Optimize LLM tool call execution and multi-repo searches

src/pipelines/code_retrieval.py

@@ -25,6 +25,7 @@
 
 from __future__ import annotations
 
+import asyncio
 import logging
 from typing import Any, Callable, Dict, List, Optional
 
@@ -37,7 +38,6 @@
 from src.scanner.code_store import CodeStore
 from src.schemas.code import (
     annotations_namespace,
-    directories_namespace,
     files_namespace,
     snippets_namespace,
     symbols_namespace,
@@ -375,18 +375,22 @@ async def run(
             turn_records: List[SourceRecord] = []
             only_read_tools = True
 
-            for tc in ai_response.tool_calls:
+            async def _process_tool_call(tc):
                 tool_name = tc["name"]
                 tool_args = tc["args"]
                 tool_id = tc["id"]
-
                 t1 = _time.perf_counter()
                 records = await self._execute_tool(
                     tool_name, tool_args, repo=repo, top_k=top_k,
                     user_id=user_id,
                 )
                 tool_ms = (_time.perf_counter() - t1) * 1000
                 logger.info("  Tool: %s(%s) → %d results (%.0fms)", tool_name, tool_args, len(records), tool_ms)
+                return tool_name, tool_args, tool_id, records
+
+            tool_results = await asyncio.gather(*[_process_tool_call(tc) for tc in ai_response.tool_calls])
+
+            for tool_name, tool_args, tool_id, records in tool_results:
                 turn_records.extend(records)
                 sources.extend(records)
 
@@ -471,17 +475,20 @@ async def run_stream(
         if ai_response.tool_calls:
             yield json.dumps({"type": "status", "content": f"Running {len(ai_response.tool_calls)} search tool(s)..."}) + "\n"
 
-            for tc in ai_response.tool_calls:
+            async def _process_tool_call_stream(tc):
                 tool_name = tc["name"]
                 tool_args = tc["args"]
                 tool_id = tc["id"]
-
                 logger.info("  Tool: %s(%s)", tool_name, tool_args)
-
                 records = await self._execute_tool(
                     tool_name, tool_args, repo=repo, top_k=top_k,
                     user_id=user_id,
                 )
+                return tool_name, tool_args, tool_id, records
+
+            tool_results = await asyncio.gather(*[_process_tool_call_stream(tc) for tc in ai_response.tool_calls])
+
+            for tool_name, tool_args, tool_id, records in tool_results:
                 sources.extend(records)
 
                 tool_result_text = self._format_tool_results(records)
@@ -589,14 +596,17 @@ async def _search_symbols(
     ) -> List[SourceRecord]:
         if not repo:
             logger.warning("search_symbols called without repo — searching all repos")
-            results = []
-            for r in self.repos:
-                results.extend(await self._search_namespace(
+            tasks = [
+                self._search_namespace(
                     namespace=symbols_namespace(self.org_id, r),
                     query=query,
                     domain="symbol",
                     top_k=top_k,
-                ))
+                )
+                for r in self.repos
+            ]
+            results_list = await asyncio.gather(*tasks)
+            results = [item for sublist in results_list for item in sublist]
             return results[:top_k]
 
         return await self._search_namespace(
@@ -612,14 +622,17 @@ async def _search_files(
         self, query: str, repo: str, top_k: int = 10,
     ) -> List[SourceRecord]:
         if not repo:
-            results = []
-            for r in self.repos:
-                results.extend(await self._search_namespace(
+            tasks = [
+                self._search_namespace(
                     namespace=files_namespace(self.org_id, r),
                     query=query,
                     domain="file",
                     top_k=top_k,
-                ))
+                )
+                for r in self.repos
+            ]
+            results_list = await asyncio.gather(*tasks)
+            results = [item for sublist in results_list for item in sublist]
             return results[:top_k]
 
         return await self._search_namespace(

src/pipelines/retrieval.py

@@ -20,8 +20,8 @@
 
 from __future__ import annotations
 
+import asyncio
 import logging
-import os
 from typing import Any, Callable, Dict, List, Optional
 
 from dotenv import load_dotenv
@@ -177,16 +177,20 @@ async def run(
 
         if ai_response.tool_calls:
             called_tools = set()
-            for tc in ai_response.tool_calls:
+
+            async def _process_tool_call(tc):
                 tool_name = tc["name"]
                 tool_args = tc["args"]
                 tool_id = tc["id"]
-
                 logger.info("  Tool call: %s(%s)", tool_name, tool_args)
-
                 records = await self._execute_tool(
                     tool_name, tool_args, user_id, top_k,
                 )
+                return tool_name, tool_args, tool_id, records
+
+            tool_results = await asyncio.gather(*[_process_tool_call(tc) for tc in ai_response.tool_calls])
+
+            for tool_name, tool_args, tool_id, records in tool_results:
                 sources.extend(records)
 
                 # Build ToolMessage for the LLM