⚡ Bolt: [performance improvement] Concurrent tool execution in Retrieval Pipeline#81
⚡ Bolt: [performance improvement] Concurrent tool execution in Retrieval Pipeline#81ishaanxgupta wants to merge 1 commit intomainfrom
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…val Pipeline Replaced sequential `await` execution of LLM-requested tool calls (e.g., `search_temporal`, `search_profile`) with `asyncio.gather` for concurrent execution. Kept list appending sequential to guarantee order stability. Added learning to `.jules/bolt.md`.
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💡 What: The optimization changes the
RetrievalPipeline.runmethod so that when the LLM requests multiple tools to be executed, they are run concurrently usingasyncio.gatherinstead of sequentially awaiting each one in aforloop.🎯 Why: When the LLM decides to hit multiple data sources (e.g., querying Pinecone for a profile and Neo4j for a temporal event), waiting for one network call to finish before starting the next scales pipeline latency linearly with the number of tools requested.
📊 Impact: Reduces tool execution latency inside the Retrieval pipeline from$O(N)$ to $O(1)$ relative to the number of tool calls, bounded by the slowest individual request. In a simulated benchmark involving 4 requested tools, concurrent execution was measured to drop execution time from ~404ms to ~101ms (a ~75% reduction).
🔬 Measurement: Check the
Retrieval Pipelineoverall response time when asking questions that trigger multiple search tools. You will notice significant speedup in end-to-end latency. Also recorded this insight in.jules/bolt.md.PR created automatically by Jules for task 3660687105885964435 started by @ishaanxgupta