DESKTOP-72TV0V4\caoxiaozhu
3a1d9ed676
- 新增 algorithm/ 目录 - 添加知识库 API 需求文档 - 添加相关截图 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
113 lines
1.7 KiB
Markdown
113 lines
1.7 KiB
Markdown
# Algorithm Service
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Python 算法服务，提供文档解析、Embedding、LLM 调用等功能。
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## 环境要求
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- Python 3.9+
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- FastAPI
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- Uvicorn
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## 安装依赖
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```bash
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pip install -r requirements.txt
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```
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## 运行服务
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```bash
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# 开发模式
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uvicorn main:app --reload --port 8081
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# 生产模式
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uvicorn main:app --host 0.0.0.0 --port 8081
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```
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## 接口列表
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### 1. 文档解析
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**请求**
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```
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POST /parse
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Content-Type: application/json
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```
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| 参数 | 类型 | 必填 | 说明 |
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|------|------|------|------|
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| file_url | String | 是 | 文件 URL |
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| engine | String | 是 | 解析引擎：markitdown / docling |
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| docling_url | String | 否 | Docling 服务 URL |
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**响应**
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```json
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{
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"success": true,
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"content": "解析后的文本内容...",
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"chunks": ["chunk1", "chunk2"],
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"total_pages": 10,
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"metadata": {
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"filename": "document.pdf",
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"file_size": 1234567
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}
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}
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```
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### 2. 生成 Embedding
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**请求**
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```
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POST /embedding
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Content-Type: application/json
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```
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| 参数 | 类型 | 必填 | 说明 |
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|------|------|------|------|
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| input | String/Array | 是 | 要 embedding 的文本 |
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| model | String | 是 | 模型名称 |
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**响应**
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```json
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{
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"success": true,
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"embeddings": [[0.1, 0.2, ...], [0.3, 0.4, ...]],
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"model": "text-embedding-3-small"
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}
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```
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### 3. LLM 对话
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**请求**
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```
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POST /chat
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Content-Type: application/json
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```
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| 参数 | 类型 | 必填 | 说明 |
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|------|------|------|------|
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| messages | Array | 是 | 消息列表 |
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| model | String | 是 | 模型名称 |
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| temperature | Float | 否 | 温度参数 |
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**响应**
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```json
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{
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"success": true,
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"message": {
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"role": "assistant",
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"content": "回复内容..."
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},
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"usage": {
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"prompt_tokens": 100,
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"completion_tokens": 50
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}
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}
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```
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