we should always have an executor

Author: KRRT7

codeflash/api/aiservice.py

@@ -35,6 +35,7 @@
     from codeflash.models.models import AIServiceCodeRepairRequest, AIServiceRefinerRequest
     from codeflash.result.explanation import Explanation
 
+
 class AiServiceClient:
     def __init__(self) -> None:
         self.base_url = self.get_aiservice_base_url()
@@ -244,11 +245,11 @@ def optimize_python_code_multi_model(
         dependency_code: str,
         base_trace_id: str,
         model_distribution: list[tuple[str, int]],
+        executor: concurrent.futures.ThreadPoolExecutor,
         experiment_metadata: ExperimentMetadata | None = None,
         *,
         is_async: bool = False,
         sequence_offset: int = 0,
-        executor: concurrent.futures.ThreadPoolExecutor | None = None,
     ) -> tuple[list[OptimizedCandidate], int]:
         """Generate optimizations using multiple models in parallel."""
         logger.info("Generating optimized candidates…")
@@ -295,9 +296,9 @@ def optimize_python_code_line_profiler_multi_model(
         base_trace_id: str,
         line_profiler_results: str,
         model_distribution: list[tuple[str, int]],
+        executor: concurrent.futures.ThreadPoolExecutor,
         experiment_metadata: ExperimentMetadata | None = None,
         sequence_offset: int = 0,
-        executor: concurrent.futures.ThreadPoolExecutor | None = None,
     ) -> tuple[list[OptimizedCandidate], int]:
         """Generate line profiler optimizations using multiple models in parallel."""
         logger.info("Generating optimized candidates with line profiler…")

codeflash/optimization/function_optimizer.py

@@ -955,13 +955,13 @@ def determine_best_candidate(
             base_trace_id=self.get_trace_id(exp_type),
             line_profiler_results=original_code_baseline.line_profile_results["str_out"],
             model_distribution=MODEL_DISTRIBUTION_LP_EFFECTIVE,
+            executor=self.executor,
             experiment_metadata=ExperimentMetadata(
                 id=self.experiment_id, group="control" if exp_type == "EXP0" else "experiment"
             )
             if self.experiment_id
             else None,
             sequence_offset=self.optimize_calls_count,
-            executor=self.executor,
         )
 
         processor = CandidateProcessor(
@@ -1393,10 +1393,10 @@ def generate_optimizations(
             read_only_context_code,
             self.function_trace_id[:-4] + "EXP0" if run_experiment else self.function_trace_id,
             MODEL_DISTRIBUTION_EFFECTIVE,
+            self.executor,
             ExperimentMetadata(id=self.experiment_id, group="control") if run_experiment else None,
             is_async=self.function_to_optimize.is_async,
             sequence_offset=N_TESTS_TO_GENERATE_EFFECTIVE,
-            executor=self.executor,
         )
 
         future_references = self.executor.submit(
@@ -1418,10 +1418,10 @@ def generate_optimizations(
                 read_only_context_code,
                 self.function_trace_id[:-4] + "EXP1",
                 MODEL_DISTRIBUTION_EFFECTIVE,
+                self.executor,
                 ExperimentMetadata(id=self.experiment_id, group="experiment"),
                 is_async=self.function_to_optimize.is_async,
                 sequence_offset=N_TESTS_TO_GENERATE_EFFECTIVE,
-                executor=self.executor,
             )
             futures.append(future_candidates_exp)