Undo Optimization Impact

[aseembits93]

User description

Current UX is problematic with lots of staging reviews created.

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PR Type

Enhancement

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Description

• Disable optimization impact gating logic

• Always respect explicit PR/staging flags

• Preserve previous code via comments

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Diagram Walkthrough

flowchart LR A["process_review"] -- "previously queried impact" --> B["get_optimization_impact"] B -- "low -> force staging" --> C["staging_review=True"] A -- "now" --> D["skip impact check"] D -- "use args only" --> E["raise_pr / staging_review flow"] 

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File Walkthrough

	Relevant files
Enhancement	function_optimizer.py Skip optimization impact-based PR/staging decision              codeflash/optimization/function_optimizer.py Comment out calls to get_optimization_impact. Remove auto-switching to staging on low impact. Keep decision solely on no_pr and staging_review args. +8/-8

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[github-actions]

PR Reviewer Guide 🔍

Here are some key observations to aid the review process:

⏱️ Estimated effort to review: 2 🔵🔵⚪⚪⚪

🧪 No relevant tests

🔒 No security concerns identified

⚡ Recommended focus areas for review Dead Code Large commented block of previously active logic is left in place; consider removing or guarding with a feature flag to avoid drift and confusion. # try: # # modify argument of staging vs pr based on the impact # opt_impact_response = self.aiservice_client.get_optimization_impact(**data) # if opt_impact_response == "low": # raise_pr = False # staging_review = True # except Exception as e: # logger.debug(f"optimization impact response failed, investigate {e}") Behavior Change Optimization impact gating is fully disabled; verify downstream flows still meet expectations and that explicit flags alone cover all intended scenarios. if raise_pr or staging_review: data["root_dir"] = git_root_dir() # try: # # modify argument of staging vs pr based on the impact # opt_impact_response = self.aiservice_client.get_optimization_impact(**data) # if opt_impact_response == "low": # raise_pr = False # staging_review = True # except Exception as e: # logger.debug(f"optimization impact response failed, investigate {e}") if raise_pr and not staging_review: data["git_remote"] = self.args.git_remote check_create_pr(**data) elif staging_review:

[github-actions]

PR Code Suggestions ✨

Explore these optional code suggestions:

Category	Suggestion	Impact
Possible issue	Restore impact-based gating By fully commenting out the optimization impact check, raise_pr and staging_review are never adjusted, potentially triggering PRs when only staging was intended. Restore the logic without swallowing exceptions silently by guarding it behind a feature flag but keeping a safe fallback. Ensure failures default to the previous behavior and are logged. codeflash/optimization/function_optimizer.py [1462-1471] if raise_pr or staging_review: data["root_dir"] = git_root_dir() - # try: - # # modify argument of staging vs pr based on the impact - # opt_impact_response = self.aiservice_client.get_optimization_impact(**data) - # if opt_impact_response == "low": - # raise_pr = False - # staging_review = True - # except Exception as e: - # logger.debug(f"optimization impact response failed, investigate {e}") + if getattr(self.args, "use_optimization_impact", True): + try: + # modify argument of staging vs pr based on the impact + opt_impact_response = self.aiservice_client.get_optimization_impact(**data) + if opt_impact_response == "low": + raise_pr = False + staging_review = True + except Exception as e: + logger.debug(f"optimization impact response failed, investigate {e}") Suggestion importance[1-10]: 7 __ Why: The PR comments out logic that adjusted raise_pr vs staging_review, changing behavior; restoring it behind a flag is reasonable and the improved code accurately reflects the intended change, referencing the correct lines. Impact is moderate since it affects workflow behavior, but it's a feature-choice rather than a critical bug.	Medium

[saga4893]

Is this condition now required?

[aseembits93]

that's from the original code, it's still required