- 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:
- Ask for pod name and type (scholar/health/shared/projects)
- Run:
python3 .../scripts/pod.py create <name> --type <type> - Confirm creation
2. Add Content (Manual)
When user asks to add content:
- Ask for pod name, title, content, tags
- Run:
python3 .../scripts/pod.py add <pod> --title "<title>" --content "<content>" --tags "<tags>" - Confirm
3. Ingest Documents (Automated)
When user wants to ingest files:
- Ask for pod name and folder path
- Run:
python3 .../scripts/ingest.py ingest <pod> <folder> - Supports: PDF, TXT, MD, DOCX, PNG, JPG
- Auto-embeds text (if sentence-transformers installed)
4. Semantic Search
When user wants to search:
- Ask for pod name and query
- Run:
python3 .../scripts/ingest.py search <pod> "<query>" - Returns ranked results with citations
5. Query (Basic)
When user asks to search notes:
- Run:
python3 .../scripts/pod.py query <pod> --text "<query>"
6. Export
When user asks to export:
- Run:
python3 .../scripts/podsync.py pack <pod>
Dependencies
pip install PyPDF2 python-docx pillow pytesseract sentence-transformersStorage Location
~/.openclaw/data-pods/
Key Commands
# 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