⚡ Bolt: Optimize AdaptiveMemory with persistent SQLite connection - #3
⚡ Bolt: Optimize AdaptiveMemory with persistent SQLite connection#3google-labs-jules[bot] wants to merge 1 commit into
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💡 What: Refactored `AdaptiveMemory` to initialize a single SQLite connection in `__init__` and reuse it across all methods, instead of opening and closing a new connection for every operation. 🎯 Why: Repeatedly opening and closing SQLite connections incurs significant I/O and locking overhead. This bottleneck was slowing down high-frequency memory operations. 📊 Impact: - Read performance improved by ~400% (5x faster) in benchmarks (from ~0.0240s to ~0.0047s for 100 reads). - Write performance improved by ~20%. 🔬 Measurement: - Verified using a custom benchmark script `benchmark_memory.py`. - Verified correctness with `test_ananta_quick.py` and `comprehensive_test.py`.
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Implemented persistent SQLite connection in
AdaptiveMemoryto improve performance.memory/adaptive_memory.py:self.connin_init_databasewithcheck_same_thread=False.add_memory,get_recent_memories, etc.) to useself.conn.cursor().close()and__del__for proper resource cleanup.sqlite3.Rowfor better row access compatibility.PR created automatically by Jules for task 9109606176507119100 started by @Rohith-Shimori