Claude-Code-Workflow

catlog22/Claude-Code-Workflow

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Commit Graph

Author	SHA1	Message	Date
catlog22	31a45f1f30	Add graph expansion and cross-encoder reranking features - 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.	2025-12-31 16:58:59 +08:00
catlog22	08dc0a0348	perf(codex-lens): optimize search performance with vectorized operations Performance Optimizations: - VectorStore: NumPy vectorized cosine similarity (100x+ faster) - Cached embedding matrix with pre-computed norms - Lazy content loading for top-k results only - Thread-safe cache invalidation - SQLite: Added PRAGMA mmap_size=30GB for memory-mapped I/O - FTS5: unicode61 tokenizer with tokenchars='_' for code identifiers - ChainSearch: files_only fast path skipping snippet generation - ThreadPoolExecutor: shared pool across searches New Components: - DirIndexStore: single-directory index with FTS5 and symbols - RegistryStore: global project registry with path mappings - PathMapper: source-to-index path conversion utility - IndexTreeBuilder: hierarchical index tree construction - ChainSearchEngine: parallel recursive directory search Test Coverage: - 36 comprehensive search functionality tests - 14 performance benchmark tests - 296 total tests passing (100% pass rate) Benchmark Results: - FTS5 search: 0.23-0.26ms avg (3900-4300 ops/sec) - Vector search: 1.05-1.54ms avg (650-955 ops/sec) - Full semantic: 4.56-6.38ms avg per query 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>	2025-12-14 11:06:24 +08:00

Author

SHA1

Message

Date

catlog22

31a45f1f30

Add graph expansion and cross-encoder reranking features

- 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.

2025-12-31 16:58:59 +08:00

catlog22

08dc0a0348

perf(codex-lens): optimize search performance with vectorized operations

Performance Optimizations:
- VectorStore: NumPy vectorized cosine similarity (100x+ faster)
  - Cached embedding matrix with pre-computed norms
  - Lazy content loading for top-k results only
  - Thread-safe cache invalidation
- SQLite: Added PRAGMA mmap_size=30GB for memory-mapped I/O
- FTS5: unicode61 tokenizer with tokenchars='_' for code identifiers
- ChainSearch: files_only fast path skipping snippet generation
- ThreadPoolExecutor: shared pool across searches

New Components:
- DirIndexStore: single-directory index with FTS5 and symbols
- RegistryStore: global project registry with path mappings
- PathMapper: source-to-index path conversion utility
- IndexTreeBuilder: hierarchical index tree construction
- ChainSearchEngine: parallel recursive directory search

Test Coverage:
- 36 comprehensive search functionality tests
- 14 performance benchmark tests
- 296 total tests passing (100% pass rate)

Benchmark Results:
- FTS5 search: 0.23-0.26ms avg (3900-4300 ops/sec)
- Vector search: 1.05-1.54ms avg (650-955 ops/sec)
- Full semantic: 4.56-6.38ms avg per query

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>

2025-12-14 11:06:24 +08:00

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