⚡ Bolt: [performance improvement] Concurrent tool execution in Retrieval Pipelines

[ishaanxgupta]

💡 What: The optimization refactors sequential for loops into concurrent execution using asyncio.gather for LLM tool executions (_execute_tool) in both RetrievalPipeline and CodeRetrievalPipeline. It also refactors _search_symbols and _search_files to search multiple repositories in parallel.

🎯 Why: When an LLM decides to use multiple tools (e.g., searching for semantic vectors, asking a graph database, looking up profiles), these calls are independent. Sequentially executing them in a for loop unnecessarily throttles the process and compounds external latency. Fetching them concurrently hides the latency behind the slowest request.

📊 Impact: Reduces total tool execution time significantly. If the LLM makes 3 tool calls taking 200ms, 300ms, and 400ms respectively, the wait time drops from ~900ms to ~400ms. Similarly, querying 5 repositories will now be as fast as the single slowest repository query.

🔬 Measurement: Use telemetry logs; trace the elapsed time tool_ms for tool execution blocks and note the overall turn execution time dropping linearly with the number of parallel tools called.

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PR created automatically by Jules for task 3952276918833983431 started by @ishaanxgupta

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