⚡ Bolt: [performance improvement] optimize redundant strip

[bashandbone]

💡 What: Used the walrus operator (:=) inside _nvidia_smi_device_ids in src/codeweaver/providers/optimize.py to prevent redundant .strip() string manipulations.
🎯 Why: .strip() was being evaluated twice per line inside a generator comprehension within _nvidia_smi_device_ids(), causing unnecessary allocation and duplicate string operations on each iteration.
📊 Impact: Reduces string allocation and .strip() evaluation overhead by half within the context of checking NVIDIA GPU availability.
🔬 Measurement: Verified that uv run pytest tests/unit/providers/ --no-cov passes without regressions, meaning output logic matches pre-walrus state exactly.

---

PR created automatically by Jules for task 13165653728050944631 started by @bashandbone

Summary by Sourcery

Enhancements:

• Reduce repeated .strip() calls when parsing nvidia-smi output in _nvidia_smi_device_ids to lower string allocation overhead.

[google-labs-jules]

👋 Jules, reporting for duty! I'm here to lend a hand with this pull request.

When you start a review, I'll add a 👀 emoji to each comment to let you know I've read it. I'll focus on feedback directed at me and will do my best to stay out of conversations between you and other bots or reviewers to keep the noise down.

I'll push a commit with your requested changes shortly after. Please note there might be a delay between these steps, but rest assured I'm on the job!

For more direct control, you can switch me to Reactive Mode. When this mode is on, I will only act on comments where you specifically mention me with @jules. You can find this option in the Pull Request section of your global Jules UI settings. You can always switch back!

New to Jules? Learn more at jules.google/docs.

---

For security, I will only act on instructions from the user who triggered this task.

[sourcery-ai]

Reviewer's guide (collapsed on small PRs)

Reviewer's Guide

Refactors the NVIDIA SMI device ID parsing helper to eliminate redundant string stripping using the walrus operator, improving performance while preserving behavior.

File-Level Changes

Change	Details	Files
Optimize NVIDIA SMI output parsing by eliminating duplicate .strip() calls with a walrus operator.	Replaces a list comprehension that calls .strip() twice per line with one that binds the stripped value using the walrus operator. Ensures the filtered lines are still validated with .isdigit() and converted to int using the stripped value. Documents the intent with an inline comment explaining the performance-focused refactor.	src/codeweaver/providers/optimize.py

---

Tips and commands

Interacting with Sourcery

• Trigger a new review: Comment @sourcery-ai review on the pull request.
• Continue discussions: Reply directly to Sourcery's review comments.
• Generate a GitHub issue from a review comment: Ask Sourcery to create an
  issue from a review comment by replying to it. You can also reply to a
  review comment with @sourcery-ai issue to create an issue from it.
• Generate a pull request title: Write @sourcery-ai anywhere in the pull
  request title to generate a title at any time. You can also comment
  @sourcery-ai title on the pull request to (re-)generate the title at any time.
• Generate a pull request summary: Write @sourcery-ai summary anywhere in
  the pull request body to generate a PR summary at any time exactly where you
  want it. You can also comment @sourcery-ai summary on the pull request to
  (re-)generate the summary at any time.
• Generate reviewer's guide: Comment @sourcery-ai guide on the pull
  request to (re-)generate the reviewer's guide at any time.
• Resolve all Sourcery comments: Comment @sourcery-ai resolve on the
  pull request to resolve all Sourcery comments. Useful if you've already
  addressed all the comments and don't want to see them anymore.
• Dismiss all Sourcery reviews: Comment @sourcery-ai dismiss on the pull
  request to dismiss all existing Sourcery reviews. Especially useful if you
  want to start fresh with a new review - don't forget to comment
  @sourcery-ai review to trigger a new review!

Customizing Your Experience

Access your dashboard to:

• Enable or disable review features such as the Sourcery-generated pull request
  summary, the reviewer's guide, and others.
• Change the review language.
• Add, remove or edit custom review instructions.
• Adjust other review settings.

Getting Help

• Contact our support team for questions or feedback.
• Visit our documentation for detailed guides and information.
• Keep in touch with the Sourcery team by following us on X/Twitter, LinkedIn or GitHub.

[github-actions]

🤖 Hi @bashandbone, I've received your request, and I'm working on it now! You can track my progress in the logs for more details.

[sourcery-ai]

Hey - I've left some high level feedback:

• Consider whether the added complexity of the walrus operator in the comprehension is worth the minor performance gain here; an explicit loop (or a small helper) might balance readability and optimization more clearly.

Prompt for AI Agents

Please address the comments from this code review:

## Overall Comments
- Consider whether the added complexity of the walrus operator in the comprehension is worth the minor performance gain here; an explicit loop (or a small helper) might balance readability and optimization more clearly.

---

Sourcery is free for open source - if you like our reviews please consider sharing them ✨

• X
• Mastodon
• LinkedIn
• Facebook

_{Help me be more useful! Please click 👍 or 👎 on each comment and I'll use the feedback to improve your reviews.}

[github-actions]

🤖 I'm sorry @bashandbone, but I was unable to process your request. Please see the logs for more details.

[Copilot]

Pull request overview

This PR makes a small performance-focused refactor in the provider runtime detection path by removing a redundant strip() call inside NVIDIA GPU ID parsing. It fits into the provider optimization layer that decides whether GPU-backed FastEmbed execution is available.

Changes:

• Rewrites _nvidia_smi_device_ids() to compute the stripped line once with the walrus operator.
• Preserves the existing filtering behavior (isdigit()) while avoiding duplicate string trimming.
• Adds an inline comment explaining the micro-optimization.

---

💡 Add Copilot custom instructions for smarter, more guided reviews. Learn how to get started.