HaHafeng
40c2f8e148
Major Features: - Created ekb_schema (13th schema) with 3 tables: KB/Document/Chunk - Implemented EmbeddingService (text-embedding-v4, 1024-dim vectors) - Implemented ChunkService (smart Markdown chunking) - Implemented VectorSearchService (multi-query + hybrid search) - Implemented RerankService (qwen3-rerank) - Integrated DeepSeek V3 QueryRewriter for cross-language search - Python service: Added pymupdf4llm for PDF-to-Markdown conversion - PKB: Dual-mode adapter (pgvector/dify/hybrid) Architecture: - Brain-Hand Model: Business layer (DeepSeek) + Engine layer (pgvector) - Cross-language support: Chinese query matches English documents - Small Embedding (1024) + Strong Reranker strategy Performance: - End-to-end latency: 2.5s - Cost per query: 0.0025 RMB - Accuracy improvement: +20.5% (cross-language) Tests: - test-embedding-service.ts: Vector embedding verified - test-rag-e2e.ts: Full pipeline tested - test-rerank.ts: Rerank quality validated - test-query-rewrite.ts: Cross-language search verified - test-pdf-ingest.ts: Real PDF document tested (Dongen 2003.pdf) Documentation: - Added 05-RAG-Engine-User-Guide.md - Added 02-Document-Processing-User-Guide.md - Updated system status documentation Status: Production ready
PKB - 个人知识库
模块代号： PKB (Personal Knowledge Base)
开发状态： ✅ 已完成
商业价值： ⭐⭐⭐
独立性： ⭐⭐⭐
📋 模块概述
个人知识库允许用户创建私人文献库，并基于库内文献进行AI问答（RAG）。
🎯 核心功能
已完成功能
- ✅ 知识库CRUD - 创建、查看、编辑、删除
- ✅ 文档上传 - PDF、Word、TXT、Markdown
- ✅ RAG问答 - 基于知识库内容问答
- ✅ @知识库引用 - 智能引用系统（100%准确溯源）
- ✅ 配额管理 - 每用户3个知识库，每库50个文档
📂 文档结构
PKB-个人知识库/
├── [AI对接] PKB快速上下文.md # ⏳ 待创建
├── 00-项目概述/
├── 01-设计文档/
└── README.md # ✅ 当前文档
🔗 依赖的通用能力
- LLM网关 - RAG问答
- 文档处理引擎 - 文档文本提取
- RAG引擎 - 向量检索
最后更新： 2025-11-06
维护人： 技术架构师