Refinement

[misrasaurabh1]

PR Type

Enhancement

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Description

• Add code refinement pipeline integration

• Accumulate and refine optimization candidates

• Multi-criteria ranking by diff & runtime

• Refactor test env and profiling helpers

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Diagram Walkthrough

flowchart LR
  A["Initial optimizations"] --> B["Accumulate candidates"]
  B --> C["Request refinements"]
  C --> D["Merge refined candidates"]
  D --> E["Rank by diff & runtime"]
  E --> F["Select best optimization"]

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File Walkthrough

	Relevant files
Enhancement	aiservice.py Integrate refinement request and logging enhancements        codeflash/api/aiservice.py Added optimize_python_code_refinement method Extended make_ai_service_request payload types Introduced safe_get_repo_owner_and_name helper Included optimized_line_profiler_results in logging +78/-7    code_utils.py Add diff and ranking utility functions                                      codeflash/code_utils/code_utils.py Added diff_length for unified diff sizing Introduced create_rank_dictionary_compact utility Imported difflib dependency +45/-0    models.py Define refiner request and model updates                                  codeflash/models/models.py Defined AIServiceRefinerRequest dataclass Extended BestOptimization with new fields +18/-0    function_optimizer.py Implement candidate refinement and ranking                              codeflash/optimization/function_optimizer.py Introduced valid_optimizations list and refine flow Added refine_optimizations candidate refinement method Refactored test env and profiling helpers Implemented diff & runtime ranking logic +159/-48
Bug fix	critic.py Support None baseline in speedup_critic                                    codeflash/result/critic.py Updated speedup_critic to accept None baseline Fallback to perf_gain when no best runtime +4/-1

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[github-actions]

PR Reviewer Guide 🔍

(Review updated until commit c596e12)

Here are some key observations to aid the review process:

⏱️ Estimated effort to review: 4 🔵🔵🔵🔵⚪

🧪 No relevant tests

🔒 No security concerns identified

⚡ Recommended focus areas for review RequestSchemaMismatch The AIServiceRefinerRequest dataclass lacks fields experiment_metadata and fto_name used in refine_optimizations, causing unexpected field errors during instantiation. @dataclass(frozen=True) class AIServiceRefinerRequest: optimization_id: str original_source_code: str read_only_dependency_code: str original_code_runtime: str optimized_source_code: str optimized_explanation: str optimized_code_runtime: str speedup: str trace_id: str original_line_profiler_results: str optimized_line_profiler_results: str BestRuntimeLogic The _best_runtime_until_now variable is initialized but never passed to speedup_critic; as a result, the critic always receives None and prior best runtimes aren't considered in selection. ) -> BestOptimization | None: best_optimization: BestOptimization | None = None _best_runtime_until_now = original_code_baseline.runtime speedup_ratios: dict[str, float | None] = {} optimized_runtimes: dict[str, float | None] = {} is_correct = {} optimized_line_profiler_results: dict[str, str] = {} IncorrectImport AIServiceRefinerRequest is imported from codeflash.api.aiservice, but it's defined in codeflash/models/models.py, which may lead to import errors or circular dependencies. from codeflash.api.aiservice import AiServiceClient, AIServiceRefinerRequest, LocalAiServiceClient

[github-actions]

PR Code Suggestions ✨

Latest suggestions up to c596e12
Explore these optional code suggestions:

Category	Suggestion	Impact
Possible issue	Define missing dataclass fields The AIServiceRefinerRequest dataclass is constructed with experiment_metadata and fto_name in refine_optimizations but those fields aren’t defined. Add matching fields to the dataclass so the init call doesn’t fail. codeflash/models/models.py [31-43] @dataclass(frozen=True) class AIServiceRefinerRequest: optimization_id: str original_source_code: str read_only_dependency_code: str original_code_runtime: str optimized_source_code: str optimized_explanation: str optimized_code_runtime: str speedup: str trace_id: str original_line_profiler_results: str optimized_line_profiler_results: str + experiment_metadata: ExperimentMetadata | None + fto_name: str Suggestion importance[1-10]: 9 __ Why: The AIServiceRefinerRequest dataclass is missing experiment_metadata and fto_name fields, which are passed in refine_optimizations, causing a constructor error at runtime.	High

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Previous suggestions

Suggestions up to commit 65d2971

Category	Suggestion	Impact
Possible issue	Fix payload field name The payload uses a non-existent field original_read_only_dependency_code; it should match the dataclass field read_only_dependency_code. Rename both the key and attribute reference to keep them consistent. codeflash/api/aiservice.py [241-242] { "original_source_code": opt.original_source_code, - "original_read_only_dependency_code": opt.original_read_only_dependency_code, + "read_only_dependency_code": opt.read_only_dependency_code, ... } Suggestion importance[1-10]: 9 __ Why: The payload key "original_read_only_dependency_code" and attribute opt.original_read_only_dependency_code do not exist on AIServiceRefinerRequest, so renaming to read_only_dependency_code is essential to avoid runtime errors.	High
General	Move refinement block This block is inside the while candidates: loop and will never run because the loop exits when len(candidates)==0. Move it outside the loop so refinement runs once after processing all candidates. codeflash/optimization/function_optimizer.py [543-571] -if len(candidates) == 0 and len(self.valid_optimizations) > 0 and not refinement_done: +# after the while-candidates loop ends +if len(self.valid_optimizations) > 0 and not refinement_done: # ... refine_optimizations ... candidates.extend(more_opt_candidates) refinement_done = True Suggestion importance[1-10]: 9 __ Why: The if len(candidates) == 0 check is inside the while candidates: loop and thus never executes, so relocating it after the loop is critical for the refinement step to run.	High
	Serialize metadata field Sending a Pydantic dataclass instance directly may fail JSON serialization. Convert the experiment_metadata to a dict (or JSON) before adding it to the payload. codeflash/api/aiservice.py [252] -"experiment_metadata": opt.experiment_metadata, +"experiment_metadata": opt.experiment_metadata.dict() if opt.experiment_metadata else None, Suggestion importance[1-10]: 6 __ Why: Passing a Pydantic dataclass directly may not serialize with requests.json, so converting opt.experiment_metadata to a dict ensures the payload is JSON-serializable.	Low

[codeflash-ai]

⚡️ Codeflash found optimizations for this PR

📄 15% (0.15x) speedup for speedup_critic in codeflash/result/critic.py

⏱️ Runtime : 1.84 milliseconds → 1.60 milliseconds (best of 56 runs)

I created a new dependent PR with the suggested changes. Please review:

• ⚡️ Speed up function speedup_critic by 15% in PR #555 (refinement) #557

If you approve, it will be merged into this PR (branch refinement).

[aseembits93]

LGTM

[github-actions]

Persistent review updated to latest commit c596e12