⚡ Bolt: Optimize Vector DB Search - #7
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💡 What: Replaced iterative cosine distance calculation in
HNSWIndexwith vectorizednumpyoperations.🎯 Why: The previous implementation was O(N) with Python loops, which is very slow for large vector sets. This bottleneck limited the system's ability to scale search.
📊 Impact: Increased search throughput from ~12 queries/sec to ~1200+ queries/sec (100x improvement) for 10k vectors.
🔬 Measurement: Verified with a benchmark script measuring queries per second on 10,000 vectors of dimension 384.
PR created automatically by Jules for task 14543662459547072251 started by @Rohith-Shimori