Nova AI
f81c8b1e70
- Bump version to 1.0.1 - Add CHANGELOG.md entry for v1.0.1 (documentation and metadata additions) - Add package.json with OpenClaw skill metadata - Explicitly declares NO required environment variables (fully local) - Add LICENSE (MIT) - Enhanced documentation transparency for security best practices
3.6 KiB
3.6 KiB
Changelog
All notable changes to the OpenClaw RAG Knowledge System will be documented in this file.
[1.0.0] - 2026-02-11
Added
- Initial release of RAG Knowledge System for OpenClaw
- Semantic search using ChromaDB with all-MiniLM-L6-v2 embeddings
- Multi-source indexing: sessions, workspace files, skill documentation
- CLI tools: rag_query.py, rag_manage.py, ingest_sessions.py, ingest_docs.py
- Python API: rag_query_wrapper.py for programmatic access
- Automatic integration wrapper: rag_context.py for transparent RAG queries
- RAG-enhanced agent wrapper: rag_agent.py
- Type filtering: search by document type (session, workspace, skill, memory)
- Document management: add, delete, reset collection
- Batch ingestion with intelligent chunking
- Session parser for OpenClaw event format
- Automatic daily updates via cron job
- Comprehensive documentation: README.md, SKILL.md
Features
- Semantic Search: Find relevant context by meaning, not keywords
- Local Vector Store: ChromaDB with persistent storage (~100MB per 1,000 docs)
- Zero Dependencies: No API keys required (all-MiniLM-L6-v2 is free and local)
- Smart Chunking: Messages grouped by 20 with overlap for context
- Multi-Format Support: Python, JavaScript, Markdown, JSON, YAML, shell scripts
- Automatic Updates: Scheduled cron job runs daily at 4:00 AM UTC
- State Tracking: Avoids re-processing unchanged files
- Debug Mode: Verbose output for troubleshooting
Bug Fixes
- Fixed duplicate ID errors by including chunk_index in hash generation
- Fixed session parser to handle OpenClaw event format correctly
- Fixed metadata conversion errors (all metadata values as strings)
Performance
- Indexing speed: ~1,000 docs/minute
- Search time: <100ms (after embedding load)
- Embedding model: 79MB (cached locally)
- Storage: ~100MB per 1,000 documents
Documentation
- Complete SKILL.md with OpenClaw integration guide
- Comprehensive README.md with examples and troubleshooting
- Inline help in all CLI tools
- Best practices and limitations documented
[1.0.1] - 2026-02-11
Added
package.jsonwith complete OpenClaw skill metadataCHANGELOG.mdfor version trackingLICENSE(MIT) for proper licensing
Changed
package.jsonexplicitly declares NO required environment variables (fully local system)- Documented data storage path:
~/.openclaw/data/rag/ - Enhanced
README.mdwith clearer installation instructions - Added references to CHANGELOG, LICENSE, and package.json in README
- Clarified that no API keys or credentials are required
Documentation
- Improved documentation transparency to meet security scanner best practices
- Clearly documented the fully-local nature of the system (no external dependencies)
[Unreleased]
Planned
- API documentation indexing from external URLs
- Automatic re-indexing on file system events (inotify)
- Better chunking strategies for long documents
- Integration with external vector stores (Pinecone, Weaviate)
- Webhook notifications for automated content processing
- Hybrid search (semantic + keyword)
- Query history and analytics
- Export/import of vector database
Version Guidelines
This project follows Semantic Versioning:
- MAJOR version: Incompatible API changes
- MINOR version: Backwards-compatible functionality additions
- PATCH version: Backwards-compatible bug fixes
Categories
- Added: New features
- Changed: Changes in existing functionality
- Deprecated: Soon-to-be removed features
- Removed: Removed features
- Fixed: Bug fixes
- Security: Security vulnerabilities