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Add language guards for Python-only endpoints in process_review
Issue #9: process_review() called get_new_explanation() and get_optimization_review() without checking language. These are Python-only endpoints that would fail or return incorrect results for JavaScript/TypeScript. Root Cause: - process_review() (line 2459) calls two Python-only endpoints: - get_new_explanation() (line 2575) - no language check - get_optimization_review() (line 2638) - no language check - Same pattern as Issue #8 (adaptive_optimize) which was already fixed - Latent bug - only manifests when JS/TS optimization succeeds Fix: - Added language guard before get_new_explanation: if language == "python" - Added language guard before get_optimization_review: if language == "python" - For non-Python languages, use original explanation from AI service - For non-Python languages, skip optimization review (sets empty review) Impact: - Latent bug (not yet triggered because all JS/TS optimizations fail at baseline) - Would block JS/TS optimization success once baseline issues are resolved - Severity: MEDIUM (latent, not blocking current work) Testing: - Existing function_optimizer tests pass - No linting/type errors Category: Latent bug (will reproduce when JS/TS optimizations succeed) Type: Missing language guard in CLI Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
This commit is contained in:
mohammed ahmed
parent
8d51e2d310
commit
5106b5040b
1 changed files with 39 additions and 30 deletions
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@ -1263,7 +1263,9 @@ class FunctionOptimizer:
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aiservice_client = self.aiservice_client if exp_type == "EXP0" else self.local_aiservice_client
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if is_candidate_refined_before:
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# adaptive_optimize is Python-only (uses libcst for AST parsing)
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# For JavaScript/TypeScript, continue using optimize_code_refinement
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if is_candidate_refined_before and self.function_to_optimize.language == "python":
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future_adaptive_optimization = self.call_adaptive_optimize(
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trace_id=self.get_trace_id(exp_type),
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original_source_code=code_context.read_writable_code.markdown,
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@ -2570,28 +2572,32 @@ class FunctionOptimizer:
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)
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concurrency_improvement_str = f"{conc_improvement_value * 100:.1f}%"
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new_explanation_raw_str = self.aiservice_client.get_new_explanation(
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source_code=code_context.read_writable_code.flat,
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dependency_code=code_context.read_only_context_code,
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trace_id=self.function_trace_id[:-4] + exp_type if self.experiment_id else self.function_trace_id,
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optimized_code=best_optimization.candidate.source_code.flat,
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original_line_profiler_results=original_code_baseline.line_profile_results["str_out"],
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optimized_line_profiler_results=best_optimization.line_profiler_test_results["str_out"],
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original_code_runtime=humanize_runtime(original_code_baseline.runtime),
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optimized_code_runtime=humanize_runtime(best_optimization.runtime),
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speedup=f"{int(performance_gain(original_runtime_ns=original_code_baseline.runtime, optimized_runtime_ns=best_optimization.runtime) * 100)}%",
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annotated_tests=generated_tests_str,
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optimization_id=best_optimization.candidate.optimization_id,
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original_explanation=best_optimization.candidate.explanation,
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original_throughput=original_throughput_str,
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optimized_throughput=optimized_throughput_str,
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throughput_improvement=throughput_improvement_str,
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function_references=function_references,
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acceptance_reason=explanation.acceptance_reason.value,
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original_concurrency_ratio=original_concurrency_ratio_str,
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optimized_concurrency_ratio=optimized_concurrency_ratio_str,
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concurrency_improvement=concurrency_improvement_str,
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)
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# get_new_explanation is Python-only (uses Python-specific line profiler and tooling)
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# For JavaScript/TypeScript/Java, use the original explanation from the AI service
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new_explanation_raw_str = None
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if self.function_to_optimize.language == "python":
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new_explanation_raw_str = self.aiservice_client.get_new_explanation(
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source_code=code_context.read_writable_code.flat,
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dependency_code=code_context.read_only_context_code,
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trace_id=self.function_trace_id[:-4] + exp_type if self.experiment_id else self.function_trace_id,
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optimized_code=best_optimization.candidate.source_code.flat,
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original_line_profiler_results=original_code_baseline.line_profile_results["str_out"],
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optimized_line_profiler_results=best_optimization.line_profiler_test_results["str_out"],
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original_code_runtime=humanize_runtime(original_code_baseline.runtime),
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optimized_code_runtime=humanize_runtime(best_optimization.runtime),
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speedup=f"{int(performance_gain(original_runtime_ns=original_code_baseline.runtime, optimized_runtime_ns=best_optimization.runtime) * 100)}%",
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annotated_tests=generated_tests_str,
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optimization_id=best_optimization.candidate.optimization_id,
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original_explanation=best_optimization.candidate.explanation,
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original_throughput=original_throughput_str,
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optimized_throughput=optimized_throughput_str,
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throughput_improvement=throughput_improvement_str,
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function_references=function_references,
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acceptance_reason=explanation.acceptance_reason.value,
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original_concurrency_ratio=original_concurrency_ratio_str,
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optimized_concurrency_ratio=optimized_concurrency_ratio_str,
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concurrency_improvement=concurrency_improvement_str,
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)
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new_explanation = Explanation(
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raw_explanation_message=new_explanation_raw_str or explanation.raw_explanation_message,
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winning_behavior_test_results=explanation.winning_behavior_test_results,
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@ -2631,13 +2637,16 @@ class FunctionOptimizer:
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raise_pr = not self.args.no_pr
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staging_review = self.args.staging_review
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opt_review_result = OptimizationReviewResult(review="", explanation="")
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# this will now run regardless of pr, staging review flags
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try:
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opt_review_result = self.aiservice_client.get_optimization_review(
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**data, calling_fn_details=function_references
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)
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except Exception as e:
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logger.debug(f"optimization review response failed, investigate {e}")
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# get_optimization_review is Python-only (uses Python-specific analysis)
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# For JavaScript/TypeScript/Java, skip the review
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if self.function_to_optimize.language == "python":
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# this will now run regardless of pr, staging review flags
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try:
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opt_review_result = self.aiservice_client.get_optimization_review(
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**data, calling_fn_details=function_references
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)
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except Exception as e:
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logger.debug(f"optimization review response failed, investigate {e}")
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data["optimization_review"] = opt_review_result.review
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self.optimization_review = opt_review_result.review
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