- Introduced a comprehensive design document for a Code Semantic Graph aimed at enhancing static analysis capabilities.
- Defined the architecture, core components, and implementation steps for analyzing function calls, data flow, and dependencies.
- Included detailed specifications for nodes and edges in the graph, along with database schema for storage.
- Outlined phases for implementation, technical challenges, success metrics, and application scenarios.
- Added active memory configuration for manual interval and Gemini tool.
- Created file modification rules for handling edits and writes.
- Implemented migration manager for managing database schema migrations.
- Added migration 001 to normalize keywords into separate tables.
- Developed tests for validating performance optimizations including keyword normalization, path lookup, and symbol search.
- Created validation script to manually verify optimization implementations.
- Implement full coverage tests for Embedder model loading and embedding generation
- Add CRUD operations and caching tests for VectorStore
- Include cosine similarity computation tests
- Validate semantic search accuracy and relevance through various queries
- Establish performance benchmarks for embedding and search operations
- Ensure edge cases and error handling are covered
- Test thread safety and concurrent access scenarios
- Verify availability of semantic search dependencies
