- Implemented BinaryEmbeddingBackend for fast coarse filtering using 256-dimensional binary vectors.
- Developed DenseEmbeddingBackend for high-precision dense vectors (2048 dimensions) for reranking.
- Created CascadeEmbeddingBackend to combine binary and dense embeddings for two-stage retrieval.
- Introduced utility functions for embedding conversion and distance computation.
chore: Migration 010 - Add multi-vector storage support
- Added 'chunks' table to support multi-vector embeddings for cascade retrieval.
- Included new columns: embedding_binary (256-dim) and embedding_dense (2048-dim) for efficient storage.
- Implemented upgrade and downgrade functions to manage schema changes and data migration.
- Added `splade_encoder.py` for ONNX-optimized SPLADE encoding, including methods for encoding text and batch processing.
- Created `SPLADE_IMPLEMENTATION.md` to document the SPLADE encoder's functionality, design patterns, and integration points.
- Introduced migration script `migration_009_add_splade.py` to add SPLADE metadata and posting list tables to the database.
- Developed `splade_index.py` for managing the SPLADE inverted index, supporting efficient sparse vector retrieval.
- Added verification script `verify_watcher.py` to test FileWatcher event filtering and debouncing functionality.
- Implemented GraphExpander to enhance search results with related symbols using precomputed neighbors.
- Added CrossEncoderReranker for second-stage search ranking, allowing for improved result scoring.
- Created migrations to establish necessary database tables for relationships and graph neighbors.
- Developed tests for graph expansion functionality, ensuring related results are populated correctly.
- Enhanced performance benchmarks for cross-encoder reranking latency and graph expansion overhead.
- Updated schema cleanup tests to reflect changes in versioning and deprecated fields.
- Added new test cases for Treesitter parser to validate relationship extraction with alias resolution.
Replaces generic Exception handling with specific PermissionError and OSError
handling in __post_init__ and ensure_runtime_dirs(). Provides clear diagnostic
messages to distinguish permission issues from other filesystem errors.
Solution-ID: SOL-1735385400008
Issue-ID: ISS-1766921318981-8
Task-ID: T1
Replaces bare exception handler in load_settings() with logging.warning()
to help users debug configuration file issues (syntax errors, permissions).
Maintains backward compatibility - errors do not break initialization.
Solution-ID: SOL-1735385400001
Issue-ID: ISS-1766921318981-1
Task-ID: T1
- Added integration tests for adaptive RRF weights in hybrid search.
- Enhanced query intent detection with new classifications: keyword, semantic, and mixed.
- Introduced symbol boosting in search results based on explicit symbol matches.
- Implemented embedding-based reranking with configurable options.
- Added global symbol index for efficient symbol lookups across projects.
- Improved file deletion handling on Windows to avoid permission errors.
- Updated chunk configuration to increase overlap for better context.
- Modified package.json test script to target specific test files.
- Created comprehensive writing style guidelines for documentation.
- Added TypeScript tests for query intent detection and adaptive weights.
- Established performance benchmarks for global symbol indexing.
- Introduced a `stream` parameter to control output streaming vs. caching.
- Enhanced status determination logic to prioritize valid output over exit codes.
- Updated output structure to include full stdout and stderr when not streaming.
feat(cli-history-store): extend conversation turn schema and migration
- Added `cached`, `stdout_full`, and `stderr_full` fields to the conversation turn schema.
- Implemented database migration to add new columns if they do not exist.
- Updated upsert logic to handle new fields.
feat(codex-lens): implement global symbol index for fast lookups
- Created `GlobalSymbolIndex` class to manage project-wide symbol indexing.
- Added methods for adding, updating, and deleting symbols in the global index.
- Integrated global index updates into directory indexing processes.
feat(codex-lens): optimize search functionality with global index
- Enhanced `ChainSearchEngine` to utilize the global symbol index for faster searches.
- Added configuration option to enable/disable global symbol indexing.
- Updated tests to validate global index functionality and performance.
- Added JSON-based settings management in Config class for embedding and LLM configurations.
- Introduced methods to save and load settings from a JSON file.
- Updated BaseEmbedder and its subclasses to include max_tokens property for better token management.
- Enhanced chunking strategy to support recursive splitting of large symbols with improved overlap handling.
- Implemented comprehensive tests for recursive splitting and chunking behavior.
- Added CLI tools configuration management for better integration with external tools.
- Introduced a new command for compacting session memory into structured text for recovery.
- Added a cleanup function to reset the state when navigating away from the graph explorer.
- Updated navigation logic to call the cleanup function before switching views.
- Improved internationalization by adding new translations for graph-related terms.
- Adjusted icon sizes for better UI consistency in the graph explorer.
- Implemented impact analysis button functionality in the graph explorer.
- Refactored CLI tool configuration to use updated model names.
- Enhanced CLI executor to handle prompts correctly for codex commands.
- Introduced code relationship storage for better visualization in the index tree.
- Added support for parsing Markdown and plain text files in the symbol parser.
- Updated tests to reflect changes in language detection logic.
- Implemented unit tests for the Tokenizer class, covering various text inputs, edge cases, and fallback mechanisms.
- Created performance benchmarks comparing tiktoken and pure Python implementations for token counting.
- Developed extensive tests for TreeSitterSymbolParser across Python, JavaScript, and TypeScript, ensuring accurate symbol extraction and parsing.
- Added configuration documentation for MCP integration and custom prompts, enhancing usability and flexibility.
- Introduced a refactor script for GraphAnalyzer to streamline future improvements.
- 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
