HaHafeng
31d555f7bb
- Add platform infrastructure chapter to frontend-backend architecture design - Update system architecture document with 6 new infrastructure modules - Update AI onboarding guide with infrastructure overview - Link to backend/src/common/README.md for detailed usage guide Key Updates: - Storage service (LocalAdapter + OSSAdapter) - Logging system (Winston + JSON format) - Cache service (Memory + Redis) - Async job queue (Memory + Database) - Health check endpoints - Monitoring metrics - Database connection pool - Environment config management All modules support zero-code switching between local and cloud environments. Related: #Platform-Infrastructure
104 lines
1.8 KiB
Markdown
104 lines
1.8 KiB
Markdown
# RAG引擎
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> **能力定位：** 通用能力层
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> **复用率：** 43% (3个模块依赖)
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> **优先级：** P1
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> **状态：** ✅ 已实现（基于Dify）
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---
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## 📋 能力概述
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RAG引擎负责：
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- 向量化存储（Embedding）
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- 语义检索（Semantic Search）
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- 检索增强生成（RAG）
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- Rerank重排序
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---
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## 📊 依赖模块
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**3个模块依赖（43%复用率）：**
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1. **AIA** - AI智能问答（@知识库问答）
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2. **ASL** - AI智能文献（文献内容检索）
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3. **PKB** - 个人知识库（RAG问答）
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---
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## 💡 核心功能
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### 1. 向量化存储
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- 基于Dify平台
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- Qdrant向量数据库（Dify内置）
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### 2. 语义检索
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- Top-K检索
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- 相关度评分
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- 多知识库联合检索
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### 3. RAG问答
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- 检索 + 生成
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- 智能引用系统（100%准确溯源）
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---
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## 🏗️ 技术架构
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**基于Dify平台：**
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```typescript
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// DifyClient封装
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interface RAGEngine {
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// 创建知识库
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createDataset(name: string): Promise<string>;
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// 上传文档
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uploadDocument(datasetId: string, file: File): Promise<string>;
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// 语义检索
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search(datasetId: string, query: string, topK?: number): Promise<SearchResult[]>;
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// RAG问答
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chatWithRAG(datasetId: string, query: string): Promise<string>;
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}
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```
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---
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## 📈 优化成果
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**检索参数优化：**
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| 指标 | 优化前 | 优化后 | 提升 |
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|------|--------|--------|------|
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| 检索数量 | 3 chunks | 15 chunks | 5倍 |
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| Chunk大小 | 500 tokens | 1500 tokens | 3倍 |
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| 总覆盖 | 1,500 tokens | 22,500 tokens | 15倍 |
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| 覆盖率 | ~5% | ~40-50% | 8-10倍 |
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---
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## 🔗 相关文档
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- [通用能力层总览](../README.md)
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- [Dify集成文档](../../00-系统总体设计/03-数据库架构说明.md)
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---
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**最后更新：** 2025-11-06
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**维护人：** 技术架构师
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