隐私优先个人知识库搭建与AI增强检索方案

You are a Knowledge Management Systems Architect with deep expertise in privacy-first, self-hosted solutions.

Design a complete personal knowledge management system that keeps ALL data local while leveraging AI for enhanced retrieval and organization.

Requirements

• Privacy level: [strict local-only / local-first with optional sync / hybrid]
• Content types: [notes, PDFs, bookmarks, code snippets, images, voice memos]
• Platforms: [macOS + iOS / Windows + Android / Linux + Web]
• Estimated knowledge base size: [e.g., 10K notes, 500 PDFs]

Please Design

1. Storage Architecture

• File format strategy (Markdown-first with frontmatter)
• Directory structure and naming conventions
• Attachment handling and deduplication
• Version control integration (git-based)
• Backup and disaster recovery plan

2. Local AI Integration

• Embedding model selection (size vs quality tradeoff)
• Vector database selection (SQLite-vec / Qdrant / ChromaDB)
• Indexing pipeline: document -> chunk -> embed -> store
• Incremental re-indexing strategy

3. Semantic Search and Retrieval

• Hybrid search: keyword (BM25) + semantic (vector) + graph
• Query expansion and reranking pipeline
• Multi-modal search (text -> find related images/PDFs)
• Search result ranking formula with weights

4. Automated Organization

• Auto-tagging pipeline using local LLM
• Bi-directional link suggestion algorithm
• Knowledge graph extraction (entities + relations)
• Daily/weekly auto-generated knowledge digests
• Duplicate and near-duplicate detection

5. AI-Powered Features

• Local RAG for Q&A over personal knowledge base
• Smart summarization of long documents
• Spaced repetition integration for learning
• Writing assistant with context from your notes
• Meeting notes to action items extraction

6. Sync and Sharing (Privacy-Preserving)

• End-to-end encrypted sync options
• Selective sharing with zero-knowledge architecture
• Export formats (HTML, PDF, EPUB)
• Migration path from Notion/Obsidian/Evernote

7. Implementation Stack

• Recommended tools with alternatives
• Docker Compose configuration
• Resource requirements (RAM, storage, GPU optional)
• Step-by-step setup guide

Provide concrete configuration files, shell commands, and code snippets for each component.