Create and manage modular portable database pods (SQLite + metadata + embeddings). Includes document ingestion with embeddings for semantic search. Full auto...
--- name: data-pods description: Create and manage modular portable database pods (SQLite + metadata + embeddings). Includes document ingestion with embeddings for semantic search. Full automation - just ask. --- # Data Pods ## Overview Create and manage portable, consent-scoped database pods. Handles document ingestion with embeddings and semantic search. ## Architecture ``` ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │ Ingestion │ ──► │ DB Pods │ ──► │ Generation │ │ (ingest) │ │ (storage) │ │ (query) │ └─────────────┘ └─────────────┘ └─────────────┘ ``` ## Triggers - "create a pod" / "new pod" - "list my pods" / "what pods do I have" - "add to pod" / "add note" / "add content" - "query pod" / "search pod" - "ingest documents" / "add files" - "semantic search" / "find相关内容" - "export pod" / "pack pod" ## Core Features ### 1. Create Pod When user asks to create a pod: 1. Ask for pod name and type (scholar/health/shared/projects) 2. Run: `python3 .../scripts/pod.py create <name> --type <type>` 3. Confirm creation ### 2. Add Content (Manual) When user asks to add content: 1. Ask for pod name, title, content, tags 2. Run: `python3 .../scripts/pod.py add <pod> --title "<title>" --content "<content>" --tags "<tags>"` 3. Confirm ### 3. Ingest Documents (Automated) When user wants to ingest files: 1. Ask for pod name and folder path 2. Run: `python3 .../scripts/ingest.py ingest <pod> <folder>` 3. Supports: PDF, TXT, MD, DOCX, PNG, JPG 4. Auto-embeds text (if sentence-transformers installed) ### 4. Semantic Search When user wants to search: 1. Ask for pod name and query 2. Run: `python3 .../scripts/ingest.py search <pod> "<query>"` 3. Returns ranked results with citations ### 5. Query (Basic) When user asks to search notes: 1. Run: `python3 .../scripts/pod.py query <pod> --text "<query>"` ### 6. Export When user asks to export: 1. Run: `python3 .../scripts/podsync.py pack <pod>` ## Dependencies ```bash pip install PyPDF2 python-docx pillow pytesseract sentence-transformers ``` ## Storage Location `~/.openclaw/data-pods/` ## Key Commands ```bash # Create pod python3 .../scripts/pod.py create research --type scholar # Add note python3 .../scripts/pod.py add research --title "..." --content "..." --tags "..." # Ingest folder python3 .../scripts/ingest.py ingest research ./documents/ # Semantic search python3 .../scripts/ingest.py search research "transformers" # List documents python3 .../scripts/ingest.py list research # Query notes python3 .../scripts/pod.py query research --text "..." ``` ## Notes - Ingestion auto-chunks large documents - Embeddings enable semantic search - File hash prevents duplicate ingestion - All data stored locally in SQLite
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