- [x] Add AST-aware code chunking for Go, Python, and TypeScript using tree-sitter
- [x] Implement LEANN-inspired hybrid vector storage with hub detection and selective embedding storage (60-80% savings)
- [x] Add observation relationship graph with CSR format and edge detection (file overlap, semantic similarity, temporal, concept)
- [x] Implement graph-aware search with two-level traversal and relationship-based ranking
- [x] Add auto-tuning system for dynamic hub threshold adjustment based on query performance
- [x] Add comprehensive metrics tracking for vector storage, queries, latency, and graph traversals
- [x] Update configuration system with graph and hybrid storage settings
- [x] Add graph stats and vector metrics endpoints to worker service
- [x] Enhance UI sidebar with advanced metrics display and graph visualization
- [x] Optimize struct field alignment throughout codebase for memory efficiency
- [x] Update documentation with LEANN Phase 2 features and performance benefits
- [x] Add tree-sitter dependency for AST parsing
* Resolves issue #13
- Switched model to bge-small-en-v1.5
- Added lazy re-embedding
- Added model version tracking per vector
- Added conversion of vectors to the new model
* Add lfs support to the workflow.
* Implements importance scoring with decay + voting #6
* Resolves issue #5 by marking observations as superseeded and scheduled for deletion
* Implement pattern detection #7
* Improve injections and observations accuracy
- Session start: Recent observations for project context (recency-based)
- User prompt: Semantically relevant observations (similarity-based with threshold)
* Added two stage retrieval with bi and cross encoder #8
* Implement query expansion and reformulation #9
* Knowledge graph and relationships ( resolves#4 )
- File Overlap Detection: Detects relationships when observations modify/read the same files
- Concept Overlap Detection: Detects relationships based on shared semantic concepts
- Type Progression Detection: Infers relationships from natural observation type progressions (e.g., discovery → bugfix = "fixes")
- Temporal Proximity Detection: Detects relationships between observations in the same session within 5 minutes
- Narrative Mention Detection: Detects explicit relationship language in narratives (e.g., "fixes", "depends on", "supersedes")
* Add visualisation of the relations to the dashboard.
* fixup! Add visualisation of the relations to the dashboard.
* Update documentation with new settings and screenshots.
lukaszraczylo