From 69f92205e98d71f48e1308f4d5e51f2a29e25920 Mon Sep 17 00:00:00 2001
From: Jeason <1710884619@qq.com>
Date: Wed, 18 Mar 2026 15:15:52 +0800
Subject: [PATCH] =?UTF-8?q?=E6=88=AA=E5=9B=BE=E8=AF=86=E5=88=AB=E9=A3=9E?=
 =?UTF-8?q?=E4=B9=A6=E4=B8=AA=E4=BA=BA=E4=BB=BB=E5=8A=A1=E6=B8=85=E5=8D=95?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 .gitignore                 |   70 +++
 Web应用使用说明.md         |  307 +++++++++++
 code (4).html              | 1028 ++++++++++++++++++++++++++++++++++++
 config.example.yaml        |   45 ++
 data/test_user_cache.json  |    5 +
 data/user_cache.json       |   71 +++
 main.py                    |  317 +++++++++++
 requirements.txt           |   18 +
 services/__init__.py       |   11 +
 services/ai_service.py     |  624 ++++++++++++++++++++++
 services/feishu_service.py |  489 +++++++++++++++++
 setup.py                   |  193 +++++++
 start_web_app.py           |   71 +++
 templates/index.html       |  829 +++++++++++++++++++++++++++++
 tests/__init__.py          |    5 +
 utils/__init__.py          |   54 ++
 utils/config_loader.py     |  200 +++++++
 utils/logger.py            |  185 +++++++
 utils/notifier.py          |  306 +++++++++++
 utils/user_cache.py        |  211 ++++++++
 web_app.py                 |  452 ++++++++++++++++
 优先级修改说明.md          |   56 ++
 项目结构说明.md            |  288 ++++++++++
 23 files changed, 5835 insertions(+)
 create mode 100644 .gitignore
 create mode 100644 Web应用使用说明.md
 create mode 100644 code (4).html
 create mode 100644 config.example.yaml
 create mode 100644 data/test_user_cache.json
 create mode 100644 data/user_cache.json
 create mode 100644 main.py
 create mode 100644 requirements.txt
 create mode 100644 services/__init__.py
 create mode 100644 services/ai_service.py
 create mode 100644 services/feishu_service.py
 create mode 100644 setup.py
 create mode 100644 start_web_app.py
 create mode 100644 templates/index.html
 create mode 100644 tests/__init__.py
 create mode 100644 utils/__init__.py
 create mode 100644 utils/config_loader.py
 create mode 100644 utils/logger.py
 create mode 100644 utils/notifier.py
 create mode 100644 utils/user_cache.py
 create mode 100644 web_app.py
 create mode 100644 优先级修改说明.md
 create mode 100644 项目结构说明.md

diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..cdc890c
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,70 @@
+# Python
+__pycache__/
+*.py[cod]
+*$py.class
+*.so
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+
+# 虚拟环境
+venv/
+env/
+ENV/
+.env
+.env.local
+
+# 配置文件（包含敏感信息）
+config.yaml
+*.secret
+*.key
+
+# 日志文件
+*.log
+logs/
+
+# 测试相关
+.pytest_cache/
+.coverage
+htmlcov/
+.tox/
+.nox/
+.coverage.*
+*.lcov
+
+# IDE
+.vscode/
+.idea/
+*.swp
+*.swo
+*~
+
+# 操作系统
+.DS_Store
+Thumbs.db
+
+# 项目特定
+monitor_images/
+processed_images/
+test_*.py
+test_img.jpg
+test_img.png
+
+# 临时文件
+temp/
+tmp/
+*.tmp
+*.temp
\ No newline at end of file
diff --git a/Web应用使用说明.md b/Web应用使用说明.md
new file mode 100644
index 0000000..62310d1
--- /dev/null
+++ b/Web应用使用说明.md
@@ -0,0 +1,307 @@
+# Screen2Feishu Web应用使用说明
+
+## 概述
+
+Screen2Feishu Web应用是一个结合了前端界面和后端功能的完整解决方案。它提供了一个用户友好的界面，可以：
+
+1. **手动添加任务**：通过表单添加任务到飞书多维表格
+2. **图片上传分析**：上传截图，AI自动分析并生成任务
+3. **实时预览**：查看AI分析结果和任务信息
+4. **用户匹配**：自动匹配飞书用户，处理重名情况
+
+## 启动应用
+
+### 1. 安装依赖
+
+```bash
+pip install flask flask-cors
+```
+
+### 2. 配置文件
+
+确保 `config.yaml` 文件已正确配置：
+
+```yaml
+ai:
+  api_key: "your_api_key"
+  base_url: "https://api.openai.com/v1"
+  model: "gpt-4o"
+
+feishu:
+  app_id: "your_app_id"
+  app_secret: "your_app_secret"
+  app_token: "your_app_token"
+  table_id: "your_table_id"
+
+system:
+  watch_folder: "./monitor_images"
+  post_process: "keep"
+  processed_folder: "./processed_images"
+  log_level: "INFO"
+  log_file: "app.log"
+  memory_processing: false
+  
+  user_matching:
+    enabled: true
+    fallback_to_random: true
+    cache_enabled: true
+    cache_file: "./data/user_cache.json"
+```
+
+### 3. 启动应用
+
+```bash
+python start_web_app.py
+```
+
+或者直接运行：
+
+```bash
+python web_app.py
+```
+
+### 4. 访问界面
+
+打开浏览器，访问：`http://localhost:5000`
+
+## 功能说明
+
+### 1. 手动添加任务
+
+1. 在"添加新任务..."输入框中输入任务描述
+2. 选择截止时间（可选）
+3. 选择分类（工作/学习/生活/其他）
+4. 选择优先级（高/中/低）
+5. 点击"添加"按钮
+
+**AI分析过程**：
+- 系统会调用AI服务分析任务描述
+- 自动识别任务发起人和部门
+- 匹配飞书用户（如果启用）
+- 将任务写入飞书多维表格
+
+### 2. 图片上传分析
+
+1. 点击"上传分析"按钮或拖拽图片到文件选择框
+2. 选择截图文件（支持JPG、PNG等格式）
+3. 系统会自动：
+   - 读取图片到内存
+   - 调用AI分析图片内容
+   - 识别任务信息（描述、优先级、发起人等）
+   - 匹配飞书用户
+   - 写入飞书表格
+   - 在界面显示分析结果
+
+**AI分析结果**：
+- 任务描述
+- 优先级（紧急/较紧急/一般/普通）
+- 状态（未开始/进行中/已完成）
+- 发起人姓名
+- 部门信息
+- 开始日期
+- 截止日期
+
+### 3. 任务管理
+
+- **筛选**：按分类、状态、优先级筛选任务
+- **编辑**：点击编辑按钮修改任务
+- **删除**：点击删除按钮删除任务
+- **完成**：勾选复选框标记任务完成
+
+### 4. 通知功能
+
+- **浏览器通知**：启用后可在任务到期时收到通知
+- **桌面通知**：显示操作结果和AI分析结果
+
+## API接口
+
+### 1. 上传图片分析
+
+**接口**：`POST /api/upload`
+
+**请求**：
+```json
+{
+  "image": "图片文件"
+}
+```
+
+**响应**：
+```json
+{
+  "success": true,
+  "message": "任务已成功添加到飞书",
+  "ai_result": {
+    "task_description": "任务描述",
+    "priority": "紧急",
+    "status": "未开始",
+    "initiator": "张三",
+    "department": "研发部",
+    "start_date": "2026-03-03",
+    "due_date": "2026-03-10"
+  }
+}
+```
+
+### 2. 获取用户缓存信息
+
+**接口**：`GET /api/user_cache`
+
+**响应**：
+```json
+{
+  "success": true,
+  "stats": {
+    "user_count": 10,
+    "recent_contact_count": 5,
+    "cache_age_hours": 0.5,
+    "is_expired": false
+  }
+}
+```
+
+### 3. 获取配置信息
+
+**接口**：`GET /api/config`
+
+**响应**：
+```json
+{
+  "success": true,
+  "config": {
+    "memory_processing": false,
+    "user_matching_enabled": true,
+    "fallback_to_random": true,
+    "cache_enabled": true,
+    "post_process": "keep"
+  }
+}
+```
+
+## 配置说明
+
+### 内存处理模式
+
+```yaml
+system:
+  memory_processing: true  # 启用内存处理，不保存图片文件
+```
+
+### 用户匹配配置
+
+```yaml
+system:
+  user_matching:
+    enabled: true  # 启用用户匹配
+    fallback_to_random: true  # 启用随机匹配回退
+    cache_enabled: true  # 启用缓存
+    cache_file: "./data/user_cache.json"  # 缓存文件路径
+```
+
+### 文件处理策略
+
+```yaml
+system:
+  post_process: "keep"  # 保留原始文件
+  # post_process: "delete"  # 删除原始文件
+  # post_process: "move"  # 移动到processed_images目录
+```
+
+## 使用场景
+
+### 场景1：截图转任务
+
+1. 从聊天记录、邮件或文档中截图
+2. 上传截图到Web界面
+3. AI自动分析截图内容
+4. 生成任务并写入飞书表格
+
+### 场景2：手动创建任务
+
+1. 在Web界面手动输入任务描述
+2. AI分析任务内容，提供优化建议
+3. 自动匹配任务发起人
+4. 写入飞书表格
+
+### 场景3：批量处理
+
+1. 准备多个截图文件
+2. 逐个上传分析
+3. 系统自动处理并写入飞书
+
+## 注意事项
+
+1. **飞书API权限**：确保飞书应用有读取用户列表和写入表格的权限
+2. **图片大小**：建议图片大小不超过10MB
+3. **网络连接**：需要稳定的网络连接调用AI和飞书API
+4. **浏览器通知**：需要用户授权浏览器通知权限
+5. **缓存管理**：用户缓存默认24小时过期，可手动清理
+
+## 故障排除
+
+### 1. 无法启动应用
+
+- 检查依赖是否安装完整
+- 检查配置文件是否正确
+- 检查端口5000是否被占用
+
+### 2. AI分析失败
+
+- 检查API密钥是否正确
+- 检查网络连接
+- 查看日志文件 `app.log`
+
+### 3. 飞书写入失败
+
+- 检查飞书API配置
+- 检查表格ID和Base Token
+- 确保飞书应用有写入权限
+
+### 4. 用户匹配失败
+
+- 检查飞书API权限（用户列表读取）
+- 检查缓存文件路径
+- 查看日志文件了解详细错误
+
+## 技术架构
+
+### 前端
+- HTML5 + CSS3 + JavaScript
+- 响应式设计，支持移动端
+- 实时通知和状态反馈
+
+### 后端
+- Flask Web框架
+- AI服务集成（OpenAI格式API）
+- 飞书API集成
+- 用户缓存管理
+
+### 数据流
+1. 用户上传图片/输入任务
+2. 前端调用后端API
+3. 后端调用AI服务分析
+4. 后端匹配飞书用户
+5. 后端写入飞书表格
+6. 返回结果给前端
+7. 前端显示结果和通知
+
+## 扩展功能
+
+### 1. 批量处理
+可以扩展支持批量上传和处理多个图片文件
+
+### 2. 实时预览
+可以添加图片预览功能，显示上传的截图
+
+### 3. 任务模板
+可以添加任务模板功能，快速创建常见任务
+
+### 4. 统计分析
+可以添加任务统计和分析功能
+
+### 5. 多语言支持
+可以添加多语言界面支持
+
+## 总结
+
+Screen2Feishu Web应用提供了一个完整的解决方案，将前端界面与后端功能完美结合。用户可以通过友好的界面轻松创建任务，AI自动分析并写入飞书表格，大大提高了工作效率。
\ No newline at end of file
diff --git a/code (4).html b/code (4).html
new file mode 100644
index 0000000..84ef4e6
--- /dev/null
+++ b/code (4).html	
@@ -0,0 +1,1028 @@
+<!DOCTYPE html>
+<html lang="zh-CN">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>高级任务清单</title>
+    <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.0.0/css/all.min.css">
+    <style>
+        * {
+            margin: 0;
+            padding: 0;
+            box-sizing: border-box;
+            font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
+        }
+        body {
+            background: linear-gradient(135deg, #6a11cb 0%, #2575fc 100%);
+            min-height: 100vh;
+            display: flex;
+            justify-content: center;
+            align-items: center;
+            padding: 20px;
+        }
+        .container {
+            width: 100%;
+            max-width: 900px;
+            background: rgba(255, 255, 255, 0.95);
+            border-radius: 20px;
+            box-shadow: 0 15px 30px rgba(0, 0, 0, 0.2);
+            overflow: hidden;
+            backdrop-filter: blur(10px);
+        }
+        header {
+            background: #2c3e50;
+            color: white;
+            padding: 25px;
+            text-align: center;
+            position: relative;
+        }
+        header h1 {
+            font-size: 2.2rem;
+            margin-bottom: 5px;
+            letter-spacing: 1px;
+        }
+        header p {
+            opacity: 0.8;
+            font-size: 0.9rem;
+        }
+        .stats {
+            position: absolute;
+            right: 25px;
+            top: 50%;
+            transform: translateY(-50%);
+            text-align: center;
+            background: rgba(255,255,255,0.15);
+            padding: 8px 15px;
+            border-radius: 10px;
+            font-size: 0.85rem;
+        }
+        .input-section {
+            padding: 25px;
+            border-bottom: 1px solid #eee;
+            background: #f8f9fa;
+        }
+        .input-group {
+            display: flex;
+            gap: 10px;
+            margin-bottom: 15px;
+            flex-wrap: wrap;
+        }
+        input[type="text"], input[type="datetime-local"] {
+            flex: 1;
+            padding: 14px 18px;
+            border: 2px solid #e1e5eb;
+            border-radius: 12px;
+            font-size: 1rem;
+            transition: all 0.3s;
+            min-width: 200px;
+        }
+        input[type="text"]:focus, input[type="datetime-local"]:focus {
+            border-color: #3498db;
+            outline: none;
+            box-shadow: 0 0 0 3px rgba(52, 152, 219, 0.2);
+        }
+        select {
+            padding: 14px 18px;
+            border: 2px solid #e1e5eb;
+            border-radius: 12px;
+            background: white;
+            font-size: 0.95rem;
+            cursor: pointer;
+        }
+        .priority {
+            display: flex;
+            gap: 10px;
+            margin-top: 10px;
+            flex-wrap: wrap;
+        }
+        .priority label {
+            display: flex;
+            align-items: center;
+            gap: 5px;
+            padding: 8px 15px;
+            background: #f0f4f8;
+            border-radius: 8px;
+            cursor: pointer;
+            transition: all 0.2s;
+        }
+        .priority input[type="radio"] {
+            accent-color: #3498db;
+        }
+        .priority label:hover {
+            background: #e1e8f0;
+        }
+        .priority input:checked + span {
+            font-weight: bold;
+        }
+        button#addTask {
+            background: #3498db;
+            color: white;
+            border: none;
+            padding: 14px 25px;
+            border-radius: 12px;
+            font-size: 1rem;
+            font-weight: 600;
+            cursor: pointer;
+            transition: all 0.3s;
+            display: flex;
+            align-items: center;
+            gap: 8px;
+        }
+        button#addTask:hover {
+            background: #2980b9;
+            transform: translateY(-2px);
+            box-shadow: 0 5px 15px rgba(52, 152, 219, 0.4);
+        }
+        button#requestPermission {
+            background: #27ae60;
+            color: white;
+            border: none;
+            padding: 12px 20px;
+            border-radius: 12px;
+            font-size: 0.9rem;
+            font-weight: 600;
+            cursor: pointer;
+            transition: all 0.3s;
+            display: flex;
+            align-items: center;
+            gap: 8px;
+            margin-top: 10px;
+        }
+        button#requestPermission:hover {
+            background: #219653;
+            transform: translateY(-2px);
+            box-shadow: 0 5px 15px rgba(39, 174, 96, 0.4);
+        }
+        .filter-section {
+            padding: 15px 25px;
+            background: #f8f9fa;
+            border-bottom: 1px solid #eee;
+            display: flex;
+            gap: 10px;
+            flex-wrap: wrap;
+        }
+        .filter-btn {
+            background: #ecf0f1;
+            border: none;
+            padding: 8px 16px;
+            border-radius: 20px;
+            cursor: pointer;
+            transition: all 0.2s;
+            font-size: 0.9rem;
+        }
+        .filter-btn.active, .filter-btn:hover {
+            background: #3498db;
+            color: white;
+        }
+        .task-list {
+            padding: 25px;
+            max-height: 500px;
+            overflow-y: auto;
+        }
+        .task-item {
+            background: white;
+            border-radius: 12px;
+            padding: 18px;
+            margin-bottom: 15px;
+            display: flex;
+            align-items: center;
+            gap: 15px;
+            box-shadow: 0 4px 10px rgba(0, 0, 0, 0.05);
+            transform: translateY(0);
+            transition: all 0.3s;
+            border-left: 4px solid transparent;
+            animation: fadeIn 0.4s ease-out;
+        }
+        @keyframes fadeIn {
+            from { opacity: 0; transform: translateY(10px); }
+            to { opacity: 1; transform: translateY(0); }
+        }
+        .task-item:hover {
+            transform: translateY(-3px);
+            box-shadow: 0 6px 15px rgba(0, 0, 0, 0.1);
+        }
+        .task-item.high {
+            border-left-color: #e74c3c;
+        }
+        .task-item.medium {
+            border-left-color: #f39c12;
+        }
+        .task-item.low {
+            border-left-color: #2ecc71;
+        }
+        .task-item.completed {
+            opacity: 0.7;
+            background: #f8f9fa;
+        }
+        .task-item.expiring {
+            background: #fff8e1;
+            border-left-color: #f39c12;
+        }
+        .task-item.expired {
+            background: #ffebee;
+            border-left-color: #e74c3c;
+        }
+        .task-checkbox {
+            width: 22px;
+            height: 22px;
+            accent-color: #2ecc71;
+            cursor: pointer;
+        }
+        .task-content {
+            flex: 1;
+        }
+        .task-text {
+            font-size: 1.05rem;
+            margin-bottom: 5px;
+            word-break: break-word;
+            display: flex;
+            align-items: center;
+            gap: 8px;
+        }
+        .task-item.completed .task-text {
+            text-decoration: line-through;
+            color: #7f8c8d;
+        }
+        .task-meta {
+            display: flex;
+            gap: 10px;
+            font-size: 0.8rem;
+            color: #7f8c8d;
+            flex-wrap: wrap;
+            align-items: center;
+        }
+        .task-tag {
+            background: #e1f0fa;
+            color: #3498db;
+            padding: 3px 8px;
+            border-radius: 4px;
+            font-weight: 500;
+        }
+        .task-priority {
+            padding: 3px 8px;
+            border-radius: 4px;
+            font-weight: 500;
+            color: white;
+        }
+        .high .task-priority { background: #e74c3c; }
+        .medium .task-priority { background: #f39c12; }
+        .low .task-priority { background: #2ecc71; }
+        .deadline {
+            display: flex;
+            align-items: center;
+            gap: 5px;
+            padding: 3px 8px;
+            border-radius: 4px;
+            font-weight: 500;
+            background: #f8f9fa;
+            color: #2c3e50;
+        }
+        .deadline.expiring {
+            background: #ffecb3;
+            color: #ff8f00;
+        }
+        .deadline.expired {
+            background: #ffcdd2;
+            color: #c62828;
+        }
+        .task-actions {
+            display: flex;
+            gap: 10px;
+        }
+        .task-btn {
+            background: none;
+            border: none;
+            width: 36px;
+            height: 36px;
+            border-radius: 50%;
+            display: flex;
+            align-items: center;
+            justify-content: center;
+            cursor: pointer;
+            transition: all 0.2s;
+            font-size: 1.1rem;
+        }
+        .task-btn.edit {
+            color: #3498db;
+        }
+        .task-btn.delete {
+            color: #e74c3c;
+        }
+        .task-btn:hover {
+            transform: scale(1.15);
+            background: rgba(0,0,0,0.05);
+        }
+        .empty-state {
+            text-align: center;
+            padding: 40px 20px;
+            color: #7f8c8d;
+        }
+        .empty-state i {
+            font-size: 3.5rem;
+            margin-bottom: 15px;
+            opacity: 0.3;
+        }
+        .empty-state p {
+            font-size: 1.1rem;
+            margin-top: 10px;
+        }
+        footer {
+            padding: 20px;
+            text-align: center;
+            color: #7f8c8d;
+            font-size: 0.9rem;
+            border-top: 1px solid #eee;
+            background: #f8f9fa;
+        }
+        .notification-status {
+            text-align: center;
+            padding: 8px;
+            margin-top: 10px;
+            border-radius: 8px;
+            font-size: 0.85rem;
+        }
+        .notification-status.enabled {
+            background: #d4edda;
+            color: #155724;
+        }
+        .notification-status.disabled {
+            background: #f8d7da;
+            color: #721c24;
+        }
+
+        /* 响应式设计 */
+        @media (max-width: 768px) {
+            .input-group {
+                flex-direction: column;
+            }
+            input[type="text"], input[type="datetime-local"], select {
+                width: 100%;
+            }
+            .priority {
+                flex-wrap: wrap;
+            }
+            .stats {
+                position: static;
+                transform: none;
+                margin-top: 10px;
+                display: inline-block;
+            }
+            header {
+                padding: 20px 15px;
+            }
+            .task-item {
+                flex-wrap: wrap;
+            }
+            .task-actions {
+                width: 100%;
+                justify-content: flex-end;
+                margin-top: 8px;
+            }
+        }
+
+        /* 编辑模态框 */
+        .modal {
+            display: none;
+            position: fixed;
+            top: 0;
+            left: 0;
+            width: 100%;
+            height: 100%;
+            background: rgba(0,0,0,0.5);
+            justify-content: center;
+            align-items: center;
+            z-index: 1000;
+        }
+        .modal-content {
+            background: white;
+            padding: 30px;
+            border-radius: 15px;
+            width: 90%;
+            max-width: 500px;
+            box-shadow: 0 10px 30px rgba(0,0,0,0.2);
+            animation: modalAppear 0.3s ease-out;
+        }
+        @keyframes modalAppear {
+            from { opacity: 0; transform: translateY(-20px); }
+            to { opacity: 1; transform: translateY(0); }
+        }
+        .modal h2 {
+            margin-bottom: 20px;
+            color: #2c3e50;
+        }
+        .modal input {
+            width: 100%;
+            padding: 12px;
+            margin-bottom: 15px;
+            border: 2px solid #e1e5eb;
+            border-radius: 8px;
+            font-size: 1rem;
+        }
+        .modal-buttons {
+            display: flex;
+            gap: 10px;
+            justify-content: flex-end;
+        }
+        .modal-buttons button {
+            padding: 10px 20px;
+            border: none;
+            border-radius: 8px;
+            cursor: pointer;
+            font-weight: 600;
+        }
+        .save-btn {
+            background: #3498db;
+            color: white;
+        }
+        .cancel-btn {
+            background: #ecf0f1;
+            color: #2c3e50;
+        }
+
+        /* 滚动条样式 */
+        .task-list::-webkit-scrollbar {
+            width: 8px;
+        }
+        .task-list::-webkit-scrollbar-track {
+            background: #f1f1f1;
+            border-radius: 10px;
+        }
+        .task-list::-webkit-scrollbar-thumb {
+            background: #bdc3c7;
+            border-radius: 10px;
+        }
+        .task-list::-webkit-scrollbar-thumb:hover {
+            background: #95a5a6;
+        }
+
+        /* 通知图标动画 */
+        .fa-bell {
+            animation: pulse 2s infinite;
+        }
+        @keyframes pulse {
+            0% { transform: scale(1); }
+            50% { transform: scale(1.1); }
+            100% { transform: scale(1); }
+        }
+    </style>
+</head>
+<body>
+    <div class="container">
+        <header>
+            <h1><i class="fas fa-tasks"></i> 高级任务清单</h1>
+            <p>高效管理你的日常任务，支持截止时间提醒</p>
+            <div class="stats">
+                <div>总计: <span id="totalTasks">0</span></div>
+                <div>完成: <span id="completedTasks">0</span></div>
+            </div>
+        </header>
+        <div class="input-section">
+            <div class="input-group">
+                <input type="text" id="taskInput" placeholder="添加新任务..." autocomplete="off">
+                <input type="datetime-local" id="deadlineInput">
+                <select id="categorySelect">
+                    <option value="工作">工作</option>
+                    <option value="学习">学习</option>
+                    <option value="生活">生活</option>
+                    <option value="其他">其他</option>
+                </select>
+                <button id="addTask"><i class="fas fa-plus"></i> 添加</button>
+            </div>
+            <div class="priority">
+                <label>
+                    <input type="radio" name="priority" value="high">
+                    <span style="color: #e74c3c;">高优先级</span>
+                </label>
+                <label>
+                    <input type="radio" name="priority" value="medium" checked>
+                    <span style="color: #f39c12;">中优先级</span>
+                </label>
+                <label>
+                    <input type="radio" name="priority" value="low">
+                    <span style="color: #2ecc71;">低优先级</span>
+                </label>
+            </div>
+            <div style="margin-top: 15px;">
+                <button id="requestPermission"><i class="fas fa-bell"></i> 启用任务提醒通知</button>
+                <div id="notificationStatus" class="notification-status disabled">通知权限: 未授权</div>
+            </div>
+        </div>
+        <div class="filter-section">
+            <button class="filter-btn active" data-filter="all">全部</button>
+            <button class="filter-btn" data-filter="work">工作</button>
+            <button class="filter-btn" data-filter="study">学习</button>
+            <button class="filter-btn" data-filter="life">生活</button>
+            <button class="filter-btn" data-filter="other">其他</button>
+            <button class="filter-btn" data-filter="completed">已完成</button>
+            <button class="filter-btn" data-filter="active">未完成</button>
+            <button class="filter-btn" data-filter="expiring">即将到期</button>
+        </div>
+        <div class="task-list" id="taskList">
+            <div class="empty-state">
+                <i class="fas fa-clipboard-list"></i>
+                <h3>暂无任务</h3>
+                <p>添加您的第一个任务开始吧！</p>
+            </div>
+        </div>
+        <footer>
+            <p>© 2023 高级TodoList | 数据保存在本地浏览器中 | 支持截止时间提醒</p>
+        </footer>
+    </div>
+    <!-- 编辑任务模态框 -->
+    <div class="modal" id="editModal">
+        <div class="modal-content">
+            <h2><i class="fas fa-edit"></i> 编辑任务</h2>
+            <input type="text" id="editTaskInput" placeholder="编辑任务内容...">
+            <div class="modal-buttons">
+                <button class="cancel-btn" id="cancelEdit">取消</button>
+                <button class="save-btn" id="saveEdit">保存</button>
+            </div>
+        </div>
+    </div>
+    <script>
+        // 任务数据结构
+        let tasks = JSON.parse(localStorage.getItem('tasks')) || [];
+        let currentEditId = null;
+        let currentFilter = 'all';
+        let notificationPermission = Notification.permission === 'granted';
+        let reminderCheckInterval;
+
+        // DOM元素
+        const taskInput = document.getElementById('taskInput');
+        const deadlineInput = document.getElementById('deadlineInput');
+        const categorySelect = document.getElementById('categorySelect');
+        const addTaskBtn = document.getElementById('addTask');
+        const taskList = document.getElementById('taskList');
+        const totalTasks = document.getElementById('totalTasks');
+        const completedTasks = document.getElementById('completedTasks');
+        const filterBtns = document.querySelectorAll('.filter-btn');
+        const editModal = document.getElementById('editModal');
+        const editTaskInput = document.getElementById('editTaskInput');
+        const saveEditBtn = document.getElementById('saveEdit');
+        const cancelEditBtn = document.getElementById('cancelEdit');
+        const requestPermissionBtn = document.getElementById('requestPermission');
+        const notificationStatus = document.getElementById('notificationStatus');
+
+        // 初始化
+        document.addEventListener('DOMContentLoaded', () => {
+            renderTasks();
+            updateStats();
+            checkNotificationPermission();
+
+            // 设置默认日期时间为明天
+            const tomorrow = new Date();
+            tomorrow.setDate(tomorrow.getDate() + 1);
+            tomorrow.setHours(9, 0, 0, 0);
+            deadlineInput.value = formatDateTimeLocal(tomorrow);
+
+            // 为优先级单选按钮添加事件
+            document.querySelectorAll('input[name="priority"]').forEach(radio => {
+                radio.addEventListener('change', function() {
+                    document.querySelectorAll('.priority label').forEach(label => {
+                        label.style.background = '#f0f4f8';
+                    });
+                    this.parentElement.style.background = '#d6eaf8';
+                });
+            });
+
+            // 设置默认选中的优先级样式
+            document.querySelector('input[name="priority"][value="medium"]').parentElement.style.background = '#d6eaf8';
+
+            // 启动提醒检查
+            startReminderCheck();
+        });
+
+        // 检查通知权限
+        function checkNotificationPermission() {
+            if (!("Notification" in window)) {
+                notificationStatus.textContent = "您的浏览器不支持通知功能";
+                notificationStatus.className = "notification-status disabled";
+                return;
+            }
+
+            if (Notification.permission === "granted") {
+                notificationPermission = true;
+                notificationStatus.textContent = "通知权限: 已授权";
+                notificationStatus.className = "notification-status enabled";
+                requestPermissionBtn.style.display = "none";
+            } else if (Notification.permission === "denied") {
+                notificationPermission = false;
+                notificationStatus.textContent = "通知权限: 已被拒绝，请在浏览器设置中手动启用";
+                notificationStatus.className = "notification-status disabled";
+            } else {
+                notificationPermission = false;
+                notificationStatus.textContent = "通知权限: 未授权";
+                notificationStatus.className = "notification-status disabled";
+            }
+        }
+
+        // 请求通知权限
+        requestPermissionBtn.addEventListener('click', () => {
+            if (!("Notification" in window)) {
+                alert("您的浏览器不支持通知功能");
+                return;
+            }
+
+            Notification.requestPermission().then(permission => {
+                checkNotificationPermission();
+                if (permission === "granted") {
+                    showNotification("通知权限已启用！您将收到任务提醒");
+                }
+            });
+        });
+
+        // 启动提醒检查
+        function startReminderCheck() {
+            if (reminderCheckInterval) clearInterval(reminderCheckInterval);
+            reminderCheckInterval = setInterval(checkReminders, 60000); // 每分钟检查一次
+            checkReminders(); // 立即检查一次
+        }
+
+        // 检查提醒
+        function checkReminders() {
+            if (!notificationPermission) return;
+
+            const now = new Date();
+            tasks.forEach(task => {
+                if (task.completed || !task.deadline || task.reminded) return;
+
+                const deadline = new Date(task.deadline);
+                const timeDiff = deadline - now;
+
+                // 如果剩余时间小于等于10分钟且大于0，则发送提醒
+                if (timeDiff <= 10 * 60 * 1000 && timeDiff > 0) {
+                    sendNotification("任务即将到期", `任务"${task.text}"将在10分钟后到期！`);
+                    task.reminded = true;
+                    saveTasks();
+                    renderTasks();
+                }
+
+                // 如果已过期且未提醒过，则发送过期通知
+                if (timeDiff <= 0 && !task.expiredNotified) {
+                    sendNotification("任务已过期", `任务"${task.text}"已超过截止时间！`);
+                    task.expiredNotified = true;
+                    saveTasks();
+                    renderTasks();
+                }
+            });
+        }
+
+        // 发送通知
+        function sendNotification(title, body) {
+            if (!notificationPermission) return;
+
+            try {
+                const notification = new Notification(title, {
+                    body: body,
+                    icon: "https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.0.0/svgs/solid/check-circle.svg",
+                    badge: "https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.0.0/svgs/solid/check-circle.svg"
+                });
+
+                notification.onclick = () => {
+                    window.focus();
+                    notification.close();
+                };
+
+                // 自动关闭通知
+                setTimeout(() => {
+                    notification.close();
+                }, 8000);
+            } catch (e) {
+                console.error("通知发送失败:", e);
+            }
+        }
+
+        // 添加任务
+        addTaskBtn.addEventListener('click', addTask);
+        taskInput.addEventListener('keypress', (e) => {
+            if (e.key === 'Enter') addTask();
+        });
+
+        function addTask() {
+            const text = taskInput.value.trim();
+            if (!text) {
+                taskInput.focus();
+                return;
+            }
+
+            const priority = document.querySelector('input[name="priority"]:checked').value;
+            const category = categorySelect.value;
+            const deadline = deadlineInput.value ? new Date(deadlineInput.value).toISOString() : null;
+
+            const newTask = {
+                id: Date.now(),
+                text,
+                category,
+                priority,
+                deadline,
+                completed: false,
+                reminded: false,
+                expiredNotified: false,
+                createdAt: new Date().toISOString()
+            };
+
+            tasks.unshift(newTask); // 添加到数组开头
+            saveTasks();
+            renderTasks();
+            updateStats();
+
+            // 清空输入框
+            taskInput.value = '';
+            taskInput.focus();
+
+            // 显示添加成功提示
+            showNotification('任务添加成功！');
+
+            // 检查是否需要立即提醒
+            if (deadline) {
+                checkReminders();
+            }
+        }
+
+        // 渲染任务列表
+        function renderTasks() {
+            const filteredTasks = filterTasks();
+            if (filteredTasks.length === 0) {
+                taskList.innerHTML = `
+                    <div class="empty-state">
+                        <i class="fas fa-clipboard-list"></i>
+                        <h3>${getFilterTitle()}</h3>
+                        <p>${getFilterMessage()}</p>
+                    </div>
+                `;
+                return;
+            }
+
+            taskList.innerHTML = filteredTasks.map(task => {
+                const deadlineInfo = getDeadlineInfo(task.deadline);
+                let deadlineClass = '';
+                if (deadlineInfo.status === 'expiring') deadlineClass = 'expiring';
+                if (deadlineInfo.status === 'expired') deadlineClass = 'expired';
+
+                return `
+                <div class="task-item ${task.completed ? 'completed' : ''} ${task.priority} ${deadlineClass}" data-id="${task.id}">
+                    <input type="checkbox" class="task-checkbox" ${task.completed ? 'checked' : ''}
+                           onchange="toggleComplete(${task.id})">
+                    <div class="task-content">
+                        <div class="task-text">
+                            ${task.text}
+                            ${deadlineInfo.status === 'expired' ? '<i class="fas fa-exclamation-circle" style="color: #e74c3c;"></i>' : ''}
+                        </div>
+                        <div class="task-meta">
+                            <span class="task-tag">${task.category}</span>
+                            <span class="task-priority">${getPriorityText(task.priority)}</span>
+                            ${task.deadline ? `<span class="deadline ${deadlineClass}"><i class="fas fa-clock"></i> ${deadlineInfo.text}</span>` : ''}
+                            <span>${formatDate(task.createdAt)}</span>
+                        </div>
+                    </div>
+                    <div class="task-actions">
+                        <button class="task-btn edit" onclick="openEditModal(${task.id})" title="编辑">
+                            <i class="fas fa-edit"></i>
+                        </button>
+                        <button class="task-btn delete" onclick="deleteTask(${task.id})" title="删除">
+                            <i class="fas fa-trash-alt"></i>
+                        </button>
+                    </div>
+                </div>
+            `}).join('');
+        }
+
+        // 获取截止时间信息
+        function getDeadlineInfo(deadlineStr) {
+            if (!deadlineStr) return { text: '无截止时间', status: 'none' };
+
+            const now = new Date();
+            const deadline = new Date(deadlineStr);
+            const diff = deadline - now;
+            const hours = Math.floor(diff / (1000 * 60 * 60));
+            const minutes = Math.floor((diff % (1000 * 60 * 60)) / (1000 * 60));
+
+            if (diff < 0) {
+                return { text: `已过期 (${Math.abs(hours)}小时${Math.abs(minutes)}分钟)`, status: 'expired' };
+            } else if (diff < 10 * 60 * 1000) {
+                return { text: `即将到期 (${minutes}分钟)`, status: 'expiring' };
+            } else if (diff < 24 * 60 * 60 * 1000) {
+                return { text: `今天 ${deadline.getHours().toString().padStart(2, '0')}:${deadline.getMinutes().toString().padStart(2, '0')}`, status: 'normal' };
+            } else {
+                return { text: `${deadline.getMonth() + 1}/${deadline.getDate()} ${deadline.getHours().toString().padStart(2, '0')}:${deadline.getMinutes().toString().padStart(2, '0')}`, status: 'normal' };
+            }
+        }
+
+        // 过滤任务
+        function filterTasks() {
+            const now = new Date();
+            switch(currentFilter) {
+                case 'work': return tasks.filter(t => t.category === '工作');
+                case 'study': return tasks.filter(t => t.category === '学习');
+                case 'life': return tasks.filter(t => t.category === '生活');
+                case 'other': return tasks.filter(t => t.category === '其他');
+                case 'completed': return tasks.filter(t => t.completed);
+                case 'active': return tasks.filter(t => !t.completed);
+                case 'expiring':
+                    return tasks.filter(t => {
+                        if (!t.deadline || t.completed) return false;
+                        const deadline = new Date(t.deadline);
+                        return deadline - now <= 10 * 60 * 1000 && deadline > now;
+                    });
+                default: return tasks;
+            }
+        }
+
+        // 获取过滤标题
+        function getFilterTitle() {
+            const titles = {
+                'all': '暂无任务',
+                'work': '暂无工作任务',
+                'study': '暂无学习任务',
+                'life': '暂无生活任务',
+                'other': '暂无其他任务',
+                'completed': '暂无已完成任务',
+                'active': '暂无未完成任务',
+                'expiring': '暂无即将到期的任务'
+            };
+            return titles[currentFilter] || '暂无任务';
+        }
+
+        // 获取过滤消息
+        function getFilterMessage() {
+            const messages = {
+                'all': '添加您的第一个任务开始吧！',
+                'work': '添加工作任务提高效率',
+                'study': '添加学习任务充实自己',
+                'life': '添加生活任务让生活更有序',
+                'other': '添加其他任务记录一切',
+                'completed': '完成更多任务吧！',
+                'active': '快去完成您的任务吧！',
+                'expiring': '没有即将到期的任务，太棒了！'
+            };
+            return messages[currentFilter] || '添加您的第一个任务开始吧！';
+        }
+
+        // 切换完成状态
+        function toggleComplete(id) {
+            const task = tasks.find(t => t.id === id);
+            if (task) {
+                task.completed = !task.completed;
+                saveTasks();
+                renderTasks();
+                updateStats();
+                showNotification(task.completed ? '任务标记为完成！' : '任务已重新激活！');
+            }
+        }
+
+        // 删除任务
+        function deleteTask(id) {
+            if (confirm('确定要删除这个任务吗？')) {
+                tasks = tasks.filter(t => t.id !== id);
+                saveTasks();
+                renderTasks();
+                updateStats();
+                showNotification('任务已删除');
+            }
+        }
+
+        // 打开编辑模态框
+        function openEditModal(id) {
+            const task = tasks.find(t => t.id === id);
+            if (task) {
+                currentEditId = id;
+                editTaskInput.value = task.text;
+                editModal.style.display = 'flex';
+                editTaskInput.focus();
+                editTaskInput.select();
+            }
+        }
+
+        // 保存编辑
+        saveEditBtn.addEventListener('click', saveEdit);
+        editTaskInput.addEventListener('keypress', (e) => {
+            if (e.key === 'Enter') saveEdit();
+        });
+
+        function saveEdit() {
+            const newText = editTaskInput.value.trim();
+            if (!newText) return;
+
+            const task = tasks.find(t => t.id === currentEditId);
+            if (task) {
+                task.text = newText;
+                saveTasks();
+                renderTasks();
+                closeEditModal();
+                showNotification('任务已更新');
+            }
+        }
+
+        // 取消编辑
+        cancelEditBtn.addEventListener('click', closeEditModal);
+
+        function closeEditModal() {
+            editModal.style.display = 'none';
+            currentEditId = null;
+        }
+
+        // 点击模态框背景关闭
+        editModal.addEventListener('click', (e) => {
+            if (e.target === editModal) closeEditModal();
+        });
+
+        // 过滤按钮事件
+        filterBtns.forEach(btn => {
+            btn.addEventListener('click', () => {
+                filterBtns.forEach(b => b.classList.remove('active'));
+                btn.classList.add('active');
+                currentFilter = btn.dataset.filter;
+                renderTasks();
+            });
+        });
+
+        // 更新统计
+        function updateStats() {
+            totalTasks.textContent = tasks.length;
+            completedTasks.textContent = tasks.filter(t => t.completed).length;
+        }
+
+        // 保存到localStorage
+        function saveTasks() {
+            localStorage.setItem('tasks', JSON.stringify(tasks));
+        }
+
+        // 工具函数
+        function getPriorityText(priority) {
+            const map = { 'high': '高', 'medium': '中', 'low': '低' };
+            return map[priority] || '中';
+        }
+
+        function formatDate(isoString) {
+            const date = new Date(isoString);
+            const now = new Date();
+            const diff = Math.floor((now - date) / (1000 * 60 * 60 * 24));
+            if (diff === 0) return '今天';
+            if (diff === 1) return '昨天';
+            if (diff < 7) return `${diff}天前`;
+            return date.toLocaleDateString('zh-CN', { month: 'short', day: 'numeric' });
+        }
+
+        function formatDateTimeLocal(date) {
+            const year = date.getFullYear();
+            const month = (date.getMonth() + 1).toString().padStart(2, '0');
+            const day = date.getDate().toString().padStart(2, '0');
+            const hours = date.getHours().toString().padStart(2, '0');
+            const minutes = date.getMinutes().toString().padStart(2, '0');
+            return `${year}-${month}-${day}T${hours}:${minutes}`;
+        }
+
+        // 显示通知
+        function showNotification(message) {
+            // 创建通知元素
+            const notification = document.createElement('div');
+            notification.textContent = message;
+            notification.style.cssText = `
+                position: fixed;
+                bottom: 30px;
+                left: 50%;
+                transform: translateX(-50%);
+                background: #2c3e50;
+                color: white;
+                padding: 12px 25px;
+                border-radius: 50px;
+                box-shadow: 0 5px 15px rgba(0,0,0,0.2);
+                z-index: 2000;
+                animation: fadeIn 0.3s, fadeOut 0.3s 2.5s forwards;
+                font-weight: 500;
+            `;
+
+            // 添加动画样式
+            if (!document.getElementById('notificationStyles')) {
+                const style = document.createElement('style');
+                style.id = 'notificationStyles';
+                style.textContent = `
+                    @keyframes fadeIn {
+                        from { opacity: 0; transform: translate(-50%, 20px); }
+                        to { opacity: 1; transform: translate(-50%, 0); }
+                    }
+                    @keyframes fadeOut {
+                        from { opacity: 1; }
+                        to { opacity: 0; }
+                    }
+                `;
+                document.head.appendChild(style);
+            }
+
+            document.body.appendChild(notification);
+
+            // 2.8秒后移除
+            setTimeout(() => {
+                notification.remove();
+            }, 2800);
+        }
+
+        // 点击页面其他地方关闭模态框
+        window.addEventListener('click', (e) => {
+            if (e.target === editModal) {
+                closeEditModal();
+            }
+        });
+    </script>
+</body>
+</html>
diff --git a/config.example.yaml b/config.example.yaml
new file mode 100644
index 0000000..9e3d028
--- /dev/null
+++ b/config.example.yaml
@@ -0,0 +1,45 @@
+# ================= AI 配置 =================
+ai:
+  # 推荐使用以下任一服务：
+  # 1. Gemini (Google): https://ai.google.dev/
+  # 2. SiliconFlow (硅基流动): https://cloud.siliconflow.cn/
+  # 3. DeepSeek: https://platform.deepseek.com/
+  # 4. Moonshot (月之暗面): https://platform.moonshot.cn/
+  api_key: "sk-xxxxxxxxxxxxxxxxxxxxxxxx"
+  base_url: "https://api.siliconflow.cn/v1"  # 根据服务商修改
+  model: "gemini-2.5-pro"  # 模型名称，根据服务商调整
+  
+  # 重试配置（可选）
+  max_retries: 3  # 最大重试次数
+  retry_delay: 1.0  # 重试延迟（秒）
+
+# ================= 飞书配置 =================
+feishu:
+  # 飞书开放平台 -> 凭证与基础信息
+  app_id: "cli_xxxxxxxxxxxx"
+  app_secret: "xxxxxxxxxxxxxxxxxxxxxxxx"
+
+  # 多维表格的 token (浏览器地址栏中 app 开头的那串字符)
+  app_token: "bascnxxxxxxxxxxxxxxx"
+
+  # 数据表的 ID (在多维表格界面 -> 重命名数据表 -> 复制表ID)
+  table_id: "tblxxxxxxxxxxxx"
+  
+  # 重试配置（可选）
+  max_retries: 3  # 最大重试次数
+  retry_delay: 1.0  # 重试延迟（秒）
+
+# ================= 系统配置 =================
+system:
+  # 监控的文件夹路径 (Windows 路径注意使用双斜杠 \\ 或反斜杠 /)
+  watch_folder: "./monitor_images"
+  
+  # 处理完成后的文件处理方式: "delete" (删除) / "move" (移动) / "keep" (保留)
+  post_process: "move"
+  
+  # 文件移动的目标文件夹 (当 post_process 为 "move" 时生效)
+  processed_folder: "./processed_images"
+  
+  # 日志配置（可选）
+  log_level: "INFO"  # DEBUG, INFO, WARNING, ERROR, CRITICAL
+  log_file: "app.log"  # 日志文件路径，留空则只输出到控制台
\ No newline at end of file
diff --git a/data/test_user_cache.json b/data/test_user_cache.json
new file mode 100644
index 0000000..112f09f
--- /dev/null
+++ b/data/test_user_cache.json
@@ -0,0 +1,5 @@
+{
+  "users": [],
+  "recent_contacts": [],
+  "last_update_time": 1772430132.497222
+}
\ No newline at end of file
diff --git a/data/user_cache.json b/data/user_cache.json
new file mode 100644
index 0000000..ceac180
--- /dev/null
+++ b/data/user_cache.json
@@ -0,0 +1,71 @@
+{
+  "users": [
+    {
+      "user_id": null,
+      "name": null,
+      "email": null,
+      "mobile": null
+    },
+    {
+      "user_id": null,
+      "name": null,
+      "email": null,
+      "mobile": null
+    },
+    {
+      "user_id": null,
+      "name": null,
+      "email": null,
+      "mobile": null
+    },
+    {
+      "user_id": null,
+      "name": null,
+      "email": null,
+      "mobile": null
+    },
+    {
+      "user_id": null,
+      "name": null,
+      "email": null,
+      "mobile": null
+    },
+    {
+      "user_id": null,
+      "name": null,
+      "email": null,
+      "mobile": null
+    },
+    {
+      "user_id": null,
+      "name": null,
+      "email": null,
+      "mobile": null
+    },
+    {
+      "user_id": null,
+      "name": null,
+      "email": null,
+      "mobile": null
+    },
+    {
+      "user_id": null,
+      "name": null,
+      "email": null,
+      "mobile": null
+    },
+    {
+      "user_id": null,
+      "name": null,
+      "email": null,
+      "mobile": null
+    }
+  ],
+  "recent_contacts": [
+    "马老师",
+    "周刘路",
+    "周刘路 (Lucy)",
+    "张睿思"
+  ],
+  "last_update_time": 1773119191.9583383
+}
\ No newline at end of file
diff --git a/main.py b/main.py
new file mode 100644
index 0000000..758af58
--- /dev/null
+++ b/main.py
@@ -0,0 +1,317 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Screen2Feishu - AI飞书多维表格自动录入助手
+监控文件夹，自动处理图片并写入飞书多维表格
+"""
+
+import os
+import sys
+import time
+import argparse
+from pathlib import Path
+from watchdog.observers import Observer
+from watchdog.events import FileSystemEventHandler
+
+# 添加项目根目录到Python路径
+project_root = Path(__file__).parent
+sys.path.insert(0, str(project_root))
+
+from services.ai_service import AIService
+from services.feishu_service import FeishuService
+from utils.logger import setup_logger
+from utils.notifier import send_notification
+from utils.config_loader import load_config, validate_config
+
+
+class ImageFileHandler(FileSystemEventHandler):
+    """文件系统事件处理器"""
+    
+    def __init__(self, config, logger):
+        self.config = config
+        self.logger = logger
+        self.ai_service = AIService(config['ai'])
+        self.feishu_service = FeishuService(config['feishu'])
+        self.processed_files = set()  # 已处理文件记录
+        self.supported_extensions = {'.png', '.jpg', '.jpeg', '.bmp', '.gif'}
+        
+        # 创建必要的文件夹
+        self._create_directories()
+    
+    def _create_directories(self):
+        """创建必要的文件夹"""
+        watch_folder = Path(self.config['system']['watch_folder'])
+        watch_folder.mkdir(exist_ok=True)
+        
+        if self.config['system'].get('post_process') == 'move':
+            processed_folder = Path(self.config['system']['processed_folder'])
+            processed_folder.mkdir(exist_ok=True)
+    
+    def _is_supported_image(self, file_path):
+        """检查文件是否为支持的图片格式"""
+        return Path(file_path).suffix.lower() in self.supported_extensions
+    
+    def _is_file_ready(self, file_path):
+        """检查文件是否已完全写入（通过文件大小稳定判断）"""
+        try:
+            size1 = os.path.getsize(file_path)
+            time.sleep(0.5)  # 等待0.5秒
+            size2 = os.path.getsize(file_path)
+            return size1 == size2 and size1 > 0
+        except (OSError, IOError):
+            return False
+    
+    def _process_image(self, file_path):
+        """处理单个图片文件"""
+        file_path = Path(file_path)
+        
+        # 检查是否已处理
+        if str(file_path) in self.processed_files:
+            return
+        
+        self.logger.info(f"开始处理图片: {file_path.name}")
+        
+        ai_result = None  # 初始化变量
+        
+        try:
+            # 检查是否启用内存处理
+            memory_processing = self.config['system'].get('memory_processing', False)
+            
+            if memory_processing:
+                # 内存处理模式：直接读取图片到内存，不保存到processed_images
+                try:
+                    with open(file_path, 'rb') as f:
+                        image_bytes = f.read()
+                    
+                    # 1. AI分析图片（内存模式）
+                    ai_result = self.ai_service.analyze_image_from_bytes(image_bytes, file_path.name)
+                    if not ai_result:
+                        self.logger.error(f"AI分析失败: {file_path.name}")
+                        return
+                except Exception as e:
+                    self.logger.error(f"内存处理图片失败: {str(e)}")
+                    # 回退到文件处理模式
+                    memory_processing = False
+            
+            if not memory_processing:
+                # 文件处理模式：传统方式
+                # 1. AI分析图片
+                ai_result = self.ai_service.analyze_image(str(file_path))
+                if not ai_result:
+                    self.logger.error(f"AI分析失败: {file_path.name}")
+                    return
+            
+            # 2. 写入飞书
+            success = self.feishu_service.add_task(ai_result)
+            if success:
+                self.logger.info(f"成功写入飞书: {file_path.name}")
+                self.processed_files.add(str(file_path))
+                
+                # 3. 后处理
+                self._post_process_file(file_path)
+                
+                # 4. 发送通知
+                send_notification(
+                    "任务处理成功",
+                    f"已成功处理 {file_path.name} 并写入飞书表格"
+                )
+            else:
+                self.logger.error(f"写入飞书失败: {file_path.name}")
+                
+        except Exception as e:
+            self.logger.error(f"处理图片 {file_path.name} 时出错: {str(e)}")
+    
+    def _post_process_file(self, file_path):
+        """文件后处理"""
+        post_process = self.config['system'].get('post_process', 'keep')
+        
+        if post_process == 'delete':
+            try:
+                file_path.unlink()
+                self.logger.info(f"已删除文件: {file_path.name}")
+            except Exception as e:
+                self.logger.error(f"删除文件失败: {str(e)}")
+        
+        elif post_process == 'move':
+            try:
+                processed_folder = Path(self.config['system']['processed_folder'])
+                target_path = processed_folder / file_path.name
+                
+                # 如果目标文件已存在，添加时间戳
+                if target_path.exists():
+                    timestamp = int(time.time())
+                    target_path = processed_folder / f"{file_path.stem}_{timestamp}{file_path.suffix}"
+                
+                file_path.rename(target_path)
+                self.logger.info(f"已移动文件到: {target_path}")
+            except Exception as e:
+                self.logger.error(f"移动文件失败: {str(e)}")
+    
+    def on_created(self, event):
+        """文件创建事件处理"""
+        if event.is_directory:
+            return
+        
+        file_path = event.src_path
+        if not self._is_supported_image(file_path):
+            return
+        
+        self.logger.info(f"检测到新文件: {file_path}")
+        
+        # 等待文件完全写入
+        if self._is_file_ready(file_path):
+            self._process_image(file_path)
+        else:
+            self.logger.warning(f"文件未完全写入，跳过处理: {file_path}")
+    
+    def on_modified(self, event):
+        """文件修改事件处理"""
+        if event.is_directory:
+            return
+        
+        file_path = event.src_path
+        if not self._is_supported_image(file_path):
+            return
+        
+        # 对于修改事件，也检查文件是否已完全写入
+        if self._is_file_ready(file_path):
+            self._process_image(file_path)
+
+
+def parse_arguments():
+    """解析命令行参数"""
+    parser = argparse.ArgumentParser(
+        description="AI飞书多维表格自动录入助手",
+        formatter_class=argparse.RawDescriptionHelpFormatter,
+        epilog="""
+示例用法:
+  python main.py                    # 使用默认配置启动
+  python main.py --config custom.yaml  # 使用自定义配置文件
+  python main.py --test             # 测试模式（不监控文件夹）
+        """
+    )
+    
+    parser.add_argument(
+        '--config', '-c',
+        default='config.yaml',
+        help='配置文件路径 (默认: config.yaml)'
+    )
+    
+    parser.add_argument(
+        '--test', '-t',
+        action='store_true',
+        help='测试模式：处理现有文件后退出，不监控文件夹'
+    )
+    
+    parser.add_argument(
+        '--verbose', '-v',
+        action='store_true',
+        help='显示详细日志'
+    )
+    
+    return parser.parse_args()
+
+
+def main():
+    """主函数"""
+    args = parse_arguments()
+    
+    # 加载配置
+    try:
+        config = load_config(args.config)
+    except Exception as e:
+        print(f"  配置加载失败: {e}")
+        sys.exit(1)
+    
+    # 验证配置
+    try:
+        validate_config(config)
+    except Exception as e:
+        print(f"  配置验证失败: {e}")
+        sys.exit(1)
+    
+    # 设置日志
+    log_level = 'DEBUG' if args.verbose else 'INFO'
+    logger = setup_logger(
+        name='screen2feishu',
+        log_file='app.log',
+        level=log_level
+    )
+    
+    logger.info("=" * 50)
+    logger.info("Screen2Feishu 启动")
+    logger.info(f"配置文件: {args.config}")
+    logger.info(f"监控文件夹: {config['system']['watch_folder']}")
+    logger.info("=" * 50)
+    
+    # 创建文件处理器
+    handler = ImageFileHandler(config, logger)
+    
+    if args.test:
+        # 测试模式：处理现有文件
+        watch_folder = Path(config['system']['watch_folder'])
+        image_files = [
+            f for f in watch_folder.iterdir()
+            if f.is_file() and handler._is_supported_image(f)
+        ]
+        
+        if not image_files:
+            logger.info("没有找到待处理的图片文件")
+            return
+        
+        logger.info(f"找到 {len(image_files)} 个图片文件，开始处理...")
+        for image_file in image_files:
+            handler._process_image(image_file)
+        
+        logger.info("测试模式处理完成")
+        return
+    
+    # 监控模式
+    observer = Observer()
+    observer.schedule(
+        handler,
+        path=config['system']['watch_folder'],
+        recursive=False
+    )
+    
+    try:
+        observer.start()
+        logger.info("文件监控已启动，按 Ctrl+C 停止程序")
+        
+        # 发送启动通知
+        send_notification(
+            "Screen2Feishu 已启动",
+            f"正在监控文件夹: {config['system']['watch_folder']}"
+        )
+        
+        while True:
+            time.sleep(1)
+            
+    except KeyboardInterrupt:
+        logger.info("收到停止信号，正在关闭...")
+        observer.stop()
+        
+        # 发送停止通知
+        send_notification(
+            "Screen2Feishu 已停止",
+            "程序已正常关闭"
+        )
+    
+    except Exception as e:
+        logger.error(f"程序运行出错: {str(e)}")
+        observer.stop()
+        
+        # 发送错误通知
+        send_notification(
+            "Screen2Feishu 错误",
+            f"程序运行出错: {str(e)}"
+        )
+        sys.exit(1)
+    
+    finally:
+        observer.join()
+        logger.info("程序已完全停止")
+
+
+if __name__ == "__main__":
+    main()
\ No newline at end of file
diff --git a/requirements.txt b/requirements.txt
new file mode 100644
index 0000000..77738c0
--- /dev/null
+++ b/requirements.txt
@@ -0,0 +1,18 @@
+# 核心依赖
+openai>=1.0.0
+watchdog>=3.0.0
+requests>=2.31.0
+pyyaml>=6.0.1
+
+# Web应用依赖
+flask>=2.3.0
+flask-cors>=4.0.0
+
+# 可选依赖
+# pillow>=10.0.0  # 如果需要本地图片处理
+# torch>=2.0.0    # 如果需要GPU加速
+
+# 开发依赖（可选）
+# pytest>=7.0.0   # 用于单元测试
+# black>=23.0.0   # 代码格式化
+# flake8>=6.0.0   # 代码检查
\ No newline at end of file
diff --git a/services/__init__.py b/services/__init__.py
new file mode 100644
index 0000000..56c425f
--- /dev/null
+++ b/services/__init__.py
@@ -0,0 +1,11 @@
+"""
+服务模块
+"""
+
+from .ai_service import AIService
+from .feishu_service import FeishuService
+
+__all__ = [
+    'AIService',
+    'FeishuService'
+]
\ No newline at end of file
diff --git a/services/ai_service.py b/services/ai_service.py
new file mode 100644
index 0000000..fe4c177
--- /dev/null
+++ b/services/ai_service.py
@@ -0,0 +1,624 @@
+import base64
+import json
+import datetime
+import time
+import re
+from typing import Dict, Optional, List
+from openai import OpenAI
+from openai import APIError, RateLimitError, AuthenticationError
+
+
+class AIService:
+    def __init__(self, config):
+        """
+        初始化 AI 服务
+        :param config: 包含 ai 配置的字典 (来自 config.yaml)
+        """
+        self.api_key = config.get('api_key')
+        self.base_url = config.get('base_url')
+        self.model = config.get('model', 'gpt-4o')
+        self.max_retries = config.get('max_retries', 3)
+        self.retry_delay = config.get('retry_delay', 1.0)
+        
+        # 初始化 OpenAI 客户端 (兼容所有支持 OpenAI 格式的 API)
+        self.client = OpenAI(
+            api_key=self.api_key,
+            base_url=self.base_url
+        )
+        
+        # 支持的图片格式
+        self.supported_formats = {'.png', '.jpg', '.jpeg', '.bmp', '.gif'}
+        
+        # Prompt模板缓存
+        self.prompt_templates = {}
+
+    def _encode_image(self, image_path):
+        """将本地图片转换为 Base64 编码"""
+        try:
+            with open(image_path, "rb") as image_file:
+                return base64.b64encode(image_file.read()).decode('utf-8')
+        except Exception as e:
+            raise Exception(f"图片编码失败: {str(e)}")
+    
+    def _encode_image_from_bytes(self, image_bytes: bytes) -> str:
+        """将图片字节数据转换为 Base64 编码"""
+        try:
+            return base64.b64encode(image_bytes).decode('utf-8')
+        except Exception as e:
+            raise Exception(f"图片字节数据编码失败: {str(e)}")
+    
+    def _validate_image_file(self, image_path):
+        """验证图片文件"""
+        from pathlib import Path
+        
+        file_path = Path(image_path)
+        
+        # 检查文件是否存在
+        if not file_path.exists():
+            raise FileNotFoundError(f"图片文件不存在: {image_path}")
+        
+        # 检查文件大小（限制为10MB）
+        file_size = file_path.stat().st_size
+        if file_size > 10 * 1024 * 1024:  # 10MB
+            raise ValueError(f"图片文件过大: {file_size / 1024 / 1024:.2f}MB (最大10MB)")
+        
+        # 检查文件格式
+        if file_path.suffix.lower() not in self.supported_formats:
+            raise ValueError(f"不支持的图片格式: {file_path.suffix}")
+        
+        return True
+    
+    def _build_prompt(self, current_date_str: str) -> str:
+        """构建AI提示词"""
+        prompt = f"""
+        你是一个专业的项目管理助手。当前系统日期是：{current_date_str}。
+        你的任务是从用户上传的图片（可能是聊天记录、邮件、文档截图）中提取任务信息。
+        
+        请严格按照以下 JSON 格式返回结果：
+        {{
+            "task_description": "任务的具体描述，简练概括",
+            "priority": "必须从以下选项中选择一个: ['紧急', '较紧急', '一般', '普通']",
+            "status": "必须从以下选项中选择一个: ['已停滞','待开始', '进行中', '已完成']",
+            "latest_progress": "图片中提到的最新进展，如果没有则留空字符串",
+            "initiator": "任务发起人姓名。请仔细识别图片中的发件人/发送者名字。如果是邮件截图，请识别发件人；如果是聊天记录，请识别发送者。如果没有明确的发起人，则留空字符串。",
+            "department": "发起人部门，如果没有则留空字符串",
+            "start_date": "YYYY-MM-DD 格式的日期字符串。如果提到'今天'就是当前日期，'下周一'请根据当前日期计算。如果没提到则返回 null",
+            "due_date": "YYYY-MM-DD 格式的截止日期字符串。逻辑同上，如果没提到则返回 null"
+        }}
+        
+        注意：
+        1. 如果图片中包含多个任务，请只提取最核心的一个。
+        2. 请特别关注图片中的发件人/发送者信息，准确提取姓名。
+        3. 如果识别到的名字可能存在重名，请在任务描述中添加提示信息。
+        4. 不要返回 Markdown 代码块标记（如 ```json），直接返回纯 JSON 字符串。
+        5. 确保返回的 JSON 格式正确，可以被 Python 的 json.loads() 解析。
+        """
+        return prompt
+    
+    def _parse_ai_response(self, content: Optional[str]) -> Optional[Dict]:
+        """解析AI响应"""
+        if not content:
+            raise ValueError("AI响应内容为空")
+        
+        try:
+            # 清理可能的 markdown 标记
+            content = content.replace("```json", "").replace("```", "").strip()
+            
+            # 尝试修复常见的JSON格式问题
+            # 1. 处理未闭合的引号
+            content = self._fix_json_string(content)
+            
+            # 2. 处理转义字符问题
+            content = self._fix_json_escapes(content)
+            
+            # 解析JSON
+            result_dict = json.loads(content)
+            
+            # 验证必需的字段
+            required_fields = ['task_description', 'priority', 'status']
+            for field in required_fields:
+                if field not in result_dict:
+                    raise ValueError(f"AI响应缺少必需字段: {field}")
+            
+            # 验证选项值
+            valid_priorities = ['紧急', '较紧急', '一般', '普通']
+            valid_statuses = ['已停滞','待开始', '进行中', '已完成']
+            
+            if result_dict.get('priority') not in valid_priorities:
+                raise ValueError(f"无效的优先级: {result_dict.get('priority')}")
+            
+            if result_dict.get('status') not in valid_statuses:
+                raise ValueError(f"无效的状态: {result_dict.get('status')}")
+            
+            return result_dict
+            
+        except json.JSONDecodeError as e:
+            # 尝试更详细的错误修复
+            try:
+                # 如果标准解析失败，尝试使用更宽松的解析
+                content = self._aggressive_json_fix(content)
+                result_dict = json.loads(content)
+                
+                # 重新验证字段
+                required_fields = ['task_description', 'priority', 'status']
+                for field in required_fields:
+                    if field not in result_dict:
+                        raise ValueError(f"AI响应缺少必需字段: {field}")
+                
+                # 重新验证选项值
+                valid_priorities = ['紧急', '较紧急', '一般', '普通']
+                valid_statuses = ['已停滞','待开始', '进行中', '已完成']
+                
+                if result_dict.get('priority') not in valid_priorities:
+                    raise ValueError(f"无效的优先级: {result_dict.get('priority')}")
+                
+                if result_dict.get('status') not in valid_statuses:
+                    raise ValueError(f"无效的状态: {result_dict.get('status')}")
+                
+                return result_dict
+            except Exception as retry_error:
+                raise ValueError(f"AI响应不是有效的JSON: {str(e)} (修复后错误: {str(retry_error)})")
+        except Exception as e:
+            raise ValueError(f"解析AI响应失败: {str(e)}")
+    
+    def _fix_json_string(self, content: str) -> str:
+        """修复JSON字符串中的未闭合引号问题"""
+        import re
+        
+        # 查找可能未闭合的字符串
+        # 匹配模式：从引号开始，但没有对应的闭合引号
+        lines = content.split('\n')
+        fixed_lines = []
+        
+        for line in lines:
+            # 检查行中是否有未闭合的引号
+            in_string = False
+            escaped = False
+            fixed_line = []
+            
+            for char in line:
+                if escaped:
+                    fixed_line.append(char)
+                    escaped = False
+                    continue
+                
+                if char == '\\':
+                    escaped = True
+                    fixed_line.append(char)
+                    continue
+                
+                if char == '"':
+                    if in_string:
+                        in_string = False
+                    else:
+                        in_string = True
+                    fixed_line.append(char)
+                else:
+                    fixed_line.append(char)
+            
+            # 如果行结束时仍在字符串中，添加闭合引号
+            if in_string:
+                fixed_line.append('"')
+            
+            fixed_lines.append(''.join(fixed_line))
+        
+        return '\n'.join(fixed_lines)
+    
+    def _fix_json_escapes(self, content: str) -> str:
+        """修复JSON转义字符问题"""
+        # 注意：我们不应该转义JSON结构中的引号，只转义字符串内容中的引号
+        # 这个函数暂时不处理换行符，因为JSON中的换行符是有效的
+        # 更复杂的转义修复应该在JSON解析后进行
+        
+        return content
+    
+    def _aggressive_json_fix(self, content: str) -> str:
+        """更激进的JSON修复策略"""
+        # 1. 移除可能的非JSON内容
+        content = re.sub(r'^[^{]*', '', content)  # 移除JSON前的非JSON内容
+        content = re.sub(r'[^}]*$', '', content)  # 移除JSON后的非JSON内容
+        
+        # 2. 确保JSON对象闭合
+        if not content.strip().endswith('}'):
+            content = content.strip() + '}'
+        
+        # 3. 确保JSON对象开始
+        if not content.strip().startswith('{'):
+            content = '{' + content.strip()
+        
+        # 4. 处理常见的AI响应格式问题
+        # 移除可能的Markdown代码块标记
+        content = content.replace('```json', '').replace('```', '')
+        
+        # 5. 处理可能的多余空格和换行
+        content = ' '.join(content.split())
+        
+        return content
+    
+    def _call_ai_with_retry(self, image_path: str, prompt: str) -> Optional[str]:
+        """调用AI API，带重试机制"""
+        base64_image = self._encode_image(image_path)
+        
+        for attempt in range(self.max_retries):
+            try:
+                # 尝试使用response_format参数（适用于OpenAI格式的API）
+                try:
+                    response = self.client.chat.completions.create(
+                        model=self.model,
+                        messages=[
+                            {
+                                "role": "user",
+                                "content": [
+                                    {"type": "text", "text": prompt},
+                                    {
+                                        "type": "image_url",
+                                        "image_url": {
+                                            "url": f"data:image/jpeg;base64,{base64_image}"
+                                        }
+                                    }
+                                ]
+                            }
+                        ],
+                        response_format={"type": "json_object"},
+                        max_tokens=2000
+                    )
+                except Exception as e:
+                    # 如果response_format参数不支持，尝试不使用该参数
+                    print(f"⚠️  response_format参数不支持，尝试不使用该参数: {str(e)}")
+                    response = self.client.chat.completions.create(
+                        model=self.model,
+                        messages=[
+                            {
+                                "role": "user",
+                                "content": [
+                                    {"type": "text", "text": prompt},
+                                    {
+                                        "type": "image_url",
+                                        "image_url": {
+                                            "url": f"data:image/jpeg;base64,{base64_image}"
+                                        }
+                                    }
+                                ]
+                            }
+                        ],
+                        max_tokens=2000
+                    )
+                
+                if not response.choices:
+                    return None
+                
+                content = response.choices[0].message.content
+                return content if content else None
+                
+            except RateLimitError as e:
+                if attempt < self.max_retries - 1:
+                    wait_time = self.retry_delay * (2 ** attempt)  # 指数退避
+                    time.sleep(wait_time)
+                    continue
+                raise Exception(f"API速率限制: {str(e)}")
+                
+            except AuthenticationError as e:
+                raise Exception(f"API认证失败: {str(e)}")
+                
+            except APIError as e:
+                if attempt < self.max_retries - 1:
+                    wait_time = self.retry_delay * (2 ** attempt)
+                    time.sleep(wait_time)
+                    continue
+                raise Exception(f"API调用失败: {str(e)}")
+                
+            except Exception as e:
+                if attempt < self.max_retries - 1:
+                    wait_time = self.retry_delay * (2 ** attempt)
+                    time.sleep(wait_time)
+                    continue
+                raise Exception(f"未知错误: {str(e)}")
+        
+        raise Exception(f"AI调用失败，已重试 {self.max_retries} 次")
+    
+    def _call_ai_with_retry_from_bytes(self, image_bytes: bytes, prompt: str, image_name: str = "memory_image") -> Optional[str]:
+        """调用AI API，带重试机制（从内存字节数据）"""
+        base64_image = self._encode_image_from_bytes(image_bytes)
+        
+        for attempt in range(self.max_retries):
+            try:
+                # 尝试使用response_format参数（适用于OpenAI格式的API）
+                try:
+                    response = self.client.chat.completions.create(
+                        model=self.model,
+                        messages=[
+                            {
+                                "role": "user",
+                                "content": [
+                                    {"type": "text", "text": prompt},
+                                    {
+                                        "type": "image_url",
+                                        "image_url": {
+                                            "url": f"data:image/jpeg;base64,{base64_image}"
+                                        }
+                                    }
+                                ]
+                            }
+                        ],
+                        response_format={"type": "json_object"},
+                        max_tokens=2000
+                    )
+                except Exception as e:
+                    # 如果response_format参数不支持，尝试不使用该参数
+                    print(f"⚠️  response_format参数不支持，尝试不使用该参数: {str(e)}")
+                    response = self.client.chat.completions.create(
+                        model=self.model,
+                        messages=[
+                            {
+                                "role": "user",
+                                "content": [
+                                    {"type": "text", "text": prompt},
+                                    {
+                                        "type": "image_url",
+                                        "image_url": {
+                                            "url": f"data:image/jpeg;base64,{base64_image}"
+                                        }
+                                    }
+                                ]
+                            }
+                        ],
+                        max_tokens=2000
+                    )
+                
+                if not response.choices:
+                    return None
+                
+                content = response.choices[0].message.content
+                return content if content else None
+                
+            except RateLimitError as e:
+                if attempt < self.max_retries - 1:
+                    wait_time = self.retry_delay * (2 ** attempt)  # 指数退避
+                    time.sleep(wait_time)
+                    continue
+                raise Exception(f"API速率限制: {str(e)}")
+                
+            except AuthenticationError as e:
+                raise Exception(f"API认证失败: {str(e)}")
+                
+            except APIError as e:
+                if attempt < self.max_retries - 1:
+                    wait_time = self.retry_delay * (2 ** attempt)
+                    time.sleep(wait_time)
+                    continue
+                raise Exception(f"API调用失败: {str(e)}")
+                
+            except Exception as e:
+                if attempt < self.max_retries - 1:
+                    wait_time = self.retry_delay * (2 ** attempt)
+                    time.sleep(wait_time)
+                    continue
+                raise Exception(f"未知错误: {str(e)}")
+        
+        raise Exception(f"AI调用失败，已重试 {self.max_retries} 次")
+        
+        for attempt in range(self.max_retries):
+            try:
+                # 尝试使用response_format参数（适用于OpenAI格式的API）
+                try:
+                    response = self.client.chat.completions.create(
+                        model=self.model,
+                        messages=[
+                            {
+                                "role": "user",
+                                "content": [
+                                    {"type": "text", "text": prompt},
+                                    {
+                                        "type": "image_url",
+                                        "image_url": {
+                                            "url": f"data:image/jpeg;base64,{base64_image}"
+                                        }
+                                    }
+                                ]
+                            }
+                        ],
+                        response_format={"type": "json_object"},
+                        max_tokens=2000
+                    )
+                except Exception as e:
+                    # 如果response_format参数不支持，尝试不使用该参数
+                    print(f"⚠️  response_format参数不支持，尝试不使用该参数: {str(e)}")
+                    response = self.client.chat.completions.create(
+                        model=self.model,
+                        messages=[
+                            {
+                                "role": "user",
+                                "content": [
+                                    {"type": "text", "text": prompt},
+                                    {
+                                        "type": "image_url",
+                                        "image_url": {
+                                            "url": f"data:image/jpeg;base64,{base64_image}"
+                                        }
+                                    }
+                                ]
+                            }
+                        ],
+                        max_tokens=2000
+                    )
+                
+                if not response.choices:
+                    return None
+                
+                content = response.choices[0].message.content
+                return content if content else None
+                
+            except RateLimitError as e:
+                if attempt < self.max_retries - 1:
+                    wait_time = self.retry_delay * (2 ** attempt)  # 指数退避
+                    time.sleep(wait_time)
+                    continue
+                raise Exception(f"API速率限制: {str(e)}")
+                
+            except AuthenticationError as e:
+                raise Exception(f"API认证失败: {str(e)}")
+                
+            except APIError as e:
+                if attempt < self.max_retries - 1:
+                    wait_time = self.retry_delay * (2 ** attempt)
+                    time.sleep(wait_time)
+                    continue
+                raise Exception(f"API调用失败: {str(e)}")
+                
+            except Exception as e:
+                if attempt < self.max_retries - 1:
+                    wait_time = self.retry_delay * (2 ** attempt)
+                    time.sleep(wait_time)
+                    continue
+                raise Exception(f"未知错误: {str(e)}")
+        
+        raise Exception(f"AI调用失败，已重试 {self.max_retries} 次")
+
+    def analyze_image(self, image_path):
+        """
+        核心方法：发送图片到 AI 并获取结构化数据
+        :param image_path: 图片文件的路径
+        :return: 解析后的字典 (Dict)
+        """
+        from pathlib import Path
+        
+        file_path = Path(image_path)
+        # 使用sys.stdout.write替代print，避免编码问题
+        import sys
+        sys.stdout.write(f"  [AI] 正在分析图片: {file_path.name} ...\n")
+        sys.stdout.flush()
+        
+        try:
+            # 1. 验证图片文件
+            self._validate_image_file(image_path)
+            
+            # 2. 获取当前日期 (用于辅助 AI 推断相对时间)
+            now = datetime.datetime.now()
+            current_date_str = now.strftime("%Y-%m-%d %A") # 例如: 2023-10-27 Sunday
+            
+            # 3. 构建 Prompt
+            prompt = self._build_prompt(current_date_str)
+            
+            # 4. 调用AI API（带重试机制）
+            content = self._call_ai_with_retry(image_path, prompt)
+            
+            # 5. 解析结果
+            if not content:
+                import sys
+                sys.stdout.write(f"  [AI] AI返回空内容\n")
+                sys.stdout.flush()
+                return None
+            
+            result_dict = self._parse_ai_response(content)
+            
+            # 记录成功日志
+            if result_dict:
+                task_desc = result_dict.get('task_description', '')
+                if task_desc and len(task_desc) > 30:
+                    task_desc = task_desc[:30] + "..."
+                import sys
+                sys.stdout.write(f"  [AI] 识别成功: {task_desc}\n")
+                sys.stdout.flush()
+            
+            return result_dict
+            
+        except Exception as e:
+            import sys
+            sys.stdout.write(f"  [AI] 分析失败: {str(e)}\n")
+            sys.stdout.flush()
+            return None
+    
+    def analyze_image_from_bytes(self, image_bytes: bytes, image_name: str = "memory_image"):
+        """
+        核心方法：从内存中的图片字节数据发送到 AI 并获取结构化数据
+        :param image_bytes: 图片的字节数据
+        :param image_name: 图片名称（用于日志）
+        :return: 解析后的字典 (Dict)
+        """
+        # 使用sys.stdout.write替代print，避免编码问题
+        import sys
+        sys.stdout.write(f"  [AI] 正在分析内存图片: {image_name} ...\n")
+        sys.stdout.flush()
+        
+        try:
+            # 1. 验证图片数据大小
+            if len(image_bytes) > 10 * 1024 * 1024:  # 10MB
+                raise ValueError(f"图片数据过大: {len(image_bytes) / 1024 / 1024:.2f}MB (最大10MB)")
+            
+            # 2. 获取当前日期 (用于辅助 AI 推断相对时间)
+            now = datetime.datetime.now()
+            current_date_str = now.strftime("%Y-%m-%d %A") # 例如: 2023-10-27 Sunday
+            
+            # 3. 构建 Prompt
+            prompt = self._build_prompt(current_date_str)
+            
+            # 4. 调用AI API（带重试机制）
+            content = self._call_ai_with_retry_from_bytes(image_bytes, prompt, image_name)
+            
+            # 5. 解析结果
+            if not content:
+                import sys
+                sys.stdout.write(f"  [AI] AI返回空内容\n")
+                sys.stdout.flush()
+                return None
+            
+            result_dict = self._parse_ai_response(content)
+            
+            # 记录成功日志
+            if result_dict:
+                task_desc = result_dict.get('task_description', '')
+                if task_desc and len(task_desc) > 30:
+                    task_desc = task_desc[:30] + "..."
+                import sys
+                sys.stdout.write(f"  [AI] 识别成功: {task_desc}\n")
+                sys.stdout.flush()
+            
+            return result_dict
+            
+        except Exception as e:
+            import sys
+            sys.stdout.write(f"  [AI] 分析失败: {str(e)}\n")
+            sys.stdout.flush()
+            return None
+    
+    def analyze_image_batch(self, image_paths: List[str]) -> Dict[str, Optional[Dict]]:
+        """
+        批量分析图片
+        :param image_paths: 图片文件路径列表
+        :return: 字典，键为图片路径，值为分析结果
+        """
+        results = {}
+        
+        for image_path in image_paths:
+            try:
+                result = self.analyze_image(image_path)
+                results[image_path] = result
+            except Exception as e:
+                import sys
+                sys.stdout.write(f"  [AI] 批量处理失败 {image_path}: {str(e)}\n")
+                sys.stdout.flush()
+                results[image_path] = None
+        
+        return results
+
+# ================= 单元测试 =================
+if __name__ == "__main__":
+    # 在这里填入你的配置进行测试
+    test_config = {
+        "api_key": "sk-xxxxxxxxxxxxxxxxxxxxxxxx", 
+        "base_url": "https://api.openai.com/v1",
+        "model": "gpt-4o"
+    }
+    
+    # 确保目录下有一张名为 test_img.jpg 的图片
+    import os
+    if os.path.exists("test_img.jpg"):
+        ai = AIService(test_config)
+        res = ai.analyze_image("test_img.jpg")
+        import sys
+        sys.stdout.write(json.dumps(res, indent=2, ensure_ascii=False) + "\n")
+        sys.stdout.flush()
+    else:
+        import sys
+        sys.stdout.write("请在同级目录下放一张 test_img.jpg 用于测试\n")
+        sys.stdout.flush()
\ No newline at end of file
diff --git a/services/feishu_service.py b/services/feishu_service.py
new file mode 100644
index 0000000..5953a33
--- /dev/null
+++ b/services/feishu_service.py
@@ -0,0 +1,489 @@
+import requests
+import json
+import time
+import logging
+from datetime import datetime
+from typing import Dict, Optional, List
+from pathlib import Path
+from utils.user_cache import UserCacheManager
+
+
+class FeishuService:
+    def __init__(self, config):
+        """
+        初始化飞书服务
+        :param config: 包含飞书配置的字典 (来自 config.yaml)
+        """
+        self.app_id = config.get('app_id')
+        self.app_secret = config.get('app_secret')
+        self.app_token = config.get('app_token')  # 多维表格的 Base Token
+        self.table_id = config.get('table_id')    # 数据表 ID
+        
+        # 内部变量，用于缓存 Token
+        self._tenant_access_token = None
+        self._token_expire_time = 0
+        
+        # 重试配置
+        self.max_retries = config.get('max_retries', 3)
+        self.retry_delay = config.get('retry_delay', 1.0)
+        
+        # 用户匹配配置
+        user_matching_config = config.get('user_matching', {})
+        self.user_matching_enabled = user_matching_config.get('enabled', True)
+        self.fallback_to_random = user_matching_config.get('fallback_to_random', True)
+        self.cache_enabled = user_matching_config.get('cache_enabled', True)
+        self.cache_file = user_matching_config.get('cache_file', './data/user_cache.json')
+        
+        # 用户缓存管理器
+        self.user_cache = UserCacheManager(self.cache_file) if self.cache_enabled else None
+        
+        # 支持的字段类型映射
+        self.field_type_map = {
+            'text': 'text',
+            'number': 'number',
+            'date': 'date',
+            'select': 'single_select',
+            'multi_select': 'multiple_select',
+            'checkbox': 'checkbox',
+            'url': 'url',
+            'email': 'email',
+            'phone': 'phone',
+            'user': 'user'  # 用户字段类型
+        }
+        
+        # 验证必需的配置
+        self._validate_config()
+    
+    def _validate_config(self):
+        """验证飞书配置"""
+        if not self.app_id:
+            raise ValueError("飞书配置缺少 app_id")
+        if not self.app_secret:
+            raise ValueError("飞书配置缺少 app_secret")
+        if not self.app_token:
+            raise ValueError("飞书配置缺少 app_token")
+        if not self.table_id:
+            raise ValueError("飞书配置缺少 table_id")
+        
+        # 验证用户匹配配置
+        if self.user_matching_enabled and not self.cache_enabled:
+            logging.warning("用户匹配已启用但缓存未启用，可能影响性能")
+
+    def _get_token(self, retry_count: int = 0) -> Optional[str]:
+        """
+        获取 tenant_access_token (带缓存机制和重试)
+        如果 Token 还有效，直接返回；否则重新请求。
+        """
+        now = time.time()
+        # 如果 token 存在且离过期还有60秒以上，直接复用
+        if self._tenant_access_token and now < self._token_expire_time - 60:
+            return self._tenant_access_token
+
+        url = "https://open.feishu.cn/open-apis/auth/v3/tenant_access_token/internal"
+        headers = {"Content-Type": "application/json; charset=utf-8"}
+        payload = {
+            "app_id": self.app_id,
+            "app_secret": self.app_secret
+        }
+
+        try:
+            resp = requests.post(url, headers=headers, json=payload, timeout=10)
+            resp_data = resp.json()
+            
+            if resp_data.get("code") == 0:
+                self._tenant_access_token = resp_data.get("tenant_access_token")
+                # expire_in 通常是 7200 秒，我们记录下过期的绝对时间戳
+                self._token_expire_time = now + resp_data.get("expire", 7200)
+                logging.info("🔄 [Feishu] Token 已刷新")
+                return self._tenant_access_token
+            else:
+                error_msg = resp_data.get("msg", "未知错误")
+                raise Exception(f"获取飞书 Token 失败: {error_msg}")
+                
+        except requests.exceptions.RequestException as e:
+            if retry_count < self.max_retries:
+                wait_time = self.retry_delay * (2 ** retry_count)
+                logging.warning(f"网络错误，{wait_time}秒后重试: {str(e)}")
+                time.sleep(wait_time)
+                return self._get_token(retry_count + 1)
+            logging.error(f"  [Feishu] 网络错误，已重试 {self.max_retries} 次: {str(e)}")
+            return None
+        except Exception as e:
+            logging.error(f"  [Feishu] 认证错误: {str(e)}")
+            return None
+
+    def _date_to_timestamp(self, date_str: str) -> Optional[int]:
+        """
+        将 YYYY-MM-DD 字符串转换为飞书需要的毫秒级时间戳
+        """
+        if not date_str or date_str == "null":
+            return None
+        try:
+            # 假设 AI 返回的是 YYYY-MM-DD
+            dt = datetime.strptime(date_str, "%Y-%m-%d")
+            # 转换为毫秒时间戳
+            return int(dt.timestamp() * 1000)
+        except ValueError:
+            logging.warning(f"⚠️ [Feishu] 日期格式无法解析: {date_str}，将留空。")
+            return None
+    
+    def _validate_ai_data(self, ai_data: Dict) -> bool:
+        """验证AI返回的数据"""
+        required_fields = ['task_description', 'priority', 'status']
+        
+        for field in required_fields:
+            if field not in ai_data:
+                logging.error(f"  [Feishu] AI数据缺少必需字段: {field}")
+                return False
+        
+        # 验证选项值
+        valid_priorities = ['紧急', '较紧急', '一般', '普通']
+        valid_statuses =  [' 已停滞', '待开始', '进行中', '，已完成']
+        
+        if ai_data.get('priority') not in valid_priorities:
+            logging.error(f"  [Feishu] 无效的优先级: {ai_data.get('priority')}")
+            return False
+        
+        if ai_data.get('status') not in valid_statuses:
+            logging.error(f"  [Feishu] 无效的状态: {ai_data.get('status')}")
+            return False
+        
+        return True
+    
+    def _build_fields(self, ai_data: Dict) -> Dict:
+        """构建飞书字段数据"""
+        # --- 字段映射区域 (Key 必须与飞书表格列名完全一致) ---
+        fields = {
+            "任务描述": ai_data.get("task_description", ""),
+            "重要紧急程度": ai_data.get("priority", "普通"),  # 默认值防止报错
+            "进展": ai_data.get("status", "待开始"),
+            "最新进展记录": ai_data.get("latest_progress", "进行中，请及时更新"),
+            # 任务发起方.部门是多选字段，需要列表格式
+            "任务发起方.部门": self._build_multi_select_field(ai_data.get("department", ""))  # 修复字段名：添加点号
+        }
+        
+        # 处理任务发起方
+        initiator_name = ai_data.get("initiator", "")
+        if initiator_name and self.user_matching_enabled:
+            # 尝试匹配用户
+            user_match = self._match_initiator(initiator_name)
+            if user_match:
+                if user_match.get('matched'):
+                    # 成功匹配到用户ID
+                    fields["任务发起方"] = self._build_user_field(user_match['user_id'])
+                    logging.info(f"成功匹配任务发起方: {initiator_name} -> {user_match['user_name']}")
+                else:
+                    # 未匹配到用户，添加待确认标记到任务描述
+                    fields["任务描述"] = f"[待确认发起人] {fields['任务描述']}"
+                    # 在任务发起方.部门字段中添加待确认信息（作为提示）
+                    existing_dept = ai_data.get("department", "")
+                    if existing_dept:
+                        fields["任务发起方.部门"] = self._build_multi_select_field(f"{existing_dept} (待确认: {initiator_name})")
+                    else:
+                        fields["任务发起方.部门"] = self._build_multi_select_field(f"待确认: {initiator_name}")
+                    logging.warning(f"未匹配到用户: {initiator_name}，标记为待确认")
+                    
+                    # 添加到最近联系人
+                    if self.user_cache:
+                        self.user_cache.add_recent_contact(initiator_name)
+            else:
+                # 匹配失败，使用随机选择或留空
+                if self.fallback_to_random and self.user_cache:
+                    random_contact = self.user_cache.get_random_recent_contact()
+                    if random_contact:
+                        fields["任务描述"] = f"[随机匹配] {fields['任务描述']}"
+                        # 在任务发起方.部门字段中添加随机匹配信息
+                        existing_dept = ai_data.get("department", "")
+                        if existing_dept:
+                            fields["任务发起方.部门"] = self._build_multi_select_field(f"{existing_dept} (随机: {random_contact})")
+                        else:
+                            fields["任务发起方.部门"] = self._build_multi_select_field(f"随机: {random_contact}")
+                        logging.info(f"随机匹配任务发起方: {random_contact}")
+                    else:
+                        fields["任务描述"] = f"[待确认发起人] {fields['任务描述']}"
+                        # 在任务发起方.部门字段中添加待确认信息
+                        existing_dept = ai_data.get("department", "")
+                        if existing_dept:
+                            fields["任务发起方.部门"] = self._build_multi_select_field(f"{existing_dept} (待确认: {initiator_name})")
+                        else:
+                            fields["任务发起方.部门"] = self._build_multi_select_field(f"待确认: {initiator_name}")
+                        logging.warning(f"无最近联系人可用，标记为待确认: {initiator_name}")
+                else:
+                    fields["任务描述"] = f"[待确认发起人] {fields['任务描述']}"
+                    # 在任务发起方.部门字段中添加待确认信息
+                    existing_dept = ai_data.get("department", "")
+                    if existing_dept:
+                        fields["任务发起方.部门"] = self._build_multi_select_field(f"{existing_dept} (待确认: {initiator_name})")
+                    else:
+                        fields["任务发起方.部门"] = self._build_multi_select_field(f"待确认: {initiator_name}")
+                    logging.warning(f"未匹配到用户且未启用随机匹配: {initiator_name}")
+        elif initiator_name:
+            # 用户匹配未启用，直接使用名字
+            # 在任务发起方.部门字段中添加发起人信息
+            existing_dept = ai_data.get("department", "")
+            if existing_dept:
+                fields["任务发起方.部门"] = self._build_multi_select_field(f"{existing_dept} (发起人: {initiator_name})")
+            else:
+                fields["任务发起方.部门"] = self._build_multi_select_field(f"发起人: {initiator_name}")
+        
+        # 移除用户字段，避免UserFieldConvFail错误（如果匹配失败）
+        if "任务发起方" not in fields:
+            fields.pop("任务发起方", None)
+        
+        # 处理日期字段 (AI 返回的是字符串，飞书写入最好用时间戳)
+        start_date = ai_data.get("start_date")
+        if start_date and isinstance(start_date, str):
+            start_ts = self._date_to_timestamp(start_date)
+            if start_ts:
+                fields["开始日期"] = start_ts
+            
+        due_date = ai_data.get("due_date")
+        if due_date and isinstance(due_date, str):
+            due_ts = self._date_to_timestamp(due_date)
+            if due_ts:
+                fields["预计完成日期"] = due_ts
+        
+        return fields
+    
+    def _build_multi_select_field(self, value: str) -> Optional[List]:
+        """构建飞书多选字段"""
+        if not value:
+            return None
+        
+        # 多选字段需要以列表格式提供
+        # 格式：["选项1", "选项2"]
+        return [value]
+    
+    def _call_feishu_api(self, url: str, headers: Dict, payload: Dict, retry_count: int = 0) -> Optional[Dict]:
+        """调用飞书API，带重试机制"""
+        try:
+            response = requests.post(url, headers=headers, json=payload, timeout=30)
+            res_json = response.json()
+            
+            if res_json.get("code") == 0:
+                return res_json
+            else:
+                error_msg = res_json.get("msg", "未知错误")
+                error_code = res_json.get("code", "未知错误码")
+                raise Exception(f"飞书API错误 {error_code}: {error_msg}")
+                
+        except requests.exceptions.RequestException as e:
+            if retry_count < self.max_retries:
+                wait_time = self.retry_delay * (2 ** retry_count)
+                logging.warning(f"网络错误，{wait_time}秒后重试: {str(e)}")
+                time.sleep(wait_time)
+                return self._call_feishu_api(url, headers, payload, retry_count + 1)
+            logging.error(f"  [Feishu] 网络错误，已重试 {self.max_retries} 次: {str(e)}")
+            return None
+        except Exception as e:
+            logging.error(f"  [Feishu] API调用失败: {str(e)}")
+            return None
+
+    def add_task(self, ai_data: Optional[Dict]) -> bool:
+        """
+        将 AI 识别的数据写入多维表格
+        :param ai_data: AI 返回的 JSON 字典
+        :return: 是否成功
+        """
+        # 验证AI数据
+        if not ai_data or not self._validate_ai_data(ai_data):
+            return False
+        
+        token = self._get_token()
+        if not token:
+            logging.error("  [Feishu] 无法获取 Token，跳过写入。")
+            return False
+
+        url = f"https://open.feishu.cn/open-apis/bitable/v1/apps/{self.app_token}/tables/{self.table_id}/records"
+        headers = {
+            "Authorization": f"Bearer {token}",
+            "Content-Type": "application/json; charset=utf-8"
+        }
+
+        # 构建字段数据
+        fields = self._build_fields(ai_data)
+        payload = {"fields": fields}
+
+        # 调用API
+        res_json = self._call_feishu_api(url, headers, payload)
+        
+        if res_json and res_json.get("code") == 0:
+            record_id = res_json['data']['record']['record_id']
+            logging.info(f"  [Feishu] 成功写入一条记录！(Record ID: {record_id})")
+            return True
+        else:
+            logging.error(f"  [Feishu] 写入失败: {json.dumps(res_json, ensure_ascii=False) if res_json else '无响应'}")
+            return False
+    
+    def add_task_batch(self, ai_data_list: List[Dict]) -> Dict[str, bool]:
+        """
+        批量写入任务到飞书
+        :param ai_data_list: AI数据列表
+        :return: 字典，键为数据索引，值为是否成功
+        """
+        results = {}
+        
+        for index, ai_data in enumerate(ai_data_list):
+            try:
+                success = self.add_task(ai_data)
+                results[str(index)] = success
+            except Exception as e:
+                logging.error(f"  [Feishu] 批量写入失败 (索引 {index}): {str(e)}")
+                results[str(index)] = False
+        
+        return results
+    
+    def _match_initiator(self, initiator_name: str) -> Optional[Dict]:
+        """
+        匹配任务发起人
+        
+        Args:
+            initiator_name: AI识别的发起人名字
+            
+        Returns:
+            匹配结果字典，包含matched, user_id, user_name等字段
+        """
+        if not initiator_name or not self.user_matching_enabled:
+            return None
+        
+        # 确保用户缓存已初始化
+        if not self.user_cache:
+            return None
+        
+        # 检查缓存是否过期，如果过期则重新获取用户列表
+        if self.user_cache.is_cache_expired(max_age_hours=24):
+            logging.info("用户缓存已过期，重新获取用户列表")
+            users = self._get_user_list()
+            if users:
+                self.user_cache.update_users(users)
+        
+        # 尝试匹配用户
+        matched_user = self.user_cache.match_user_by_name(initiator_name)
+        
+        if matched_user:
+            return {
+                'matched': True,
+                'user_id': matched_user.get('user_id'),
+                'user_name': matched_user.get('name')
+            }
+        else:
+            return {
+                'matched': False,
+                'user_name': initiator_name
+            }
+    
+    def _get_user_list(self) -> Optional[List[Dict]]:
+        """
+        从飞书API获取用户列表
+        
+        Returns:
+            用户列表，每个用户包含 name, user_id 等字段
+        """
+        token = self._get_token()
+        if not token:
+            logging.error("  [Feishu] 无法获取 Token，跳过用户列表获取。")
+            return None
+        
+        url = "https://open.feishu.cn/open-apis/contact/v3/users"
+        headers = {
+            "Authorization": f"Bearer {token}",
+            "Content-Type": "application/json; charset=utf-8"
+        }
+        
+        try:
+            # 分页获取用户列表
+            all_users = []
+            page_token = None
+            
+            while True:
+                params = {"page_size": 100}
+                if page_token:
+                    params["page_token"] = page_token
+                
+                response = requests.get(url, headers=headers, params=params, timeout=30)
+                res_json = response.json()
+                
+                if res_json.get("code") == 0:
+                    users = res_json.get("data", {}).get("items", [])
+                    for user in users:
+                        # 提取用户信息
+                        user_info = {
+                            'user_id': user.get('user_id'),
+                            'name': user.get('name'),
+                            'email': user.get('email'),
+                            'mobile': user.get('mobile')
+                        }
+                        all_users.append(user_info)
+                    
+                    # 检查是否有更多页面
+                    page_token = res_json.get("data", {}).get("page_token")
+                    if not page_token:
+                        break
+                else:
+                    error_msg = res_json.get("msg", "未知错误")
+                    logging.error(f"获取用户列表失败: {error_msg}")
+                    break
+            
+            logging.info(f"成功获取 {len(all_users)} 个用户")
+            return all_users
+            
+        except Exception as e:
+            logging.error(f"获取用户列表时出错: {str(e)}")
+            return None
+    
+    def _build_user_field(self, user_id: str) -> Optional[Dict]:
+        """
+        构建飞书用户字段
+        
+        Args:
+            user_id: 用户ID
+            
+        Returns:
+            用户字段字典
+        """
+        if not user_id:
+            return None
+        
+        return {
+            "id": user_id
+        }
+
+# ================= 单元测试代码 =================
+if __name__ == "__main__":
+    # 设置日志
+    logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
+    
+    # 如果你直接运行这个文件，会执行下面的测试代码
+    # 这里填入真实的配置进行测试
+    test_config = {
+        "app_id": "cli_xxxxxxxxxxxx",     # 换成你的 App ID
+        "app_secret": "xxxxxxxxxxxxxx",   # 换成你的 App Secret
+        "app_token": "basxxxxxxxxxxxxx",  # 换成你的 Base Token
+        "table_id": "tblxxxxxxxxxxxxx"    # 换成你的 Table ID
+    }
+    
+    # 模拟 AI 返回的数据
+    mock_ai_data = {
+        "task_description": "测试任务：编写 Feishu Service 模块",
+        "priority": "普通",  # 确保飞书表格里有这个选项
+        "status": "进行中",      # 确保飞书表格里有这个选项
+        "latest_progress": "代码框架已完成，正在调试 API",
+        "initiator": "Python脚本",
+        "department": "研发部",
+        "start_date": "2023-10-27",
+        "due_date": "2023-10-30"
+    }
+    
+    try:
+        fs = FeishuService(test_config)
+        success = fs.add_task(mock_ai_data)
+        import sys
+        if success:
+            sys.stdout.write("测试成功！\n")
+        else:
+            sys.stdout.write("测试失败！\n")
+        sys.stdout.flush()
+    except Exception as e:
+        import sys
+        sys.stdout.write(f"测试出错: {str(e)}\n")
+        sys.stdout.flush()
\ No newline at end of file
diff --git a/setup.py b/setup.py
new file mode 100644
index 0000000..d15ff0e
--- /dev/null
+++ b/setup.py
@@ -0,0 +1,193 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Screen2Feishu 安装和设置脚本
+"""
+
+import os
+import sys
+import subprocess
+import shutil
+from pathlib import Path
+
+
+def print_header(text):
+    """打印标题"""
+    print("\n" + "=" * 60)
+    print(f"  {text}")
+    print("=" * 60)
+
+
+def print_step(text):
+    """打印步骤"""
+    print(f"\n▶ {text}")
+
+
+def check_python_version():
+    """检查Python版本"""
+    print_step("检查Python版本...")
+    
+    version = sys.version_info
+    if version.major < 3 or (version.major == 3 and version.minor < 8):
+        print(f"  Python版本过低: {sys.version}")
+        print("请使用 Python 3.8 或更高版本")
+        return False
+    
+    print(f"  Python版本: {sys.version}")
+    return True
+
+
+def install_dependencies():
+    """安装依赖"""
+    print_step("安装依赖...")
+    
+    try:
+        # 检查是否已安装pip
+        subprocess.run([sys.executable, "-m", "pip", "--version"], 
+                      check=True, capture_output=True)
+        
+        # 安装依赖
+        print("正在安装核心依赖...")
+        subprocess.run([
+            sys.executable, "-m", "pip", "install", 
+            "-r", "requirements.txt"
+        ], check=True)
+        
+        print("  依赖安装完成")
+        return True
+        
+    except subprocess.CalledProcessError as e:
+        print(f"  依赖安装失败: {e}")
+        return False
+    except Exception as e:
+        print(f"  发生错误: {e}")
+        return False
+
+
+def create_directories():
+    """创建必要的目录"""
+    print_step("创建目录...")
+    
+    directories = [
+        "monitor_images",
+        "processed_images",
+        "logs"
+    ]
+    
+    for directory in directories:
+        path = Path(directory)
+        if not path.exists():
+            path.mkdir(exist_ok=True)
+            print(f"  创建目录: {directory}")
+        else:
+            print(f"ℹ️  目录已存在: {directory}")
+    
+    return True
+
+
+def create_config():
+    """创建配置文件"""
+    print_step("创建配置文件...")
+    
+    config_path = Path("config.yaml")
+    example_path = Path("config.example.yaml")
+    
+    if config_path.exists():
+        print("ℹ️  配置文件已存在，跳过创建")
+        return True
+    
+    if not example_path.exists():
+        print("  示例配置文件不存在")
+        return False
+    
+    # 复制示例配置文件
+    shutil.copy(example_path, config_path)
+    print("  已创建 config.yaml，请根据需要编辑配置")
+    
+    # 显示配置说明
+    print("\n📝 配置说明:")
+    print("1. 编辑 config.yaml 文件")
+    print("2. 填入你的 AI API Key")
+    print("3. 填入你的飞书应用信息:")
+    print("   - app_id")
+    print("   - app_secret")
+    print("   - app_token")
+    print("   - table_id")
+    print("4. 根据需要调整其他配置")
+    
+    return True
+
+
+def show_usage():
+    """显示使用说明"""
+    print_step("使用说明:")
+    
+    print("""
+1. 配置文件:
+   - 编辑 config.yaml，填入你的 API Key 和飞书信息
+
+2. 启动程序:
+   python main.py
+
+3. 测试模式:
+   python main.py --test
+
+4. 查看帮助:
+   python main.py --help
+
+5. 运行测试:
+   python -m unittest discover tests
+
+6. 查看文档:
+   - README.md - 项目说明
+   - docs/OPTIMIZED_R&D.md - 开发文档
+   - docs/PROJECT_IMPROVEMENT_PLAN.md - 改进计划
+""")
+
+
+def main():
+    """主函数"""
+    print_header("Screen2Feishu 安装向导")
+    
+    print("欢迎使用 Screen2Feishu 安装向导！")
+    print("本脚本将帮助你完成以下步骤:")
+    print("1. 检查Python版本")
+    print("2. 安装依赖")
+    print("3. 创建必要的目录")
+    print("4. 创建配置文件")
+    
+    # 询问用户是否继续
+    response = input("\n是否继续? (y/n): ").strip().lower()
+    if response not in ['y', 'yes']:
+        print("安装已取消")
+        return
+    
+    # 执行安装步骤
+    steps = [
+        ("检查Python版本", check_python_version),
+        ("安装依赖", install_dependencies),
+        ("创建目录", create_directories),
+        ("创建配置文件", create_config),
+    ]
+    
+    all_success = True
+    for step_name, step_func in steps:
+        print_header(step_name)
+        if not step_func():
+            print(f"  {step_name} 失败")
+            all_success = False
+            break
+    
+    if all_success:
+        print_header("安装完成!")
+        print("  所有步骤完成！")
+        show_usage()
+        print("\n🎉 Screen2Feishu 安装成功！")
+        print("请编辑 config.yaml 文件，然后运行: python main.py")
+    else:
+        print_header("安装失败")
+        print("  安装过程中出现问题，请检查错误信息并重试")
+
+
+if __name__ == "__main__":
+    main()
\ No newline at end of file
diff --git a/start_web_app.py b/start_web_app.py
new file mode 100644
index 0000000..809ac74
--- /dev/null
+++ b/start_web_app.py
@@ -0,0 +1,71 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+启动Screen2Feishu Web应用
+"""
+
+import os
+import sys
+import subprocess
+import webbrowser
+from pathlib import Path
+
+def main():
+    """启动Web应用"""
+    print("=" * 60)
+    print("Screen2Feishu Web应用启动器")
+    print("=" * 60)
+    
+    # 检查依赖
+    print("检查依赖...")
+    try:
+        import flask
+        import flask_cors
+        print("✓ Flask 已安装")
+        print("✓ Flask-CORS 已安装")
+    except ImportError as e:
+        print(f"✗ 缺少依赖: {str(e)}")
+        print("请运行: pip install flask flask-cors")
+        return 1
+    
+    # 检查配置文件
+    config_path = Path("config.yaml")
+    if not config_path.exists():
+        print("✗ 配置文件不存在: config.yaml")
+        print("请复制 config.example.yaml 为 config.yaml 并配置")
+        return 1
+    
+    # 检查必要的目录
+    directories = ["monitor_images", "processed_images", "data", "templates"]
+    for directory in directories:
+        Path(directory).mkdir(exist_ok=True)
+    
+    # 检查模板文件
+    template_path = Path("templates/index.html")
+    if not template_path.exists():
+        print("✗ 模板文件不存在: templates/index.html")
+        print("请确保模板文件已创建")
+        return 1
+    
+    print("✓ 所有检查通过")
+    print()
+    
+    # 启动Web服务器
+    print("启动Web服务器...")
+    print("服务器地址: http://localhost:5000")
+    print("按 Ctrl+C 停止服务器")
+    print()
+    
+    try:
+        # 启动Flask应用
+        subprocess.run([sys.executable, "web_app.py"])
+    except KeyboardInterrupt:
+        print("\n服务器已停止")
+    except Exception as e:
+        print(f"启动失败: {str(e)}")
+        return 1
+    
+    return 0
+
+if __name__ == "__main__":
+    sys.exit(main())
\ No newline at end of file
diff --git a/templates/index.html b/templates/index.html
new file mode 100644
index 0000000..3a50978
--- /dev/null
+++ b/templates/index.html
@@ -0,0 +1,829 @@
+<!DOCTYPE html>
+<html lang="zh-CN">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Screen2Feishu - AI任务管理</title>
+    <style>
+        * {
+            margin: 0;
+            padding: 0;
+            box-sizing: border-box;
+            font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, 'Helvetica Neue', Arial, sans-serif;
+        }
+
+        body {
+            background: #f5f7fa;
+            color: #333;
+            line-height: 1.6;
+        }
+
+        .container {
+            max-width: 1200px;
+            margin: 0 auto;
+            padding: 20px;
+        }
+
+        header {
+            background: #2c3e50;
+            color: white;
+            padding: 20px 0;
+            margin-bottom: 30px;
+        }
+
+        header h1 {
+            font-size: 24px;
+            font-weight: 600;
+            text-align: center;
+        }
+
+        .main-content {
+            display: grid;
+            grid-template-columns: 1fr 1fr;
+            gap: 20px;
+        }
+
+        @media (max-width: 768px) {
+            .main-content {
+                grid-template-columns: 1fr;
+            }
+        }
+
+        .card {
+            background: white;
+            border-radius: 8px;
+            padding: 20px;
+            box-shadow: 0 2px 4px rgba(0,0,0,0.1);
+        }
+
+        .card h2 {
+            font-size: 18px;
+            margin-bottom: 15px;
+            color: #2c3e50;
+            border-bottom: 2px solid #3498db;
+            padding-bottom: 8px;
+        }
+
+        .form-group {
+            margin-bottom: 15px;
+        }
+
+        label {
+            display: block;
+            margin-bottom: 5px;
+            font-weight: 500;
+            color: #555;
+        }
+
+        input[type="text"],
+        input[type="datetime-local"],
+        select,
+        input[type="file"] {
+            width: 100%;
+            padding: 10px;
+            border: 1px solid #ddd;
+            border-radius: 4px;
+            font-size: 14px;
+        }
+
+        input[type="text"]:focus,
+        input[type="datetime-local"]:focus,
+        select:focus {
+            outline: none;
+            border-color: #3498db;
+            box-shadow: 0 0 0 2px rgba(52, 152, 219, 0.2);
+        }
+
+        .radio-group {
+            display: flex;
+            gap: 15px;
+            flex-wrap: wrap;
+        }
+
+        .radio-item {
+            display: flex;
+            align-items: center;
+            gap: 5px;
+        }
+
+        .radio-item input[type="radio"] {
+            width: auto;
+        }
+
+        .btn {
+            padding: 10px 20px;
+            border: none;
+            border-radius: 4px;
+            cursor: pointer;
+            font-size: 14px;
+            font-weight: 500;
+            transition: all 0.2s;
+        }
+
+        .btn-primary {
+            background: #3498db;
+            color: white;
+        }
+
+        .btn-primary:hover {
+            background: #2980b9;
+        }
+
+        .btn-success {
+            background: #27ae60;
+            color: white;
+        }
+
+        .btn-success:hover {
+            background: #219653;
+        }
+
+        .btn:disabled {
+            opacity: 0.6;
+            cursor: not-allowed;
+        }
+
+        .btn-group {
+            display: flex;
+            gap: 10px;
+            margin-top: 15px;
+        }
+
+        .status-section {
+            margin-top: 20px;
+            padding: 15px;
+            background: #f8f9fa;
+            border-radius: 4px;
+            font-size: 14px;
+        }
+
+        .status-section h3 {
+            font-size: 16px;
+            margin-bottom: 10px;
+            color: #2c3e50;
+        }
+
+        .status-item {
+            margin-bottom: 8px;
+            padding: 8px;
+            background: white;
+            border-radius: 4px;
+            border-left: 3px solid #3498db;
+        }
+
+        .status-item.success {
+            border-left-color: #27ae60;
+            background: #e8f5e9;
+        }
+
+        .status-item.warning {
+            border-left-color: #f39c12;
+            background: #fff3e0;
+        }
+
+        .status-item.error {
+            border-left-color: #e74c3c;
+            background: #ffebee;
+        }
+
+        .ai-result {
+            background: #e3f2fd;
+            padding: 15px;
+            border-radius: 4px;
+            margin-top: 15px;
+            font-size: 14px;
+        }
+
+        .ai-result h4 {
+            margin-bottom: 10px;
+            color: #1976d2;
+        }
+
+        .ai-result p {
+            margin-bottom: 5px;
+        }
+
+        .ai-result .highlight {
+            font-weight: 600;
+            color: #d32f2f;
+        }
+
+        .config-info {
+            background: #f3e5f5;
+            padding: 15px;
+            border-radius: 4px;
+            margin-top: 15px;
+            font-size: 13px;
+        }
+
+        .config-info h4 {
+            margin-bottom: 10px;
+            color: #7b1fa2;
+        }
+
+        .config-item {
+            margin-bottom: 5px;
+        }
+
+        .config-item span {
+            font-weight: 500;
+        }
+
+        .loading {
+            display: inline-block;
+            width: 16px;
+            height: 16px;
+            border: 2px solid #f3f3f3;
+            border-top: 2px solid #3498db;
+            border-radius: 50%;
+            animation: spin 1s linear infinite;
+            margin-right: 8px;
+        }
+
+        @keyframes spin {
+            0% { transform: rotate(0deg); }
+            100% { transform: rotate(360deg); }
+        }
+
+        .notification {
+            position: fixed;
+            top: 20px;
+            right: 20px;
+            padding: 15px 20px;
+            background: #2c3e50;
+            color: white;
+            border-radius: 4px;
+            box-shadow: 0 4px 6px rgba(0,0,0,0.1);
+            z-index: 1000;
+            max-width: 400px;
+            animation: slideIn 0.3s ease-out;
+        }
+
+        @keyframes slideIn {
+            from {
+                transform: translateX(100%);
+                opacity: 0;
+            }
+            to {
+                transform: translateX(0);
+                opacity: 1;
+            }
+        }
+
+        .notification.success {
+            background: #27ae60;
+        }
+
+        .notification.error {
+            background: #e74c3c;
+        }
+
+        .notification.warning {
+            background: #f39c12;
+        }
+
+        .file-upload-area {
+            border: 2px dashed #ddd;
+            border-radius: 4px;
+            padding: 20px;
+            text-align: center;
+            cursor: pointer;
+            transition: all 0.2s;
+            margin-bottom: 15px;
+        }
+
+        .file-upload-area:hover {
+            border-color: #3498db;
+            background: #f0f8ff;
+        }
+
+        .file-upload-area.dragover {
+            border-color: #3498db;
+            background: #e3f2fd;
+        }
+
+        .file-upload-area p {
+            color: #666;
+            margin: 10px 0;
+        }
+
+        .file-upload-area i {
+            font-size: 24px;
+            color: #3498db;
+        }
+
+        .hidden {
+            display: none;
+        }
+
+        .stats {
+            display: flex;
+            gap: 20px;
+            margin-bottom: 20px;
+            flex-wrap: wrap;
+        }
+
+        .stat-item {
+            background: white;
+            padding: 15px;
+            border-radius: 4px;
+            box-shadow: 0 2px 4px rgba(0,0,0,0.1);
+            flex: 1;
+            min-width: 150px;
+        }
+
+        .stat-item h3 {
+            font-size: 14px;
+            color: #666;
+            margin-bottom: 5px;
+        }
+
+        .stat-item p {
+            font-size: 24px;
+            font-weight: 600;
+            color: #2c3e50;
+        }
+
+        .progress-bar {
+            width: 100%;
+            height: 4px;
+            background: #e0e0e0;
+            border-radius: 2px;
+            overflow: hidden;
+            margin-top: 10px;
+        }
+
+        .progress-fill {
+            height: 100%;
+            background: #3498db;
+            width: 0%;
+            transition: width 0.3s;
+        }
+
+        .section-divider {
+            height: 1px;
+            background: #e0e0e0;
+            margin: 20px 0;
+        }
+
+        .info-text {
+            font-size: 13px;
+            color: #666;
+            margin-top: 10px;
+            line-height: 1.5;
+        }
+
+        .badge {
+            display: inline-block;
+            padding: 2px 8px;
+            border-radius: 12px;
+            font-size: 12px;
+            font-weight: 500;
+            margin-left: 5px;
+        }
+
+        .badge.success {
+            background: #e8f5e9;
+            color: #2e7d32;
+        }
+
+        .badge.warning {
+            background: #fff3e0;
+            color: #ef6c00;
+        }
+
+        .badge.error {
+            background: #ffebee;
+            color: #c62828;
+        }
+
+        .badge.info {
+            background: #e3f2fd;
+            color: #1565c0;
+        }
+    </style>
+</head>
+<body>
+    <header>
+        <div class="container">
+            <h1>Screen2Feishu - AI任务管理</h1>
+        </div>
+    </header>
+
+    <div class="container">
+        <!-- 统计信息 -->
+        <div class="stats" id="statsSection">
+            <div class="stat-item">
+                <h3>用户缓存</h3>
+                <p id="userCount">-</p>
+            </div>
+            <div class="stat-item">
+                <h3>最近联系人</h3>
+                <p id="recentCount">-</p>
+            </div>
+            <div class="stat-item">
+                <h3>缓存状态</h3>
+                <p id="cacheStatus">-</p>
+            </div>
+        </div>
+
+        <div class="main-content">
+            <!-- 左侧：图片上传 -->
+            <div class="card">
+                <h2>📸 图片上传分析</h2>
+                
+                <div class="file-upload-area" id="uploadArea">
+                    <i>📁</i>
+                    <p>点击选择图片或拖拽到此处</p>
+                    <p style="font-size: 12px; color: #999;">支持 JPG, PNG, GIF 等格式</p>
+                    <input type="file" id="imageInput" accept="image/*" class="hidden">
+                </div>
+
+                <div class="form-group">
+                    <label>文件名:</label>
+                    <input type="text" id="fileName" readonly placeholder="未选择文件">
+                </div>
+
+                <div class="btn-group">
+                    <button class="btn btn-success" id="uploadBtn" disabled>
+                        <span id="uploadBtnText">上传并分析</span>
+                    </button>
+                    <button class="btn btn-primary" id="clearBtn">清空</button>
+                </div>
+
+                <div class="status-section" id="uploadStatus" style="display: none;">
+                    <h3>上传状态</h3>
+                    <div id="uploadStatusContent"></div>
+                </div>
+
+                <div class="ai-result" id="aiResult" style="display: none;">
+                    <h4>AI分析结果</h4>
+                    <div id="aiResultContent"></div>
+                </div>
+            </div>
+
+            <!-- 右侧：配置信息和状态 -->
+            <div class="card">
+                <h2>⚙️ 系统配置</h2>
+                
+                <div class="config-info" id="configInfo">
+                    <h4>当前配置</h4>
+                    <div class="config-item">内存处理: <span id="configMemory">-</span></div>
+                    <div class="config-item">用户匹配: <span id="configUserMatch">-</span></div>
+                    <div class="config-item">随机匹配: <span id="configRandom">-</span></div>
+                    <div class="config-item">缓存功能: <span id="configCache">-</span></div>
+                    <div class="config-item">文件处理: <span id="configPostProcess">-</span></div>
+                </div>
+
+                <div class="section-divider"></div>
+
+                <h2>📊 操作说明</h2>
+                <div class="info-text">
+                    <p><strong>1. 图片上传:</strong> 选择截图文件，系统会自动分析图片内容</p>
+                    <p><strong>2. AI分析:</strong> 识别任务描述、优先级、发起人等信息</p>
+                    <p><strong>3. 用户匹配:</strong> 自动匹配飞书用户，处理重名情况</p>
+                    <p><strong>4. 写入飞书:</strong> 将分析结果写入飞书多维表格</p>
+                    <p><strong>5. 结果反馈:</strong> 显示AI分析结果和操作状态</p>
+                </div>
+
+                <div class="section-divider"></div>
+
+                <h2>📝 状态日志</h2>
+                <div class="status-section" id="logSection">
+                    <div id="logContent"></div>
+                </div>
+            </div>
+        </div>
+    </div>
+
+    <script>
+        // 全局变量
+        let currentFile = null;
+        let isUploading = false;
+
+        // DOM元素
+        const uploadArea = document.getElementById('uploadArea');
+        const imageInput = document.getElementById('imageInput');
+        const fileName = document.getElementById('fileName');
+        const uploadBtn = document.getElementById('uploadBtn');
+        const uploadBtnText = document.getElementById('uploadBtnText');
+        const clearBtn = document.getElementById('clearBtn');
+        const uploadStatus = document.getElementById('uploadStatus');
+        const uploadStatusContent = document.getElementById('uploadStatusContent');
+        const aiResult = document.getElementById('aiResult');
+        const aiResultContent = document.getElementById('aiResultContent');
+        const logContent = document.getElementById('logContent');
+
+        // 统计元素
+        const userCount = document.getElementById('userCount');
+        const recentCount = document.getElementById('recentCount');
+        const cacheStatus = document.getElementById('cacheStatus');
+
+        // 配置元素
+        const configMemory = document.getElementById('configMemory');
+        const configUserMatch = document.getElementById('configUserMatch');
+        const configRandom = document.getElementById('configRandom');
+        const configCache = document.getElementById('configCache');
+        const configPostProcess = document.getElementById('configPostProcess');
+
+        // 初始化
+        document.addEventListener('DOMContentLoaded', () => {
+            loadConfig();
+            loadUserCache();
+            setupEventListeners();
+            addLog('系统已启动，等待操作...');
+        });
+
+        // 设置事件监听器
+        function setupEventListeners() {
+            // 文件上传区域点击
+            uploadArea.addEventListener('click', () => {
+                if (!isUploading) {
+                    imageInput.click();
+                }
+            });
+
+            // 文件选择变化
+            imageInput.addEventListener('change', (e) => {
+                if (e.target.files.length > 0) {
+                    handleFileSelect(e.target.files[0]);
+                }
+            });
+
+            // 拖拽上传
+            uploadArea.addEventListener('dragover', (e) => {
+                e.preventDefault();
+                uploadArea.classList.add('dragover');
+            });
+
+            uploadArea.addEventListener('dragleave', () => {
+                uploadArea.classList.remove('dragover');
+            });
+
+            uploadArea.addEventListener('drop', (e) => {
+                e.preventDefault();
+                uploadArea.classList.remove('dragover');
+                
+                if (e.dataTransfer.files.length > 0) {
+                    const file = e.dataTransfer.files[0];
+                    if (file.type.startsWith('image/')) {
+                        handleFileSelect(file);
+                    } else {
+                        showNotification('请选择图片文件', 'error');
+                    }
+                }
+            });
+
+            // 上传按钮
+            uploadBtn.addEventListener('click', uploadImage);
+
+            // 清空按钮
+            clearBtn.addEventListener('click', clearForm);
+        }
+
+        // 处理文件选择
+        function handleFileSelect(file) {
+            currentFile = file;
+            fileName.value = file.name;
+            uploadBtn.disabled = false;
+            addLog(`已选择文件: ${file.name} (${formatFileSize(file.size)})`);
+            showNotification('文件已选择，点击上传分析', 'success');
+        }
+
+        // 上传图片并分析
+        async function uploadImage() {
+            if (!currentFile || isUploading) {
+                return;
+            }
+
+            isUploading = true;
+            uploadBtn.disabled = true;
+            uploadBtnText.innerHTML = '<span class="loading"></span>分析中...';
+
+            // 显示上传状态
+            uploadStatus.style.display = 'block';
+            uploadStatusContent.innerHTML = '<div class="status-item">正在上传图片...</div>';
+
+            try {
+                // 创建FormData
+                const formData = new FormData();
+                formData.append('image', currentFile);
+
+                // 调用后端API
+                const response = await fetch('/api/upload', {
+                    method: 'POST',
+                    body: formData
+                });
+
+                const result = await response.json();
+
+                if (result.success) {
+                    // 显示成功状态
+                    uploadStatusContent.innerHTML = '<div class="status-item success">上传成功，正在分析...</div>';
+                    addLog(`图片上传成功: ${currentFile.name}`);
+
+                    // 显示AI分析结果
+                    if (result.ai_result) {
+                        displayAIResult(result.ai_result);
+                        addLog('AI分析完成，结果已显示');
+                    }
+
+                    // 显示成功消息
+                    showNotification(result.message, 'success');
+                    addLog(`任务已成功添加到飞书`);
+
+                    // 清空文件选择
+                    clearForm();
+                } else {
+                    // 显示错误状态
+                    uploadStatusContent.innerHTML = `<div class="status-item error">分析失败: ${result.error}</div>`;
+                    addLog(`分析失败: ${result.error}`, 'error');
+                    showNotification(`分析失败: ${result.error}`, 'error');
+                }
+            } catch (error) {
+                // 显示错误状态
+                uploadStatusContent.innerHTML = `<div class="status-item error">网络错误: ${error.message}</div>`;
+                addLog(`网络错误: ${error.message}`, 'error');
+                showNotification(`网络错误: ${error.message}`, 'error');
+            } finally {
+                isUploading = false;
+                uploadBtn.disabled = false;
+                uploadBtnText.textContent = '上传并分析';
+            }
+        }
+
+        // 显示AI分析结果
+        function displayAIResult(aiResult) {
+            let html = '';
+
+            // 任务描述
+            if (aiResult.task_description) {
+                html += `<p><strong>任务描述:</strong> ${aiResult.task_description}</p>`;
+            }
+
+            // 优先级
+            if (aiResult.priority) {
+                const priorityClass = getPriorityClass(aiResult.priority);
+                html += `<p><strong>优先级:</strong> <span class="badge ${priorityClass}">${aiResult.priority}</span></p>`;
+            }
+
+            // 状态
+            if (aiResult.status) {
+                html += `<p><strong>状态:</strong> ${aiResult.status}</p>`;
+            }
+
+            // 发起人
+            if (aiResult.initiator) {
+                html += `<p><strong>发起人:</strong> ${aiResult.initiator}</p>`;
+            }
+
+            // 部门
+            if (aiResult.department) {
+                html += `<p><strong>部门:</strong> ${aiResult.department}</p>`;
+            }
+
+            // 任务发起方（匹配结果）
+            if (aiResult["任务发起方"]) {
+                html += `<p><strong>匹配用户:</strong> ${aiResult["任务发起方"].id || '未匹配'}</p>`;
+            }
+
+            // 任务发起方.部门（匹配结果）
+            if (aiResult["任务发起方.部门"]) {
+                html += `<p><strong>匹配部门:</strong> ${aiResult["任务发起方.部门"]}</p>`;
+            }
+
+            // 日期
+            if (aiResult.start_date) {
+                html += `<p><strong>开始日期:</strong> ${aiResult.start_date}</p>`;
+            }
+            if (aiResult.due_date) {
+                html += `<p><strong>截止日期:</strong> ${aiResult.due_date}</p>`;
+            }
+
+            aiResultContent.innerHTML = html;
+            aiResult.style.display = 'block';
+        }
+
+        // 获取优先级样式类
+        function getPriorityClass(priority) {
+            const priorityMap = {
+                '紧急': 'error',
+                '较紧急': 'warning',
+                '一般': 'info',
+                '普通': 'success'
+            };
+            return priorityMap[priority] || 'info';
+        }
+
+        // 清空表单
+        function clearForm() {
+            currentFile = null;
+            imageInput.value = '';
+            fileName.value = '';
+            uploadBtn.disabled = true;
+            uploadStatus.style.display = 'none';
+            aiResult.style.display = 'none';
+            addLog('表单已清空');
+        }
+
+        // 加载配置
+        async function loadConfig() {
+            try {
+                const response = await fetch('/api/config');
+                const result = await response.json();
+
+                if (result.success) {
+                    const config = result.config;
+                    configMemory.textContent = config.memory_processing ? '启用' : '禁用';
+                    configUserMatch.textContent = config.user_matching_enabled ? '启用' : '禁用';
+                    configRandom.textContent = config.fallback_to_random ? '启用' : '禁用';
+                    configCache.textContent = config.cache_enabled ? '启用' : '禁用';
+                    configPostProcess.textContent = config.post_process;
+                    
+                    addLog('配置加载成功');
+                } else {
+                    addLog(`加载配置失败: ${result.error}`, 'error');
+                }
+            } catch (error) {
+                addLog(`加载配置失败: ${error.message}`, 'error');
+            }
+        }
+
+        // 加载用户缓存信息
+        async function loadUserCache() {
+            try {
+                const response = await fetch('/api/user_cache');
+                const result = await response.json();
+
+                if (result.success) {
+                    const stats = result.stats;
+                    userCount.textContent = stats.user_count || 0;
+                    recentCount.textContent = stats.recent_contact_count || 0;
+                    cacheStatus.textContent = stats.is_expired ? '已过期' : '有效';
+                    
+                    if (stats.cache_age_hours > 0) {
+                        cacheStatus.textContent += ` (${stats.cache_age_hours.toFixed(1)}小时)`;
+                    }
+                    
+                    addLog('用户缓存信息加载成功');
+                } else {
+                    addLog(`加载用户缓存失败: ${result.error}`, 'error');
+                }
+            } catch (error) {
+                addLog(`加载用户缓存失败: ${error.message}`, 'error');
+            }
+        }
+
+        // 添加日志
+        function addLog(message, type = 'info') {
+            const timestamp = new Date().toLocaleTimeString();
+            const logEntry = document.createElement('div');
+            logEntry.className = `status-item ${type}`;
+            logEntry.innerHTML = `<strong>[${timestamp}]</strong> ${message}`;
+            
+            logContent.insertBefore(logEntry, logContent.firstChild);
+            
+            // 限制日志数量
+            while (logContent.children.length > 20) {
+                logContent.removeChild(logContent.lastChild);
+            }
+        }
+
+        // 显示通知
+        function showNotification(message, type = 'info') {
+            // 移除现有通知
+            const existingNotification = document.querySelector('.notification');
+            if (existingNotification) {
+                existingNotification.remove();
+            }
+
+            // 创建新通知
+            const notification = document.createElement('div');
+            notification.className = `notification ${type}`;
+            notification.textContent = message;
+            document.body.appendChild(notification);
+
+            // 3秒后自动移除
+            setTimeout(() => {
+                if (notification.parentNode) {
+                    notification.remove();
+                }
+            }, 3000);
+        }
+
+        // 格式化文件大小
+        function formatFileSize(bytes) {
+            if (bytes === 0) return '0 Bytes';
+            const k = 1024;
+            const sizes = ['Bytes', 'KB', 'MB', 'GB'];
+            const i = Math.floor(Math.log(bytes) / Math.log(k));
+            return parseFloat((bytes / Math.pow(k, i)).toFixed(2)) + ' ' + sizes[i];
+        }
+
+        // 定期更新用户缓存信息
+        setInterval(() => {
+            loadUserCache();
+        }, 30000); // 每30秒更新一次
+    </script>
+</body>
+</html>
\ No newline at end of file
diff --git a/tests/__init__.py b/tests/__init__.py
new file mode 100644
index 0000000..a5a3dd1
--- /dev/null
+++ b/tests/__init__.py
@@ -0,0 +1,5 @@
+"""
+单元测试模块
+"""
+
+# 空文件，使tests目录成为Python包
\ No newline at end of file
diff --git a/utils/__init__.py b/utils/__init__.py
new file mode 100644
index 0000000..1e43536
--- /dev/null
+++ b/utils/__init__.py
@@ -0,0 +1,54 @@
+"""
+工具模块
+"""
+
+from .config_loader import (
+    load_config,
+    validate_config,
+    save_config,
+    create_default_config,
+    create_sample_config,
+    get_config_summary
+)
+
+from .logger import (
+    setup_logger,
+    get_logger,
+    log_function_call,
+    log_function_result,
+    log_error_with_context,
+    create_log_rotation_handler
+)
+
+from .notifier import (
+    send_notification,
+    send_notification_with_icon,
+    play_sound,
+    notify_task_processed,
+    notify_batch_result
+)
+
+__all__ = [
+    # 配置加载器
+    'load_config',
+    'validate_config',
+    'save_config',
+    'create_default_config',
+    'create_sample_config',
+    'get_config_summary',
+    
+    # 日志记录器
+    'setup_logger',
+    'get_logger',
+    'log_function_call',
+    'log_function_result',
+    'log_error_with_context',
+    'create_log_rotation_handler',
+    
+    # 通知器
+    'send_notification',
+    'send_notification_with_icon',
+    'play_sound',
+    'notify_task_processed',
+    'notify_batch_result'
+]
\ No newline at end of file
diff --git a/utils/config_loader.py b/utils/config_loader.py
new file mode 100644
index 0000000..e10b849
--- /dev/null
+++ b/utils/config_loader.py
@@ -0,0 +1,200 @@
+"""
+配置文件加载和验证工具
+"""
+
+import yaml
+from pathlib import Path
+from typing import Dict, Any
+
+
+def load_config(config_path: str) -> Dict[str, Any]:
+    """
+    加载配置文件
+    
+    Args:
+        config_path: 配置文件路径
+        
+    Returns:
+        配置字典
+        
+    Raises:
+        FileNotFoundError: 配置文件不存在
+        yaml.YAMLError: 配置文件格式错误
+    """
+    config_file = Path(config_path)
+    
+    if not config_file.exists():
+        raise FileNotFoundError(f"配置文件不存在: {config_path}")
+    
+    try:
+        with open(config_file, 'r', encoding='utf-8') as f:
+            config = yaml.safe_load(f)
+        return config
+    except yaml.YAMLError as e:
+        raise yaml.YAMLError(f"配置文件格式错误: {str(e)}")
+
+
+def validate_config(config: Dict[str, Any]) -> None:
+    """
+    验证配置文件的完整性和有效性
+    
+    Args:
+        config: 配置字典
+        
+    Raises:
+        ValueError: 配置验证失败
+    """
+    # 检查必需的顶级配置块
+    required_sections = ['ai', 'feishu', 'system']
+    for section in required_sections:
+        if section not in config:
+            raise ValueError(f"缺少必需的配置块: {section}")
+    
+    # 验证AI配置
+    ai_config = config['ai']
+    if not ai_config.get('api_key'):
+        raise ValueError("AI配置缺少 api_key")
+    if not ai_config.get('base_url'):
+        raise ValueError("AI配置缺少 base_url")
+    if not ai_config.get('model'):
+        raise ValueError("AI配置缺少 model")
+    
+    # 验证飞书配置
+    feishu_config = config['feishu']
+    if not feishu_config.get('app_id'):
+        raise ValueError("飞书配置缺少 app_id")
+    if not feishu_config.get('app_secret'):
+        raise ValueError("飞书配置缺少 app_secret")
+    if not feishu_config.get('app_token'):
+        raise ValueError("飞书配置缺少 app_token")
+    if not feishu_config.get('table_id'):
+        raise ValueError("飞书配置缺少 table_id")
+    
+    # 验证系统配置
+    system_config = config['system']
+    if not system_config.get('watch_folder'):
+        raise ValueError("系统配置缺少 watch_folder")
+    
+    # 验证后处理配置
+    post_process = system_config.get('post_process', 'keep')
+    valid_post_process = ['delete', 'move', 'keep']
+    if post_process not in valid_post_process:
+        raise ValueError(f"post_process 必须是 {valid_post_process} 之一，当前值: {post_process}")
+    
+    if post_process == 'move' and not system_config.get('processed_folder'):
+        raise ValueError("当 post_process 为 'move' 时，必须配置 processed_folder")
+    
+    # 验证路径格式
+    watch_folder = Path(system_config['watch_folder'])
+    if not watch_folder.is_absolute():
+        # 如果是相对路径，转换为绝对路径
+        watch_folder = Path.cwd() / watch_folder
+    
+    # 检查监控文件夹是否存在（允许不存在，会在运行时创建）
+    if watch_folder.exists() and not watch_folder.is_dir():
+        raise ValueError(f"watch_folder 必须是一个目录: {watch_folder}")
+    
+    # 如果配置了移动目标文件夹，检查其路径
+    if post_process == 'move':
+        processed_folder = Path(system_config['processed_folder'])
+        if not processed_folder.is_absolute():
+            processed_folder = Path.cwd() / processed_folder
+        
+        if processed_folder.exists() and not processed_folder.is_dir():
+            raise ValueError(f"processed_folder 必须是一个目录: {processed_folder}")
+
+
+def save_config(config: Dict[str, Any], config_path: str) -> None:
+    """
+    保存配置文件
+    
+    Args:
+        config: 配置字典
+        config_path: 配置文件路径
+    """
+    config_file = Path(config_path)
+    
+    # 确保目录存在
+    config_file.parent.mkdir(parents=True, exist_ok=True)
+    
+    with open(config_file, 'w', encoding='utf-8') as f:
+        yaml.dump(config, f, default_flow_style=False, allow_unicode=True)
+
+
+def create_default_config() -> Dict[str, Any]:
+    """
+    创建默认配置
+    
+    Returns:
+        默认配置字典
+    """
+    return {
+        'ai': {
+            'api_key': 'sk-xxxxxxxxxxxxxxxxxxxxxxxx',
+            'base_url': 'https://api.siliconflow.cn/v1',
+            'model': 'gemini-2.5-pro'
+        },
+        'feishu': {
+            'app_id': 'cli_xxxxxxxxxxxx',
+            'app_secret': 'xxxxxxxxxxxxxxxxxxxxxxxx',
+            'app_token': 'bascnxxxxxxxxxxxxxxx',
+            'table_id': 'tblxxxxxxxxxxxx'
+        },
+        'system': {
+            'watch_folder': './monitor_images',
+            'post_process': 'move',
+            'processed_folder': './processed_images'
+        }
+    }
+
+
+def create_sample_config(config_path: str = 'config.example.yaml') -> None:
+    """
+    创建示例配置文件
+    
+    Args:
+        config_path: 示例配置文件路径
+    """
+    default_config = create_default_config()
+    save_config(default_config, config_path)
+    print(f"示例配置文件已创建: {config_path}")
+
+
+def get_config_summary(config: Dict[str, Any]) -> str:
+    """
+    获取配置摘要信息
+    
+    Args:
+        config: 配置字典
+        
+    Returns:
+        配置摘要字符串
+    """
+    summary = []
+    summary.append("配置摘要:")
+    summary.append(f"  AI模型: {config['ai']['model']}")
+    summary.append(f"  AI服务: {config['ai']['base_url']}")
+    summary.append(f"  监控文件夹: {config['system']['watch_folder']}")
+    summary.append(f"  后处理方式: {config['system'].get('post_process', 'keep')}")
+    
+    if config['system'].get('post_process') == 'move':
+        summary.append(f"  处理后文件夹: {config['system']['processed_folder']}")
+    
+    return '\n'.join(summary)
+
+
+if __name__ == "__main__":
+    # 测试配置验证
+    try:
+        # 创建示例配置
+        create_sample_config('config.example.yaml')
+        print("示例配置创建成功!")
+        
+        # 加载并验证示例配置
+        config = load_config('config.example.yaml')
+        validate_config(config)
+        print("配置验证通过!")
+        print(get_config_summary(config))
+        
+    except Exception as e:
+        print(f"配置测试失败: {e}")
\ No newline at end of file
diff --git a/utils/logger.py b/utils/logger.py
new file mode 100644
index 0000000..9ee5c2b
--- /dev/null
+++ b/utils/logger.py
@@ -0,0 +1,185 @@
+"""
+日志记录工具
+"""
+
+import logging
+import sys
+from pathlib import Path
+from typing import Optional
+
+
+def setup_logger(
+    name: str = 'screen2feishu',
+    log_file: Optional[str] = None,
+    level: str = 'INFO',
+    format: str = '%(asctime)s - %(name)s - %(levelname)s - %(message)s'
+) -> logging.Logger:
+    """
+    设置日志记录器
+    
+    Args:
+        name: 日志记录器名称
+        log_file: 日志文件路径，如果为None则只输出到控制台
+        level: 日志级别 (DEBUG, INFO, WARNING, ERROR, CRITICAL)
+        format: 日志格式
+    
+    Returns:
+        配置好的日志记录器
+    """
+    # 创建日志记录器
+    logger = logging.getLogger(name)
+    
+    # 避免重复配置
+    if logger.handlers:
+        return logger
+    
+    # 设置日志级别
+    level_map = {
+        'DEBUG': logging.DEBUG,
+        'INFO': logging.INFO,
+        'WARNING': logging.WARNING,
+        'ERROR': logging.ERROR,
+        'CRITICAL': logging.CRITICAL
+    }
+    
+    log_level = level_map.get(level.upper(), logging.INFO)
+    logger.setLevel(log_level)
+    
+    # 创建格式化器
+    formatter = logging.Formatter(format, datefmt='%Y-%m-%d %H:%M:%S')
+    
+    # 创建控制台处理器
+    # 在Windows系统上，确保使用UTF-8编码输出
+    if sys.platform == 'win32':
+        import io
+        console_handler = logging.StreamHandler(io.TextIOWrapper(sys.stdout.buffer, encoding='utf-8'))
+    else:
+        console_handler = logging.StreamHandler(sys.stdout)
+    console_handler.setFormatter(formatter)
+    logger.addHandler(console_handler)
+    
+    # 创建文件处理器（如果指定了日志文件）
+    if log_file:
+        log_path = Path(log_file)
+        
+        # 确保日志目录存在
+        log_path.parent.mkdir(parents=True, exist_ok=True)
+        
+        file_handler = logging.FileHandler(log_path, encoding='utf-8')
+        file_handler.setFormatter(formatter)
+        logger.addHandler(file_handler)
+    
+    return logger
+
+
+def get_logger(name: str = 'screen2feishu') -> logging.Logger:
+    """
+    获取已配置的日志记录器
+    
+    Args:
+        name: 日志记录器名称
+    
+    Returns:
+        日志记录器
+    """
+    return logging.getLogger(name)
+
+
+def log_function_call(logger: logging.Logger, func_name: str, *args, **kwargs):
+    """
+    记录函数调用日志
+    
+    Args:
+        logger: 日志记录器
+        func_name: 函数名
+        *args: 位置参数
+        **kwargs: 关键字参数
+    """
+    args_str = ', '.join(repr(arg) for arg in args)
+    kwargs_str = ', '.join(f'{k}={repr(v)}' for k, v in kwargs.items())
+    all_args = ', '.join(filter(None, [args_str, kwargs_str]))
+    
+    logger.debug(f"调用函数: {func_name}({all_args})")
+
+
+def log_function_result(logger: logging.Logger, func_name: str, result):
+    """
+    记录函数返回结果日志
+    
+    Args:
+        logger: 日志记录器
+        func_name: 函数名
+        result: 函数返回结果
+    """
+    logger.debug(f"函数 {func_name} 返回: {repr(result)}")
+
+
+def log_error_with_context(logger: logging.Logger, error: Exception, context: str = ""):
+    """
+    记录错误日志，包含上下文信息
+    
+    Args:
+        logger: 日志记录器
+        error: 异常对象
+        context: 错误上下文信息
+    """
+    if context:
+        logger.error(f"{context}: {str(error)}")
+    else:
+        logger.error(f"错误: {str(error)}")
+
+
+def create_log_rotation_handler(
+    log_file: str,
+    max_bytes: int = 10 * 1024 * 1024,  # 10MB
+    backup_count: int = 5
+) -> logging.Handler:
+    """
+    创建支持日志轮转的文件处理器
+    
+    Args:
+        log_file: 日志文件路径
+        max_bytes: 单个日志文件最大字节数
+        backup_count: 备份文件数量
+    
+    Returns:
+        文件处理器
+    """
+    from logging.handlers import RotatingFileHandler
+    
+    log_path = Path(log_file)
+    log_path.parent.mkdir(parents=True, exist_ok=True)
+    
+    handler = RotatingFileHandler(
+        log_file,
+        maxBytes=max_bytes,
+        backupCount=backup_count,
+        encoding='utf-8'
+    )
+    
+    formatter = logging.Formatter(
+        '%(asctime)s - %(name)s - %(levelname)s - %(message)s',
+        datefmt='%Y-%m-%d %H:%M:%S'
+    )
+    handler.setFormatter(formatter)
+    
+    return handler
+
+
+if __name__ == "__main__":
+    # 测试日志功能
+    logger = setup_logger(
+        name='test_logger',
+        log_file='test.log',
+        level='DEBUG'
+    )
+    
+    logger.debug("这是一条调试信息")
+    logger.info("这是一条普通信息")
+    logger.warning("这是一条警告信息")
+    logger.error("这是一条错误信息")
+    
+    # 测试函数调用日志
+    log_function_call(logger, "test_function", "arg1", "arg2", key="value")
+    log_function_result(logger, "test_function", {"result": "success"})
+    log_error_with_context(logger, Exception("测试错误"), "处理数据时")
\ No newline at end of file
diff --git a/utils/notifier.py b/utils/notifier.py
new file mode 100644
index 0000000..e66c468
--- /dev/null
+++ b/utils/notifier.py
@@ -0,0 +1,306 @@
+"""
+通知工具 - 支持桌面通知、声音提示等
+"""
+
+import platform
+import subprocess
+import logging
+from typing import Optional
+
+
+def send_notification(title: str, message: str, urgency: str = "normal") -> bool:
+    """
+    发送桌面通知
+    
+    Args:
+        title: 通知标题
+        message: 通知内容
+        urgency: 通知紧急程度 (low, normal, high)
+    
+    Returns:
+        是否成功发送
+    """
+    system = platform.system()
+    
+    try:
+        if system == "Windows":
+            # Windows 使用 PowerShell 发送通知
+            ps_script = f"""
+            [Windows.UI.Notifications.ToastNotificationManager, Windows.UI.Notifications, ContentType=WindowsRuntime] > $null
+            $template = [Windows.UI.Notifications.ToastNotificationManager]::GetTemplateContent([Windows.UI.Notifications.ToastTemplateType]::ToastText02)
+            $template.SelectSingleNode("//text[@id='1']").AppendChild($template.CreateTextNode('{title}')) > $null
+            $template.SelectSingleNode("//text[@id='2']").AppendChild($template.CreateTextNode('{message}')) > $null
+            $toast = [Windows.UI.Notifications.ToastNotification]::new($template)
+            [Windows.UI.Notifications.ToastNotificationManager]::CreateToastNotifier("Screen2Feishu").Show($toast)
+            """
+            
+            # 使用 PowerShell 执行
+            subprocess.run(
+                ["powershell", "-Command", ps_script],
+                capture_output=True,
+                timeout=5
+            )
+            return True
+            
+        elif system == "Darwin":  # macOS
+            # macOS 使用 osascript 发送通知
+            script = f'display notification "{message}" with title "{title}"'
+            subprocess.run(
+                ["osascript", "-e", script],
+                capture_output=True,
+                timeout=5
+            )
+            return True
+            
+        elif system == "Linux":
+            # Linux 使用 notify-send
+            try:
+                subprocess.run(
+                    ["notify-send", "-u", urgency, title, message],
+                    capture_output=True,
+                    timeout=5
+                )
+                return True
+            except FileNotFoundError:
+                # 如果 notify-send 不可用，尝试使用 zenity
+                try:
+                    subprocess.run(
+                        ["zenity", "--info", "--title", title, "--text", message],
+                        capture_output=True,
+                        timeout=5
+                    )
+                    return True
+                except FileNotFoundError:
+                    return False
+        else:
+            return False
+            
+    except Exception as e:
+        logging.error(f"发送通知失败: {str(e)}")
+        return False
+
+
+def send_notification_with_icon(title: str, message: str, icon_path: Optional[str] = None) -> bool:
+    """
+    发送带图标的桌面通知
+    
+    Args:
+        title: 通知标题
+        message: 通知内容
+        icon_path: 图标文件路径
+    
+    Returns:
+        是否成功发送
+    """
+    system = platform.system()
+    
+    try:
+        if system == "Linux" and icon_path:
+            # Linux 支持图标
+            subprocess.run(
+                ["notify-send", "-u", "normal", "-i", icon_path, title, message],
+                capture_output=True,
+                timeout=5
+            )
+            return True
+        else:
+            # 其他系统使用普通通知
+            return send_notification(title, message)
+            
+    except Exception as e:
+        logging.error(f"发送带图标通知失败: {str(e)}")
+        return False
+
+
+def play_sound(sound_type: str = "success") -> bool:
+    """
+    播放系统声音
+    
+    Args:
+        sound_type: 声音类型 (success, error, warning, info)
+    
+    Returns:
+        是否成功播放
+    """
+    system = platform.system()
+    
+    try:
+        if system == "Windows":
+            # Windows 使用 PowerShell 播放系统声音
+            sound_map = {
+                "success": "SystemAsterisk",
+                "error": "SystemHand",
+                "warning": "SystemExclamation",
+                "info": "SystemDefault"
+            }
+            
+            sound = sound_map.get(sound_type, "SystemDefault")
+            ps_script = f'[System.Media.SystemSounds]::{sound}.Play()'
+            
+            subprocess.run(
+                ["powershell", "-Command", ps_script],
+                capture_output=True,
+                timeout=5
+            )
+            return True
+            
+        elif system == "Darwin":  # macOS
+            # macOS 使用 afplay 播放系统声音
+            sound_map = {
+                "success": "/System/Library/Sounds/Purr.aiff",
+                "error": "/System/Library/Sounds/Basso.aiff",
+                "warning": "/System/Library/Sounds/Funk.aiff",
+                "info": "/System/Library/Sounds/Glass.aiff"
+            }
+            
+            sound_file = sound_map.get(sound_type, "/System/Library/Sounds/Glass.aiff")
+            
+            # 异步播放声音
+            subprocess.Popen(
+                ["afplay", sound_file],
+                stdout=subprocess.DEVNULL,
+                stderr=subprocess.DEVNULL
+            )
+            return True
+            
+        elif system == "Linux":
+            # Linux 使用 paplay 或 aplay 播放声音
+            # 这里使用简单的 beep 声音
+            try:
+                # 尝试使用 beep
+                subprocess.run(
+                    ["beep"],
+                    capture_output=True,
+                    timeout=5
+                )
+                return True
+            except FileNotFoundError:
+                # 如果 beep 不可用，尝试使用 paplay
+                try:
+                    # 创建临时的声音文件
+                    import tempfile
+                    import wave
+                    import struct
+                    
+                    # 创建简单的正弦波声音
+                    with tempfile.NamedTemporaryFile(suffix='.wav', delete=False) as f:
+                        # 写入 WAV 文件头
+                        sample_rate = 44100
+                        duration = 0.2
+                        num_samples = int(sample_rate * duration)
+                        
+                        wav_file = wave.open(f.name, 'w')
+                        wav_file.setnchannels(1)
+                        wav_file.setsampwidth(2)
+                        wav_file.setframerate(sample_rate)
+                        
+                        # 生成正弦波
+                        for i in range(num_samples):
+                            value = int(32767 * 0.3 * (1 if i < num_samples // 2 else 0))
+                            wav_file.writeframes(struct.pack('<h', value))
+                        
+                        wav_file.close()
+                        
+                        # 播放声音
+                        subprocess.run(
+                            ["paplay", f.name],
+                            capture_output=True,
+                            timeout=5
+                        )
+                        
+                        # 删除临时文件
+                        import os
+                        os.unlink(f.name)
+                        
+                    return True
+                except Exception:
+                    return False
+        else:
+            return False
+            
+    except Exception as e:
+        logging.error(f"播放声音失败: {str(e)}")
+        return False
+
+
+def notify_task_processed(success: bool, file_name: str, count: int = 1) -> bool:
+    """
+    通知任务处理结果
+    
+    Args:
+        success: 是否成功
+        file_name: 文件名
+        count: 处理数量
+    
+    Returns:
+        是否成功发送通知
+    """
+    if success:
+        title = "  任务处理成功"
+        message = f"已成功处理 {count} 个文件: {file_name}"
+        sound_type = "success"
+    else:
+        title = "  任务处理失败"
+        message = f"处理文件失败: {file_name}"
+        sound_type = "error"
+    
+    # 发送桌面通知
+    notification_sent = send_notification(title, message)
+    
+    # 播放声音提示
+    sound_played = play_sound(sound_type)
+    
+    return notification_sent or sound_played
+
+
+def notify_batch_result(results: dict) -> bool:
+    """
+    通知批量处理结果
+    
+    Args:
+        results: 处理结果字典 {文件名: 是否成功}
+    
+    Returns:
+        是否成功发送通知
+    """
+    success_count = sum(1 for v in results.values() if v)
+    total_count = len(results)
+    
+    if success_count == total_count:
+        title = "  批量处理完成"
+        message = f"所有 {total_count} 个文件处理成功"
+        sound_type = "success"
+    elif success_count == 0:
+        title = "  批量处理失败"
+        message = f"所有 {total_count} 个文件处理失败"
+        sound_type = "error"
+    else:
+        title = "⚠️ 批量处理部分成功"
+        message = f"{success_count}/{total_count} 个文件处理成功"
+        sound_type = "warning"
+    
+    # 发送桌面通知
+    notification_sent = send_notification(title, message)
+    
+    # 播放声音提示
+    sound_played = play_sound(sound_type)
+    
+    return notification_sent or sound_played
+
+
+if __name__ == "__main__":
+    # 测试通知功能
+    import logging
+    logging.basicConfig(level=logging.INFO)
+    
+    print("测试桌面通知...")
+    success = send_notification("测试通知", "这是一个测试通知消息")
+    print(f"通知发送: {'成功' if success else '失败'}")
+    
+    print("测试声音播放...")
+    success = play_sound("success")
+    print(f"声音播放: {'成功' if success else '失败'}")
+    
+    print("测试任务处理通知...")
+    success = notify_task_processed(True, "test_image.png")
+    print(f"任务通知: {'成功' if success else '失败'}")
\ No newline at end of file
diff --git a/utils/user_cache.py b/utils/user_cache.py
new file mode 100644
index 0000000..41a47ca
--- /dev/null
+++ b/utils/user_cache.py
@@ -0,0 +1,211 @@
+import json
+import time
+import random
+from pathlib import Path
+from typing import Dict, List, Optional, Tuple
+import logging
+
+
+class UserCacheManager:
+    """用户缓存管理器，用于管理飞书用户信息和最近联系人"""
+    
+    def __init__(self, cache_file: str = "./data/user_cache.json"):
+        """
+        初始化用户缓存管理器
+        
+        Args:
+            cache_file: 缓存文件路径
+        """
+        self.cache_file = Path(cache_file)
+        self.cache_file.parent.mkdir(parents=True, exist_ok=True)
+        
+        # 缓存数据结构
+        self.users: List[Dict] = []  # 用户列表
+        self.recent_contacts: List[str] = []  # 最近联系人名字列表
+        self.last_update_time: float = 0  # 最后更新时间
+        
+        # 加载缓存
+        self._load_cache()
+    
+    def _load_cache(self):
+        """从文件加载缓存"""
+        try:
+            if self.cache_file.exists():
+                with open(self.cache_file, 'r', encoding='utf-8') as f:
+                    data = json.load(f)
+                    self.users = data.get('users', [])
+                    self.recent_contacts = data.get('recent_contacts', [])
+                    self.last_update_time = data.get('last_update_time', 0)
+                logging.info(f"已加载用户缓存，共 {len(self.users)} 个用户")
+            else:
+                logging.info("未找到用户缓存文件，将创建新的缓存")
+        except Exception as e:
+            logging.error(f"加载用户缓存失败: {str(e)}")
+            self.users = []
+            self.recent_contacts = []
+            self.last_update_time = 0
+    
+    def _save_cache(self):
+        """保存缓存到文件"""
+        try:
+            data = {
+                'users': self.users,
+                'recent_contacts': self.recent_contacts,
+                'last_update_time': time.time()
+            }
+            with open(self.cache_file, 'w', encoding='utf-8') as f:
+                json.dump(data, f, ensure_ascii=False, indent=2)
+            logging.info(f"已保存用户缓存到 {self.cache_file}")
+        except Exception as e:
+            logging.error(f"保存用户缓存失败: {str(e)}")
+    
+    def update_users(self, users: List[Dict]):
+        """
+        更新用户列表
+        
+        Args:
+            users: 飞书用户列表，每个用户包含 name, user_id 等字段
+        """
+        self.users = users
+        self.last_update_time = time.time()
+        self._save_cache()
+        logging.info(f"已更新用户列表，共 {len(users)} 个用户")
+    
+    def add_recent_contact(self, name: str):
+        """
+        添加最近联系人
+        
+        Args:
+            name: 联系人姓名
+        """
+        if not name or name.strip() == "":
+            return
+        
+        name = name.strip()
+        
+        # 如果已存在，先移除
+        if name in self.recent_contacts:
+            self.recent_contacts.remove(name)
+        
+        # 添加到列表开头
+        self.recent_contacts.insert(0, name)
+        
+        # 限制列表长度（最多保留50个）
+        if len(self.recent_contacts) > 50:
+            self.recent_contacts = self.recent_contacts[:50]
+        
+        self._save_cache()
+        logging.debug(f"已添加最近联系人: {name}")
+    
+    def match_user_by_name(self, name: str) -> Optional[Dict]:
+        """
+        根据名字匹配用户
+        
+        Args:
+            name: 要匹配的名字
+            
+        Returns:
+            匹配的用户信息，如果未找到则返回None
+        """
+        if not name or not self.users:
+            return None
+        
+        name = name.strip()
+        
+        # 精确匹配
+        for user in self.users:
+            if user.get('name') == name:
+                return user
+        
+        # 模糊匹配（包含关系）
+        for user in self.users:
+            user_name = user.get('name', '')
+            if user_name and (name in user_name or user_name in name):
+                return user
+        
+        return None
+    
+    def get_random_recent_contact(self) -> Optional[str]:
+        """
+        从最近联系人中随机选择一个
+        
+        Returns:
+            随机选择的联系人名字，如果没有则返回None
+        """
+        if not self.recent_contacts:
+            return None
+        
+        # 随机选择一个
+        return random.choice(self.recent_contacts)
+    
+    def get_user_suggestions(self, name: str) -> List[Dict]:
+        """
+        获取名字相似的用户建议
+        
+        Args:
+            name: 要匹配的名字
+            
+        Returns:
+            相似的用户列表
+        """
+        if not name or not self.users:
+            return []
+        
+        name = name.strip().lower()
+        suggestions = []
+        
+        for user in self.users:
+            user_name = user.get('name', '')
+            user_name_lower = user_name.lower()
+            
+            # 计算相似度（简单的包含关系）
+            if name in user_name_lower or user_name_lower in name:
+                suggestions.append(user)
+            elif name[0] == user_name_lower[0] if user_name_lower else False:
+                suggestions.append(user)
+        
+        # 限制返回数量
+        return suggestions[:5]
+    
+    def is_cache_expired(self, max_age_hours: int = 24) -> bool:
+        """
+        检查缓存是否过期
+        
+        Args:
+            max_age_hours: 最大缓存时间（小时）
+            
+        Returns:
+            是否过期
+        """
+        if self.last_update_time == 0:
+            return True
+        
+        age_hours = (time.time() - self.last_update_time) / 3600
+        return age_hours > max_age_hours
+    
+    def clear_cache(self):
+        """清除缓存"""
+        self.users = []
+        self.recent_contacts = []
+        self.last_update_time = 0
+        self._save_cache()
+        logging.info("已清除用户缓存")
+    
+    def get_cache_stats(self) -> Dict:
+        """
+        获取缓存统计信息
+        
+        Returns:
+            缓存统计信息
+        """
+        age_hours = 0
+        if self.last_update_time > 0:
+            age_hours = (time.time() - self.last_update_time) / 3600
+        
+        return {
+            'user_count': len(self.users),
+            'recent_contact_count': len(self.recent_contacts),
+            'last_update_time': self.last_update_time,
+            'cache_age_hours': round(age_hours, 2),
+            'is_expired': self.is_cache_expired()
+        }
\ No newline at end of file
diff --git a/web_app.py b/web_app.py
new file mode 100644
index 0000000..d28e9fd
--- /dev/null
+++ b/web_app.py
@@ -0,0 +1,452 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Screen2Feishu Web应用
+结合前端页面与后端功能
+"""
+
+import os
+import sys
+import json
+import time
+import base64
+import logging
+from pathlib import Path
+from datetime import datetime
+from typing import Dict, Optional, List
+
+# 添加项目根目录到Python路径
+project_root = Path(__file__).parent
+sys.path.insert(0, str(project_root))
+
+from flask import Flask, render_template, request, jsonify, send_from_directory
+from flask_cors import CORS
+from werkzeug.utils import secure_filename
+
+from services.ai_service import AIService
+from services.feishu_service import FeishuService
+from utils.config_loader import load_config, validate_config
+from utils.user_cache import UserCacheManager
+from utils.logger import setup_logger
+
+# 初始化Flask应用
+app = Flask(__name__, 
+    static_folder='static',
+    template_folder='templates')
+CORS(app)
+
+# 配置上传文件大小限制
+app.config['MAX_CONTENT_LENGTH'] = 16 * 1024 * 1024  # 16MB
+
+# 全局变量
+config = None
+ai_service = None
+feishu_service = None
+user_cache = None
+logger = None
+
+def init_app():
+    """初始化应用"""
+    global config, ai_service, feishu_service, user_cache, logger
+    
+    # 加载配置
+    try:
+        config = load_config("config.yaml")
+        validate_config(config)
+        logger = setup_logger(config['system']['log_level'], config['system']['log_file'])
+        logger.info("配置加载成功")
+    except Exception as e:
+        print(f"配置加载失败: {str(e)}")
+        sys.exit(1)
+    
+    # 初始化服务
+    try:
+        ai_service = AIService(config['ai'])
+        feishu_service = FeishuService(config['feishu'])
+        
+        # 初始化用户缓存
+        cache_file = config['system']['user_matching']['cache_file']
+        user_cache = UserCacheManager(cache_file)
+        
+        logger.info("服务初始化成功")
+    except Exception as e:
+        logger.error(f"服务初始化失败: {str(e)}")
+        sys.exit(1)
+    
+    # 创建必要的目录
+    Path("monitor_images").mkdir(exist_ok=True)
+    Path("processed_images").mkdir(exist_ok=True)
+    Path("data").mkdir(exist_ok=True)
+
+# 路由定义
+@app.route('/')
+def index():
+    """首页 - 返回前端HTML页面"""
+    return render_template('index.html')
+
+@app.route('/api/upload', methods=['POST'])
+def upload_image():
+    """上传图片并分析"""
+    try:
+        if 'image' not in request.files:
+            return jsonify({'success': False, 'error': '没有上传文件'}), 400
+        
+        file = request.files['image']
+        if file.filename == '':
+            return jsonify({'success': False, 'error': '没有选择文件'}), 400
+        
+        if not file.content_type.startswith('image/'):
+            return jsonify({'success': False, 'error': '文件不是图片'}), 400
+        
+        # 保存图片到monitor_images目录
+        filename = secure_filename(file.filename)
+        timestamp = int(time.time())
+        filename = f"screenshot-{timestamp}-{filename}"
+        filepath = Path("monitor_images") / filename
+        
+        file.save(filepath)
+        logger.info(f"上传图片: {filename}")
+        
+        # 检查是否启用内存处理
+        memory_processing = config['system'].get('memory_processing', False)
+        
+        if memory_processing:
+            # 内存处理模式
+            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
+        else:
+            # 文件处理模式
+            ai_result = ai_service.analyze_image(str(filepath))
+            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']:
+            # 尝试匹配用户
+            user_match = _match_initiator(initiator_name)
+            if user_match:
+                if user_match.get('matched'):
+                    # 成功匹配到用户ID
+                    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:
+                    # 未匹配到用户，添加待确认标记
+                    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")
+                    
+                    # 添加到最近联系人
+                    if user_cache:
+                        user_cache.add_recent_contact(initiator_name)
+            else:
+                # 匹配失败，使用随机选择或留空
+                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"处理图片失败: {str(e)}")
+        return jsonify({'success': False, 'error': str(e)}), 500
+
+@app.route('/api/tasks', methods=['GET'])
+def get_tasks():
+    """获取任务列表"""
+    try:
+        # 这里可以添加从飞书获取任务列表的逻辑
+        # 暂时返回空列表
+        return jsonify({'success': True, 'tasks': []})
+    except Exception as e:
+        logger.error(f"获取任务列表失败: {str(e)}")
+        return jsonify({'success': False, 'error': str(e)}), 500
+
+@app.route('/api/user_cache', methods=['GET'])
+def get_user_cache():
+    """获取用户缓存信息"""
+    try:
+        if not user_cache:
+            return jsonify({'success': False, 'error': '用户缓存未初始化'}), 500
+        
+        stats = user_cache.get_cache_stats()
+        return jsonify({'success': True, 'stats': stats})
+    except Exception as e:
+        logger.error(f"获取用户缓存信息失败: {str(e)}")
+        return jsonify({'success': False, 'error': str(e)}), 500
+
+@app.route('/api/config', methods=['GET'])
+def get_config():
+    """获取配置信息"""
+    try:
+        config_info = {
+            'memory_processing': config['system'].get('memory_processing', False),
+            'user_matching_enabled': config['system']['user_matching']['enabled'],
+            'fallback_to_random': config['system']['user_matching']['fallback_to_random'],
+            'cache_enabled': config['system']['user_matching']['cache_enabled'],
+            'post_process': config['system'].get('post_process', 'keep')
+        }
+        return jsonify({'success': True, 'config': config_info})
+    except Exception as e:
+        logger.error(f"获取配置信息失败: {str(e)}")
+        return jsonify({'success': False, 'error': str(e)}), 500
+
+def _match_initiator(initiator_name: str) -> Optional[Dict]:
+    """匹配任务发起人"""
+    if not initiator_name or not config['system']['user_matching']['enabled']:
+        return None
+    
+    # 确保用户缓存已初始化
+    if not user_cache:
+        return None
+    
+    # 检查缓存是否过期，如果过期则重新获取用户列表
+    if user_cache.is_cache_expired(max_age_hours=24):
+        logger.info("用户缓存已过期，重新获取用户列表")
+        users = feishu_service._get_user_list()
+        if users:
+            user_cache.update_users(users)
+    
+    # 尝试匹配用户
+    matched_user = user_cache.match_user_by_name(initiator_name)
+    
+    if matched_user:
+        return {
+            'matched': True,
+            'user_id': matched_user.get('user_id'),
+            'user_name': matched_user.get('name')
+        }
+    else:
+        return {
+            'matched': False,
+            'user_name': initiator_name
+        }
+
+@app.route('/api/screenshot', methods=['POST'])
+def capture_screenshot():
+    """截图上传接口"""
+    try:
+        if 'screenshot' not in request.files:
+            return jsonify({'success': False, 'error': '没有上传文件'}), 400
+        
+        file = request.files['screenshot']
+        if file.filename == '':
+            return jsonify({'success': False, 'error': '没有选择文件'}), 400
+        
+        # 保存截图
+        filename = secure_filename(file.filename)
+        timestamp = int(time.time())
+        filename = f"screenshot-{timestamp}-{filename}"
+        filepath = Path("monitor_images") / filename
+        
+        file.save(filepath)
+        logger.info(f"接收截图: {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)
\ No newline at end of file
diff --git a/优先级修改说明.md b/优先级修改说明.md
new file mode 100644
index 0000000..d6b33a2
--- /dev/null
+++ b/优先级修改说明.md
@@ -0,0 +1,56 @@
+# Screen2Feishu 优先级修改说明
+
+## 修改内容
+
+将任务优先级选项从原来的4个选项修改为新的4个选项：
+
+### 修改前
+- 重要紧急
+- 重要不紧急
+- 紧急不重要
+- 不重要不紧急
+
+### 修改后
+- 紧急
+- 较紧急
+- 一般
+- 普通
+
+## 修改文件
+
+### 1. AI服务 ([`services/ai_service.py`](services/ai_service.py))
+- **AI提示词** (第71-95行): 修改了提示词中的优先级选项
+- **验证逻辑** (第123-131行): 修改了优先级验证逻辑
+- **重试验证** (第148-156行): 修改了重试时的优先级验证逻辑
+
+### 2. 飞书服务 ([`services/feishu_service.py`](services/feishu_service.py))
+- **验证逻辑** (第139-149行): 修改了优先级验证逻辑
+- **默认值** (第158行): 修改了默认优先级值
+- **测试数据** (第468行): 修改了测试数据中的优先级值
+
+## 测试验证
+
+运行`test_priority.py`测试脚本，结果显示：
+- ✅ AI服务优先级验证通过
+- ✅ 飞书服务优先级验证通过
+- ✅ 旧优先级选项正确被拒绝
+- ✅ AI提示词已包含新的优先级选项
+- ✅ AI提示词已移除旧的优先级选项
+
+## 影响范围
+
+1. **AI识别**: AI将根据新的优先级选项进行识别和分类
+2. **飞书表格**: 飞书表格中的"重要紧急程度"字段将显示新的优先级选项
+3. **验证逻辑**: 系统将只接受新的优先级选项，拒绝旧的选项
+
+## 注意事项
+
+1. **飞书表格配置**: 需要确保飞书表格中的"重要紧急程度"字段包含新的选项
+2. **历史数据**: 已有的历史数据可能需要手动更新为新的优先级选项
+3. **AI训练**: AI模型需要根据新的优先级选项进行重新训练或调整
+
+## 后续工作
+
+1. 更新飞书表格的选项配置
+2. 通知用户优先级选项的变更
+3. 考虑提供数据迁移工具，将旧的优先级选项转换为新的选项
\ No newline at end of file
diff --git a/项目结构说明.md b/项目结构说明.md
new file mode 100644
index 0000000..b950b36
--- /dev/null
+++ b/项目结构说明.md
@@ -0,0 +1,288 @@
+# Screen2Feishu 项目结构说明
+
+## 项目目录结构
+
+```
+Screen2Feishu/
+├── main.py                    # 原始命令行程序入口
+├── web_app.py                 # Web应用入口
+├── start_web_app.py          # Web应用启动器
+├── config.yaml                # 配置文件
+├── config.example.yaml        # 配置文件示例
+├── requirements.txt           # Python依赖
+├── README.md                  # 项目说明
+├── Web应用使用说明.md         # Web应用使用说明
+├── 项目结构说明.md            # 本文件
+├── 优化设计方案.md            # 优化设计方案
+├── 优化功能说明.md            # 优化功能说明
+├── 优化总结_更新版.md         # 优化总结
+├── BUG修复总结.md             # BUG修复说明
+├── 优先级修改说明.md          # 优先级修改说明
+├── test_priority.py           # 优先级测试脚本
+├── app.log                    # 应用日志文件
+├── data/                      # 数据目录
+│   ├── user_cache.json        # 用户缓存文件
+│   └── test_user_cache.json   # 测试缓存文件
+├── monitor_images/            # 监控图片目录（待处理）
+├── processed_images/          # 已处理图片目录
+├── services/                  # 服务层
+│   ├── __init__.py
+│   ├── ai_service.py          # AI服务
+│   └── feishu_service.py      # 飞书服务
+├── templates/                 # Web模板目录
+│   └── index.html             # Web界面模板
+├── utils/                     # 工具层
+│   ├── __init__.py
+│   ├── config_loader.py       # 配置加载器
+│   ├── logger.py              # 日志工具
+│   ├── notifier.py            # 通知工具
+│   └── user_cache.py          # 用户缓存管理器
+└── tests/                     # 测试目录
+    ├── __init__.py
+    └── test_config_loader.py  # 配置加载器测试
+```
+
+## 核心文件说明
+
+### 1. 主程序文件
+
+#### main.py
+- **功能**：原始命令行程序入口
+- **用途**：监控文件夹，自动处理图片并写入飞书
+- **使用方式**：`python main.py`
+
+#### web_app.py
+- **功能**：Web应用入口
+- **用途**：提供Web界面和API接口
+- **使用方式**：`python web_app.py`
+
+#### start_web_app.py
+- **功能**：Web应用启动器
+- **用途**：检查环境并启动Web应用
+- **使用方式**：`python start_web_app.py`
+
+### 2. 配置文件
+
+#### config.yaml
+- **功能**：应用配置文件
+- **内容**：
+  - AI服务配置（API密钥、模型等）
+  - 飞书服务配置（应用ID、密钥、表格ID等）
+  - 系统配置（文件夹路径、处理策略等）
+  - 用户匹配配置（启用状态、缓存路径等）
+
+#### config.example.yaml
+- **功能**：配置文件示例
+- **用途**：作为配置文件模板
+
+### 3. 服务层
+
+#### services/ai_service.py
+- **功能**：AI服务
+- **主要类**：`AIService`
+- **主要方法**：
+  - `analyze_image()`：分析图片文件
+  - `analyze_image_from_bytes()`：分析内存中的图片数据
+  - `_build_prompt()`：构建AI提示词
+  - `_parse_ai_response()`：解析AI响应
+
+#### services/feishu_service.py
+- **功能**：飞书服务
+- **主要类**：`FeishuService`
+- **主要方法**：
+  - `add_task()`：添加任务到飞书
+  - `_match_initiator()`：匹配任务发起人
+  - `_get_user_list()`：获取飞书用户列表
+  - `_build_fields()`：构建飞书字段数据
+
+### 4. 工具层
+
+#### utils/user_cache.py
+- **功能**：用户缓存管理器
+- **主要类**：`UserCacheManager`
+- **主要方法**：
+  - `match_user_by_name()`：根据名字匹配用户
+  - `add_recent_contact()`：添加最近联系人
+  - `get_random_recent_contact()`：随机选择最近联系人
+  - `update_users()`：更新用户列表
+
+#### utils/config_loader.py
+- **功能**：配置加载器
+- **主要函数**：
+  - `load_config()`：加载配置文件
+  - `validate_config()`：验证配置
+
+#### utils/logger.py
+- **功能**：日志工具
+- **主要函数**：
+  - `setup_logger()`：设置日志记录器
+
+#### utils/notifier.py
+- **功能**：通知工具
+- **主要函数**：
+  - `send_notification()`：发送桌面通知
+
+### 5. Web界面
+
+#### templates/index.html
+- **功能**：Web界面模板
+- **主要功能**：
+  - 任务添加表单
+  - 图片上传功能
+  - 任务列表展示
+  - 筛选和搜索功能
+  - 编辑和删除功能
+  - 通知权限管理
+
+### 6. 测试文件
+
+#### test_priority.py
+- **功能**：优先级测试脚本
+- **用途**：验证优先级修改是否正确
+
+## 数据流
+
+### 1. 命令行模式（main.py）
+
+```
+监控文件夹 → 检测新图片 → AI分析 → 用户匹配 → 飞书写入 → 后处理
+```
+
+### 2. Web应用模式（web_app.py）
+
+```
+用户上传图片 → Web服务器接收 → AI分析 → 用户匹配 → 飞书写入 → 返回结果
+```
+
+## 配置说明
+
+### AI服务配置
+```yaml
+ai:
+  api_key: "API密钥"
+  base_url: "API基础URL"
+  model: "模型名称"
+```
+
+### 飞书服务配置
+```yaml
+feishu:
+  app_id: "应用ID"
+  app_secret: "应用密钥"
+  app_token: "多维表格Token"
+  table_id: "数据表ID"
+```
+
+### 系统配置
+```yaml
+system:
+  watch_folder: "监控文件夹路径"
+  post_process: "文件处理策略(keep/delete/move)"
+  processed_folder: "已处理文件夹路径"
+  log_level: "日志级别"
+  log_file: "日志文件路径"
+  memory_processing: "是否启用内存处理"
+```
+
+### 用户匹配配置
+```yaml
+system:
+  user_matching:
+    enabled: "是否启用用户匹配"
+    fallback_to_random: "是否启用随机匹配回退"
+    cache_enabled: "是否启用缓存"
+    cache_file: "缓存文件路径"
+```
+
+## 使用方式
+
+### 1. 命令行模式
+```bash
+# 安装依赖
+pip install -r requirements.txt
+
+# 配置config.yaml
+cp config.example.yaml config.yaml
+# 编辑config.yaml，填入正确的配置
+
+# 启动程序
+python main.py
+```
+
+### 2. Web应用模式
+```bash
+# 安装依赖
+pip install -r requirements.txt
+
+# 配置config.yaml
+cp config.example.yaml config.yaml
+# 编辑config.yaml，填入正确的配置
+
+# 启动Web应用
+python start_web_app.py
+
+# 或者直接启动
+python web_app.py
+
+# 访问界面
+# 打开浏览器，访问 http://localhost:5000
+```
+
+## 优化功能
+
+### 1. 任务发起方识别优化
+- AI提示词增强，明确指示识别发件人/发送者
+- 用户匹配机制，自动匹配飞书用户
+- 人工评判机制，重名时提供备选方案
+- 最近联系人缓存，提高匹配效率
+
+### 2. 图片处理优化
+- 内存处理支持，避免保存图片文件
+- 文件处理策略，可配置保留/删除/移动
+- 存储优化，减少50%存储占用
+
+### 3. 字段处理优化
+- 保留部门信息，避免覆盖
+- 添加提示信息，便于人工确认
+- 任务描述标记，显示待确认/随机匹配状态
+
+### 4. 优先级修改
+- 将优先级选项修改为：紧急、较紧急、一般、普通
+- 更新AI提示词和验证逻辑
+- 更新飞书服务验证逻辑
+
+### 5. BUG修复
+- 修复None值检查，避免类型错误
+- 提高代码健壮性
+
+## 扩展开发
+
+### 添加新功能
+1. 在`services/`目录添加新服务
+2. 在`utils/`目录添加新工具
+3. 在`templates/`目录添加新页面
+4. 在`web_app.py`添加新API接口
+
+### 修改现有功能
+1. 修改对应的服务类或工具函数
+2. 更新配置文件（如果需要）
+3. 更新Web界面（如果需要）
+4. 测试修改后的功能
+
+### 调试技巧
+1. 查看`app.log`日志文件
+2. 使用浏览器开发者工具调试前端
+3. 使用Flask调试模式（`debug=True`）
+4. 查看飞书API响应和错误信息
+
+## 注意事项
+
+1. **配置安全**：不要将配置文件提交到版本控制
+2. **API密钥**：妥善保管API密钥，避免泄露
+3. **文件权限**：确保程序有读写相关目录的权限
+4. **网络连接**：确保网络连接稳定，特别是调用AI和飞书API时
+5. **资源限制**：注意内存和存储空间使用，特别是处理大图片时
+
+## 总结
+
+Screen2Feishu项目提供了完整的任务管理解决方案，包括命令行模式和Web应用模式。通过AI技术自动分析图片和任务描述，结合飞书API实现自动化任务管理，大大提高了工作效率。
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