Privacy-first personal knowledge base construction and AI-enhanced search solutions

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.