⚡ Bolt: concurrent LLM tool execution in retrieval pipelines#111
⚡ Bolt: concurrent LLM tool execution in retrieval pipelines#111ishaanxgupta wants to merge 1 commit intomainfrom
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Wrapped tool call execution in helper async functions and utilized asyncio.gather to fetch tools concurrently. This reduces I/O bound bottlenecks across the retrieval pipeline while preserving proper aggregation and ordering of context messages.
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💡 What: Refactored LLM tool execution logic in
src/pipelines/code_retrieval.pyandsrc/pipelines/retrieval.pyto execute concurrently usingasyncio.gather.🎯 Why: Tool calls were executed sequentially within a loop. By executing them concurrently, the I/O-bound latency incurred when the LLM requested multiple search tools simultaneously is significantly reduced.
📊 Impact: Pipeline response time will be noticeably faster when resolving multi-tool query inputs, as wait times are now bounded by the single slowest search tool instead of the cumulative sum of all invoked search tools.
🔬 Measurement: Can be verified by observing the total
llm_msturnaround time across LLM tool call loops versus sequentially processing large search sweeps on multiple domains at the same time.PR created automatically by Jules for task 16229732312529966654 started by @ishaanxgupta