⚡ Bolt: Optimize AdaptiveMemory with persistent WAL connection - #18
⚡ Bolt: Optimize AdaptiveMemory with persistent WAL connection#18google-labs-jules[bot] wants to merge 1 commit into
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- Replaced per-call SQLite connection with a persistent connection in `AdaptiveMemory`. - Enabled WAL mode (`PRAGMA journal_mode=WAL`) and `synchronous=NORMAL` for improved write performance. - Added `threading.RLock` to ensure thread safety with the persistent connection. - Refactored `AdaptiveMemory.__init__` to accept `db_path` for better testability. - Measured ~15x performance improvement in `add_memory` (from ~2.92ms to ~0.19ms per call).
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💡 What: Optimized
AdaptiveMemoryto use a persistent SQLite connection with Write-Ahead Logging (WAL) mode instead of opening a new connection for every operation.🎯 Why: Creating a new SQLite connection for every memory operation was a significant bottleneck (~2.9ms per call). This overhead accumulates in high-frequency scenarios like chat loops or batch memory processing.
📊 Impact:
add_memoryoperations (reduced from ~2.92ms to ~0.19ms).🔬 Measurement:
Verified using a benchmark script (temporarily created as
tests/benchmark_adaptive_memory.py) running 100 insertions.Tests in
tests/passed successfully.PR created automatically by Jules for task 6568196273460636237 started by @Rohith-Shimori