perf: Tier 2 optimizations - vector reset and file caching#180
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Two performance optimizations (removed module map change after benchmarking
showed pathlib overhead made it slower):
1. Vector search collection reset (vector_searcher.py)
- Track reset state to avoid redundant resets on multiple add() calls
- Use delete_collection as primary fast path (avoids count() call)
- Only fall back to expensive ID enumeration when necessary
- ~2-5x faster build_index() restarts
2. Context extractor file caching (context_extractor.py)
- Add mtime-based file content cache shared across methods
- chunk_file_by_lines, chunk_file_by_symbols, extract_context_around_line
now share cached file reads
- Simple FIFO eviction when cache exceeds 100 files
- 10-94x faster for repeated reads of same file
Benchmark results:
- File caching: 10x speedup (10 reads), 94x speedup (100 reads)
- Context extractor: 0.88ms avg per call with caching enabled
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Summary
Two performance optimizations from Tier 2 (removed module map change after benchmarking showed pathlib overhead made it slower):
1. Vector search collection reset (
vector_searcher.py)add()callsdelete_collectionas primary fast path (avoidscount()call)build_index()restarts2. Context extractor file caching (
context_extractor.py)chunk_file_by_lines,chunk_file_by_symbols,extract_context_around_linenow share cached file readsBenchmark Results
File Caching (synthetic)
Real-world (kit codebase)
Removed
os.path.dirname()loops. The theoretical O(n²) → O(n) improvement was overwhelmed by constant factors.Test plan