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4061ae48c4
- 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.
42 lines
1.9 KiB
Markdown
42 lines
1.9 KiB
Markdown
# CodexLens – Optimization Plan Changelog
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This changelog tracks the **CodexLens optimization plan** milestones (not the Python package version in `pyproject.toml`).
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## v1.0 (Optimization) – 2025-12-26
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### Optimizations
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1. **P0: Context-aware hybrid chunking**
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- Docstrings are extracted into dedicated chunks and excluded from code chunks.
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- Docstring chunks include `parent_symbol` metadata when the docstring belongs to a function/class/method.
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- Sliding-window chunk boundaries are deterministic for identical input.
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2. **P1: Adaptive RRF weights (QueryIntent)**
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- Query intent is classified as `keyword` / `semantic` / `mixed`.
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- RRF weights adapt to intent:
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- `keyword`: exact-heavy (favors lexical matches)
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- `semantic`: vector-heavy (favors semantic matches)
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- `mixed`: keeps base/default weights
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3. **P2: Symbol boost**
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- Fused results with an explicit symbol match (`symbol_name`) receive a multiplicative boost (default `1.5x`).
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4. **P2: Embedding-based re-ranking (optional)**
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- A second-stage ranker can reorder top results by semantic similarity.
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- Re-ranking runs only when `Config.enable_reranking=True`.
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5. **P3: Global symbol index (incremental + fast path)**
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- `GlobalSymbolIndex` stores project-wide symbols in one SQLite DB for fast symbol lookups.
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- `ChainSearchEngine.search_symbols()` uses the global index fast path when enabled.
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### Migration Notes
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- **Reindexing (recommended)**: deterministic chunking and docstring metadata affect stored chunks. For best results, regenerate indexes/embeddings after upgrading:
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- Rebuild indexes and/or re-run embedding generation for existing projects.
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- **New config flags**:
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- `Config.enable_reranking` (default `False`)
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- `Config.reranking_top_k` (default `50`)
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- `Config.symbol_boost_factor` (default `1.5`)
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- `Config.global_symbol_index_enabled` (default `True`)
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- **Breaking changes**: none (behavioral improvements only).
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