⚡ Bolt: [Graph Entity Similarity Search Optimization]

[Theory903]

💡 What: The optimization replaces the N+1 query loop in find_similar_entities with a single, efficient SQL CTE.
🎯 Why: The previous code looped over potentially thousands of candidate entities to calculate Jaccard similarities, hitting the database repeatedly and causing severe bottleneck performance degradation in large graphs.
📊 Impact: The performance was measured using a benchmarking script running on 1000 generated items. The initial runtime was approximately 1.01 seconds. The execution time of the refactored code dropped down to approximately ~0.03 seconds (measured: 0.0362s), yielding a roughly 96% reduction in query latency.
🔬 Measurement: Python script querying SQLite populated with synthetic dense relationships over 1000 nodes, resulting in 999 similarities returned.

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PR created automatically by Jules for task 6991095973470980475 started by @Theory903

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ℹ️ Review info

⚙️ Run configuration

Configuration used: defaults

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Run ID: 6541d2cd-34bd-4451-8075-c843317fcd2c

📥 Commits

Reviewing files that changed from the base of the PR and between 29c13ba and 119cc34.

📒 Files selected for processing (2)

• .jules/bolt.md
• src/ippoc/mnemosyne/graph/manager.py

✨ Finishing Touches

🧪 Generate unit tests (beta)

• Create PR with unit tests
• Commit unit tests in branch perf/graph-similarity-optimization-6991095973470980475

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