai_service = None
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feishu_service = None
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user_cache = None
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logger = None
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def init_app():
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"""初始化应用"""
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global config, ai_service, feishu_service, user_cache, logger
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# 加载配置
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try:
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config = load_config("config.yaml")
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validate_config(config)
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logger = setup_logger(config['system']['log_level'], config['system']['log_file'])
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logger.info("配置加载成功")
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except Exception as e:
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print(f"配置加载失败: {str(e)}")
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sys.exit(1)
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# 初始化服务
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try:
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ai_service = AIService(config['ai'])
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feishu_service = FeishuService(config['feishu'])
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# 初始化用户缓存
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cache_file = config['system']['user_matching']['cache_file']
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user_cache = UserCacheManager(cache_file)
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logger.info("服务初始化成功")
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except Exception as e:
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logger.error(f"服务初始化失败: {str(e)}")
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sys.exit(1)
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# 创建必要的目录
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Path("monitor_images").mkdir(exist_ok=True)
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Path("processed_images").mkdir(exist_ok=True)
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Path("data").mkdir(exist_ok=True)
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# 路由定义
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@app.route('/')
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def index():
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"""首页 - 返回前端HTML页面"""
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return render_template('index.html')
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@app.route('/api/upload', methods=['POST'])
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def upload_image():
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"""上传图片并分析"""
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try:
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if 'image' not in request.files:
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return jsonify({'success': False, 'error': '没有上传文件'}), 400
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file = request.files['image']
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if file.filename == '':
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return jsonify({'success': False, 'error': '没有选择文件'}), 400
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if not file.content_type.startswith('image/'):
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return jsonify({'success': False, 'error': '文件不是图片'}), 400
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# 保存图片到monitor_images目录
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filename = secure_filename(file.filename)
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timestamp = int(time.time())
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filename = f"screenshot-{timestamp}-{filename}"
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filepath = Path("monitor_images") / filename
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file.save(filepath)
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logger.info(f"上传图片: {filename}")
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# 检查是否启用内存处理
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memory_processing = config['system'].get('memory_processing', False)
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if memory_processing:
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# 内存处理模式
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with open(filepath, 'rb') as f:
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image_bytes = f.read()
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# AI分析图片
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ai_result = ai_service.analyze_image_from_bytes(image_bytes, filename)
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if not ai_result:
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return jsonify({'success': False, 'error': 'AI分析失败'}), 500
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else:
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# 文件处理模式
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ai_result = ai_service.analyze_image(str(filepath))
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if not ai_result:
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return jsonify({'success': False, 'error': 'AI分析失败'}), 500
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# 处理任务发起方
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initiator_name = ai_result.get("initiator", "")
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if initiator_name and config['system']['user_matching']['enabled']:
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# 尝试匹配用户
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user_match = _match_initiator(initiator_name)
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if user_match:
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if user_match.get('matched'):
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# 成功匹配到用户ID
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ai_result["任务发起方"] = {"id": user_match['user_id']}
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logger.info(f"成功匹配任务发起方: {initiator_name} -> {user_match['user_name']}")
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else:
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# 未匹配到用户，添加待确认标记
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ai_result["task_description"] = f"[待确认发起人] {ai_result['task_description']}"
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ai_result["任务发起方.部门"] = f"待确认: {initiator_name}"
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logger.warning(f"未匹配到用户: {initiator_name}，标记为待确认")
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# 添加到最近联系人
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if user_cache:
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user_cache.add_recent_contact(initiator_name)
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else:
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# 匹配失败，使用随机选择或留空
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if config['system']['user_matching']['fallback_to_random'] and user_cache:
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random_contact = user_cache.get_random_recent_contact()
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if random_contact:
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ai_result["task_description"] = f"[随机匹配] {ai_result['task_description']}"
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ai_result["任务发起方.部门"] = f"随机: {random_contact}"
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logger.info(f"随机匹配任务发起方: {random_contact}")
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else:
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ai_result["task_description"] = f"[待确认发起人] {ai_result['task_description']}"
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logger.warning(f"无最近联系人可用，标记为待确认: {initiator_name}")
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else:
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ai_result["task_description"] = f"[待确认发起人] {ai_result['task_description']}"
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logger.warning(f"未匹配到用户且未启用随机匹配: {initiator_name}")
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# 处理部门信息
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if "department" in ai_result and ai_result["department"]:
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if "任务发起方.部门" not in ai_result:
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ai_result["任务发起方.部门"] = ai_result["department"]
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# 写入飞书
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success = feishu_service.add_task(ai_result)
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if success:
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# 后处理文件
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post_process = config['system'].get('post_process', 'keep')
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if post_process == 'delete':
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filepath.unlink()
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logger.info(f"已删除文件: {filename}")
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elif post_process == 'move':
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processed_folder = Path(config['system']['processed_folder'])
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processed_folder.mkdir(exist_ok=True)
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target_path = processed_folder / filename
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filepath.rename(target_path)
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logger.info(f"已移动文件到: {target_path}")
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return jsonify({
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'success': True,
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'message': '任务已成功添加到飞书',
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'ai_result': ai_result
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})
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else:
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return jsonify({'success': False, 'error': '写入飞书失败'}), 500
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except Exception as e:
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logger.error(f"处理图片失败: {str(e)}")
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return jsonify({'success': False, 'error': str(e)}), 500
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@app.route('/api/tasks', methods=['GET'])
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def get_tasks():
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"""获取任务列表"""
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try:
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# 这里可以添加从飞书获取任务列表的逻辑
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# 暂时返回空列表
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return jsonify({'success': True, 'tasks': []})
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except Exception as e:
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logger.error(f"获取任务列表失败: {str(e)}")
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return jsonify({'success': False, 'error': str(e)}), 500
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@app.route('/api/user_cache', methods=['GET'])
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def get_user_cache():
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"""获取用户缓存信息"""
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try:
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if not user_cache:
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return jsonify({'success': False, 'error': '用户缓存未初始化'}), 500
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stats = user_cache.get_cache_stats()
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return jsonify({'success': True, 'stats': stats})
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except Exception as e:
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logger.error(f"获取用户缓存信息失败: {str(e)}")
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return jsonify({'success': False, 'error': str(e)}), 500
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@app.route('/api/config', methods=['GET'])
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def get_config():
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"""获取配置信息"""
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try:
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config_info = {
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'memory_processing': config['system'].get('memory_processing', False),
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'user_matching_enabled': config['system']['user_matching']['enabled'],
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'fallback_to_random': config['system']['user_matching']['fallback_to_random'],
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'cache_enabled': config['system']['user_matching']['cache_enabled'],
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'post_process': config['system'].get('post_process', 'keep')
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}
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return jsonify({'success': True, 'config': config_info})
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except Exception as e:
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logger.error(f"获取配置信息失败: {str(e)}")
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return jsonify({'success': False, 'error': str(e)}), 500
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def _match_initiator(initiator_name: str) -> Optional[Dict]:
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"""匹配任务发起人"""
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if not initiator_name or not config['system']['user_matching']['enabled']:
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return None
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# 确保用户缓存已初始化
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if not user_cache:
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return None
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# 检查缓存是否过期，如果过期则重新获取用户列表
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if user_cache.is_cache_expired(max_age_hours=24):
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logger.info("用户缓存已过期，重新获取用户列表")
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users = feishu_service._get_user_list()
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if users:
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user_cache.update_users(users)
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# 尝试匹配用户
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matched_user = user_cache.match_user_by_name(initiator_name)
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if matched_user:
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return {
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'matched': True,
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'user_id': matched_user.get('user_id'),
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'user_name': matched_user.get('name')
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}
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else:
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return {
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'matched': False,
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'user_name': initiator_name
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}
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@app.route('/api/screenshot', methods=['POST'])
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def capture_screenshot():
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"""截图上传接口"""
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try:
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if 'screenshot' not in request.files:
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return jsonify({'success': False, 'error': '没有上传文件'}), 400
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file = request.files['screenshot']
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if file.filename == '':
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return jsonify({'success': False, 'error': '没有选择文件'}), 400
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# 保存截图
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filename = secure_filename(file.filename)
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timestamp = int(time.time())
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filename = f"screenshot-{timestamp}-{filename}"
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filepath = Path("monitor_images") / filename
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file.save(filepath)
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logger.info(f"接收截图: {filename}")
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# 调用分析接口
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with open(filepath, 'rb') as f:
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image_bytes = f.read()
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# AI分析图片
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ai_result = ai_service.analyze_image_from_bytes(image_bytes, filename)
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if not ai_result:
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return jsonify({'success': False, 'error': 'AI分析失败'}), 500
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# 处理任务发起方
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initiator_name = ai_result.get("initiator", "")
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if initiator_name and config['system']['user_matching']['enabled']:
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user_match = _match_initiator(initiator_name)
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if user_match:
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if user_match.get('matched'):
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ai_result["任务发起方"] = {"id": user_match['user_id']}
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logger.info(f"成功匹配任务发起方: {initiator_name} -> {user_match['user_name']}")
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else:
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ai_result["task_description"] = f"[待确认发起人] {ai_result['task_description']}"
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ai_result["任务发起方.部门"] = f"待确认: {initiator_name}"
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logger.warning(f"未匹配到用户: {initiator_name}，标记为待确认")
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if user_cache:
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user_cache.add_recent_contact(initiator_name)
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else:
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if config['system']['user_matching']['fallback_to_random'] and user_cache:
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random_contact = user_cache.get_random_recent_contact()
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if random_contact:
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ai_result["task_description"] = f"[随机匹配] {ai_result['task_description']}"
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ai_result["任务发起方.部门"] = f"随机: {random_contact}"
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logger.info(f"随机匹配任务发起方: {random_contact}")
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else:
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ai_result["task_description"] = f"[待确认发起人] {ai_result['task_description']}"
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logger.warning(f"无最近联系人可用，标记为待确认: {initiator_name}")
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else:
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ai_result["task_description"] = f"[待确认发起人] {ai_result['task_description']}"
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logger.warning(f"未匹配到用户且未启用随机匹配: {initiator_name}")
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# 处理部门信息
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if "department" in ai_result and ai_result["department"]:
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if "任务发起方.部门" not in ai_result:
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ai_result["任务发起方.部门"] = ai_result["department"]
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# 写入飞书
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success = feishu_service.add_task(ai_result)
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if success:
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# 后处理文件
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post_process = config['system'].get('post_process', 'keep')
|
||
|
|
if post_process == 'delete':
|
||
|
|
filepath.unlink()
|
||
|
|
logger.info(f"已删除文件: {filename}")
|
||
|
|
elif post_process == 'move':
|
||
|
|
processed_folder = Path(config['system']['processed_folder'])
|
||
|
|
processed_folder.mkdir(exist_ok=True)
|
||
|
|
target_path = processed_folder / filename
|
||
|
|
filepath.rename(target_path)
|
||
|
|
logger.info(f"已移动文件到: {target_path}")
|
||
|
|
|
||
|
|
return jsonify({
|
||
|
|
'success': True,
|
||
|
|
'message': '任务已成功添加到飞书',
|
||
|
|
'ai_result': ai_result
|
||
|
|
})
|
||
|
|
else:
|
||
|
|
return jsonify({'success': False, 'error': '写入飞书失败'}), 500
|
||
|
|
|
||
|
|
except Exception as e:
|
||
|
|
logger.error(f"处理截图失败: {str(e)}")
|
||
|
|
return jsonify({'success': False, 'error': str(e)}), 500
|
||
|
|
|
||
|
|
@app.route('/api/monitor', methods=['POST'])
|
||
|
|
def monitor_upload():
|
||
|
|
"""监控文件夹上传接口"""
|
||
|
|
try:
|
||
|
|
if 'file' not in request.files:
|
||
|
|
return jsonify({'success': False, 'error': '没有上传文件'}), 400
|
||
|
|
|
||
|
|
file = request.files['file']
|
||
|
|
if file.filename == '':
|
||
|
|
return jsonify({'success': False, 'error': '没有选择文件'}), 400
|
||
|
|
|
||
|
|
# 保存文件到monitor_images
|
||
|
|
filename = secure_filename(file.filename)
|
||
|
|
filepath = Path("monitor_images") / filename
|
||
|
|
|
||
|
|
file.save(filepath)
|
||
|
|
logger.info(f"接收监控文件: {filename}")
|
||
|
|
|
||
|
|
# 调用分析接口
|
||
|
|
with open(filepath, 'rb') as f:
|
||
|
|
image_bytes = f.read()
|
||
|
|
|
||
|
|
# AI分析图片
|
||
|
|
ai_result = ai_service.analyze_image_from_bytes(image_bytes, filename)
|
||
|
|
if not ai_result:
|
||
|
|
return jsonify({'success': False, 'error': 'AI分析失败'}), 500
|
||
|
|
|
||
|
|
# 处理任务发起方
|
||
|
|
initiator_name = ai_result.get("initiator", "")
|
||
|
|
if initiator_name and config['system']['user_matching']['enabled']:
|
||
|
|
user_match = _match_initiator(initiator_name)
|
||
|
|
if user_match:
|
||
|
|
if user_match.get('matched'):
|
||
|
|
ai_result["任务发起方"] = {"id": user_match['user_id']}
|
||
|
|
logger.info(f"成功匹配任务发起方: {initiator_name} -> {user_match['user_name']}")
|
||
|
|
else:
|
||
|
|
ai_result["task_description"] = f"[待确认发起人] {ai_result['task_description']}"
|
||
|
|
ai_result["任务发起方.部门"] = f"待确认: {initiator_name}"
|
||
|
|
logger.warning(f"未匹配到用户: {initiator_name}，标记为待确认")
|
||
|
|
|
||
|
|
if user_cache:
|
||
|
|
user_cache.add_recent_contact(initiator_name)
|
||
|
|
else:
|
||
|
|
if config['system']['user_matching']['fallback_to_random'] and user_cache:
|
||
|
|
random_contact = user_cache.get_random_recent_contact()
|
||
|
|
if random_contact:
|
||
|
|
ai_result["task_description"] = f"[随机匹配] {ai_result['task_description']}"
|
||
|
|
ai_result["任务发起方.部门"] = f"随机: {random_contact}"
|
||
|
|
logger.info(f"随机匹配任务发起方: {random_contact}")
|
||
|
|
else:
|
||
|
|
ai_result["task_description"] = f"[待确认发起人] {ai_result['task_description']}"
|
||
|
|
logger.warning(f"无最近联系人可用，标记为待确认: {initiator_name}")
|
||
|
|
else:
|
||
|
|
ai_result["task_description"] = f"[待确认发起人] {ai_result['task_description']}"
|
||
|
|
logger.warning(f"未匹配到用户且未启用随机匹配: {initiator_name}")
|
||
|
|
|
||
|
|
# 处理部门信息
|
||
|
|
if "department" in ai_result and ai_result["department"]:
|
||
|
|
if "任务发起方.部门" not in ai_result:
|
||
|
|
ai_result["任务发起方.部门"] = ai_result["department"]
|
||
|
|
|
||
|
|
# 写入飞书
|
||
|
|
success = feishu_service.add_task(ai_result)
|
||
|
|
|
||
|
|
if success:
|
||
|
|
# 后处理文件
|
||
|
|
post_process = config['system'].get('post_process', 'keep')
|
||
|
|
if post_process == 'delete':
|
||
|
|
filepath.unlink()
|
||
|
|
logger.info(f"已删除文件: {filename}")
|
||
|
|
elif post_process == 'move':
|
||
|
|
processed_folder = Path(config['system']['processed_folder'])
|
||
|
|
processed_folder.mkdir(exist_ok=True)
|
||
|
|
target_path = processed_folder / filename
|
||
|
|
filepath.rename(target_path)
|
||
|
|
logger.info(f"已移动文件到: {target_path}")
|
||
|
|
|
||
|
|
return jsonify({
|
||
|
|
'success': True,
|
||
|
|
'message': '任务已成功添加到飞书',
|
||
|
|
'ai_result': ai_result
|
||
|
|
})
|
||
|
|
else:
|
||
|
|
return jsonify({'success': False, 'error': '写入飞书失败'}), 500
|
||
|
|
|
||
|
|
except Exception as e:
|
||
|
|
logger.error(f"处理监控文件失败: {str(e)}")
|
||
|
|
return jsonify({'success': False, 'error': str(e)}), 500
|
||
|
|
|
||
|
|
if __name__ == '__main__':
|
||
|
|
# 初始化应用
|
||
|
|
init_app()
|
||
|
|
|
||
|
|
# 启动Web服务器
|
||
|
|
logger.info("启动Web服务器...")
|
||
|
|
app.run(host='0.0.0.0', port=5000, debug=False)
|