Phase 7 Task 7: 插件与集成系统

- 创建 plugin_manager.py 模块
  - PluginManager: 插件管理主类
  - ChromeExtensionHandler: Chrome 插件处理
  - BotHandler: 飞书/钉钉/Slack 机器人处理
  - WebhookIntegration: Zapier/Make Webhook 集成
  - WebDAVSync: WebDAV 同步管理

- 创建完整的 Chrome 扩展代码
  - manifest.json, background.js, content.js, content.css
  - popup.html/js: 弹出窗口界面
  - options.html/js: 设置页面
  - 支持网页剪藏、选中文本保存、项目选择

- 更新 schema.sql 添加插件相关数据库表
  - plugins: 插件配置表
  - bot_sessions: 机器人会话表
  - webhook_endpoints: Webhook 端点表
  - webdav_syncs: WebDAV 同步配置表
  - plugin_activity_logs: 插件活动日志表

- 更新 main.py 添加插件相关 API 端点
  - GET/POST /api/v1/plugins - 插件管理
  - POST /api/v1/plugins/chrome/clip - Chrome 插件保存网页
  - POST /api/v1/bots/webhook/{platform} - 接收机器人消息
  - GET /api/v1/bots/sessions - 机器人会话列表
  - POST /api/v1/webhook-endpoints - 创建 Webhook 端点
  - POST /webhook/{type}/{token} - 接收外部 Webhook
  - POST /api/v1/webdav-syncs - WebDAV 同步配置
  - POST /api/v1/webdav-syncs/{id}/test - 测试 WebDAV 连接
  - POST /api/v1/webdav-syncs/{id}/sync - 触发 WebDAV 同步

- 更新 requirements.txt 添加插件依赖
  - beautifulsoup4: HTML 解析
  - webdavclient3: WebDAV 客户端

- 更新 STATUS.md 和 README.md 开发进度
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# InsightFlow Phase 7 - 多模态支持 API 文档
## 概述
Phase 7 多模态支持模块为 InsightFlow 添加了处理视频和图片的能力,支持:
1. **视频处理**提取音频、关键帧、OCR 识别
2. **图片处理**识别白板、PPT、手写笔记等内容
3. **多模态实体关联**:跨模态实体对齐和知识融合
## 新增 API 端点
### 视频处理
#### 上传视频
```
POST /api/v1/projects/{project_id}/upload-video
```
**参数:**
- `file` (required): 视频文件
- `extract_interval` (optional): 关键帧提取间隔(秒),默认 5 秒
**响应:**
```json
{
"video_id": "abc123",
"project_id": "proj456",
"filename": "meeting.mp4",
"status": "completed",
"audio_extracted": true,
"frame_count": 24,
"ocr_text_preview": "会议内容预览...",
"message": "Video processed successfully"
}
```
#### 获取项目视频列表
```
GET /api/v1/projects/{project_id}/videos
```
**响应:**
```json
[
{
"id": "abc123",
"filename": "meeting.mp4",
"duration": 120.5,
"fps": 30.0,
"resolution": {"width": 1920, "height": 1080},
"ocr_preview": "会议内容...",
"status": "completed",
"created_at": "2024-01-15T10:30:00"
}
]
```
#### 获取视频关键帧
```
GET /api/v1/videos/{video_id}/frames
```
**响应:**
```json
[
{
"id": "frame001",
"frame_number": 1,
"timestamp": 0.0,
"image_url": "/tmp/frames/video123/frame_000001_0.00.jpg",
"ocr_text": "第一页内容...",
"entities": [{"name": "Project Alpha", "type": "PROJECT"}]
}
]
```
### 图片处理
#### 上传图片
```
POST /api/v1/projects/{project_id}/upload-image
```
**参数:**
- `file` (required): 图片文件
- `detect_type` (optional): 是否自动检测图片类型,默认 true
**响应:**
```json
{
"image_id": "img789",
"project_id": "proj456",
"filename": "whiteboard.jpg",
"image_type": "whiteboard",
"ocr_text_preview": "白板内容...",
"description": "这是一张白板图片。内容摘要:...",
"entity_count": 5,
"status": "completed"
}
```
#### 批量上传图片
```
POST /api/v1/projects/{project_id}/upload-images-batch
```
**参数:**
- `files` (required): 多个图片文件
**响应:**
```json
{
"project_id": "proj456",
"total_count": 3,
"success_count": 3,
"failed_count": 0,
"results": [
{
"image_id": "img001",
"status": "success",
"image_type": "ppt",
"entity_count": 4
}
]
}
```
#### 获取项目图片列表
```
GET /api/v1/projects/{project_id}/images
```
### 多模态实体关联
#### 跨模态实体对齐
```
POST /api/v1/projects/{project_id}/multimodal/align
```
**参数:**
- `threshold` (optional): 相似度阈值,默认 0.85
**响应:**
```json
{
"project_id": "proj456",
"aligned_count": 5,
"links": [
{
"link_id": "link001",
"source_entity_id": "ent001",
"target_entity_id": "ent002",
"source_modality": "video",
"target_modality": "document",
"link_type": "same_as",
"confidence": 0.95,
"evidence": "Cross-modal alignment: exact"
}
],
"message": "Successfully aligned 5 cross-modal entity pairs"
}
```
#### 获取多模态统计信息
```
GET /api/v1/projects/{project_id}/multimodal/stats
```
**响应:**
```json
{
"project_id": "proj456",
"video_count": 3,
"image_count": 10,
"multimodal_entity_count": 25,
"cross_modal_links": 8,
"modality_distribution": {
"audio": 15,
"video": 8,
"image": 12,
"document": 20
}
}
```
#### 获取实体多模态提及
```
GET /api/v1/entities/{entity_id}/multimodal-mentions
```
**响应:**
```json
[
{
"id": "mention001",
"entity_id": "ent001",
"entity_name": "Project Alpha",
"modality": "video",
"source_id": "video123",
"source_type": "video_frame",
"text_snippet": "Project Alpha 进度",
"confidence": 1.0,
"created_at": "2024-01-15T10:30:00"
}
]
```
#### 建议多模态实体合并
```
GET /api/v1/projects/{project_id}/multimodal/suggest-merges
```
**响应:**
```json
{
"project_id": "proj456",
"suggestion_count": 3,
"suggestions": [
{
"entity1": {"id": "ent001", "name": "K8s", "type": "TECH"},
"entity2": {"id": "ent002", "name": "Kubernetes", "type": "TECH"},
"similarity": 0.95,
"match_type": "alias_match",
"suggested_action": "merge"
}
]
}
```
## 数据库表结构
### videos 表
存储视频文件信息
- `id`: 视频ID
- `project_id`: 所属项目ID
- `filename`: 文件名
- `duration`: 视频时长(秒)
- `fps`: 帧率
- `resolution`: 分辨率JSON
- `audio_transcript_id`: 关联的音频转录ID
- `full_ocr_text`: 所有帧OCR文本合并
- `extracted_entities`: 提取的实体JSON
- `extracted_relations`: 提取的关系JSON
- `status`: 处理状态
### video_frames 表
存储视频关键帧信息
- `id`: 帧ID
- `video_id`: 所属视频ID
- `frame_number`: 帧序号
- `timestamp`: 时间戳(秒)
- `image_url`: 图片URL或路径
- `ocr_text`: OCR识别文本
- `extracted_entities`: 该帧提取的实体
### images 表
存储图片文件信息
- `id`: 图片ID
- `project_id`: 所属项目ID
- `filename`: 文件名
- `ocr_text`: OCR识别文本
- `description`: 图片描述
- `extracted_entities`: 提取的实体
- `extracted_relations`: 提取的关系
- `status`: 处理状态
### multimodal_mentions 表
存储实体在多模态中的提及
- `id`: 提及ID
- `project_id`: 所属项目ID
- `entity_id`: 实体ID
- `modality`: 模态类型audio/video/image/document
- `source_id`: 来源ID
- `source_type`: 来源类型
- `text_snippet`: 文本片段
- `confidence`: 置信度
### multimodal_entity_links 表
存储跨模态实体关联
- `id`: 关联ID
- `entity_id`: 实体ID
- `linked_entity_id`: 关联实体ID
- `link_type`: 关联类型same_as/related_to/part_of
- `confidence`: 置信度
- `evidence`: 关联证据
- `modalities`: 涉及的模态列表
## 依赖安装
```bash
pip install ffmpeg-python pillow opencv-python pytesseract
```
注意:使用 OCR 功能需要安装 Tesseract OCR 引擎:
- Ubuntu/Debian: `sudo apt-get install tesseract-ocr tesseract-ocr-chi-sim`
- macOS: `brew install tesseract tesseract-lang`
- Windows: 下载安装包从 https://github.com/UB-Mannheim/tesseract/wiki
## 环境变量
```bash
# 可选:自定义临时目录
export INSIGHTFLOW_TEMP_DIR=/path/to/temp
# 可选Tesseract 路径Windows
export TESSERACT_CMD=C:\Program Files\Tesseract-OCR\tesseract.exe
```