Return to opus. It just works better

[sourcery-ai-experiments-bot]

No description provided.

[sourcery-ai-experiments-bot]

This is a benchmark review for experiment review_of_reviews_20240423.
Run ID: review_of_reviews_20240423/benchmark_2024-04-23T16-37-59_v1-16-0-177-gfebff3a45.

This pull request was cloned from https://github.com/jquagga/ttt/pull/76. (Note: the URL is not a link to avoid triggering a notification on the original pull request.)

Experiment configuration

review_config:
  # User configuration for the review
  # - benchmark - use the user config from the benchmark reviews
  # - <value> - use the value directly
  user_config:
    enable_ai_review: true
    enable_rule_comments: false

    enable_complexity_comments: benchmark
    enable_docstring_comments: benchmark
    enable_security_comments: benchmark
    enable_tests_comments: benchmark
    enable_comment_suggestions: benchmark

    enable_approvals: true

  ai_review_config:
    # The model responses to use for the experiment
    # - benchmark - use the model responses from the benchmark reviews
    # - llm - call the language model to generate responses
    model_responses:
      comments_model: benchmark
      comment_validation_model: benchmark
      comment_suggestion_model: benchmark
      complexity_model: benchmark
      docstrings_model: benchmark
      security_model: benchmark
      tests_model: benchmark

# The pull request dataset to run the experiment on
pull_request_dataset:
- https://github.com/albumentations-team/albumentations/pull/1679
- https://github.com/gdsfactory/kfactory/pull/301
- https://github.com/gdsfactory/kfactory/pull/300
- https://github.com/jquagga/ttt/pull/70
- https://github.com/gdsfactory/kfactory/pull/298
- https://github.com/gdsfactory/gplugins/pull/385
- https://github.com/shreejitverma/MScFE690-Capstone/pull/7
- https://github.com/gdsfactory/gdsfactory/pull/2694
- https://github.com/yelinaung/advent_of_code_2023/pull/8
- https://github.com/fairdataihub/fairdataihub.org/pull/620
- https://github.com/jquagga/ttt/pull/75
- https://github.com/jquagga/ttt/pull/77
- https://github.com/aboutmydreams/aiis.read/pull/16
- https://github.com/usama-maxenius/image-editor/pull/71
- https://github.com/okisdev/ChatChat/pull/322
- https://github.com/okisdev/ChatChat/pull/323
- https://github.com/iphysresearch/Eryn/pull/1
- https://github.com/W-zrd/unishare_mobile/pull/9
- https://github.com/wassupluke/recipe-emailer/pull/24
- https://github.com/jquagga/ttt/pull/79
- https://github.com/Remi-Gau/nilearn/pull/50
- https://github.com/gdsfactory/gdsfactory/pull/2697
- https://github.com/0ussamaBernou/my-portfolio/pull/8
- https://github.com/kloudlite/web/pull/195
- https://github.com/ElectronicBabylonianLiterature/ebl-api/pull/546
- https://github.com/okisdev/ChatChat/pull/319
- https://github.com/strawberry-graphql/strawberry/pull/3469
- https://github.com/ShiroePL/EasternTalesShelf/pull/44
- https://github.com/jquagga/ttt/pull/78
- https://github.com/W-zrd/unishare_mobile/pull/10
- https://github.com/erxes/erxes/pull/5157
- https://github.com/jquagga/ttt/pull/67
- https://github.com/jquagga/ttt/pull/76
- https://github.com/jkool702/openwrt/pull/41
- https://github.com/jquagga/ttt/pull/73
- https://github.com/W-zrd/unishare_mobile/pull/8
- https://github.com/UCL/dxss/pull/63
- https://github.com/shreejitverma/MScFE690-Capstone/pull/6
- https://github.com/DevCycleHQ/go-server-sdk/pull/248
- https://github.com/Quarticai/graphene-django-extras/pull/104
- https://github.com/wassupluke/recipe-emailer/pull/29
- https://github.com/erxes/erxes/pull/5158
- https://github.com/0ussamaBernou/my-portfolio/pull/6
- https://github.com/2lambda123/kwenta/pull/50
- https://github.com/dciborow/action-pylint/pull/14
- https://github.com/ShiroePL/EasternTalesShelf/pull/45
- https://github.com/W-zrd/unishare_mobile/pull/6
- https://github.com/gdsfactory/gdsfactory/pull/2696
- https://github.com/megasanjay/scholar-stack-mvp/pull/159
- https://github.com/W-zrd/unishare_mobile/pull/7
review_comment_labels:
- label: correct
  question: Is this comment correct?
- label: helpful
  question: Is this comment helpful?
- label: comment-type
  question: Is the comment type correct?
- label: comment-area
  question: Is the comment area correct?
- label: llm-test
  question: Should this comment become an LLM test?

# Benchmark reviews generated by running
#   python -m scripts.experiment benchmark <experiment_name>
benchmark_reviews: []

[SourceryAI]

Hey @sourcery-ai-experiments-bot - I've reviewed your changes and they look great!

Here's what I looked at during the review

• 🟡 General issues: 3 issues found
• 🟢 Security: all looks good
• 🟡 Testing: 2 issues found
• 🟢 Complexity: all looks good
• 🟢 Docstrings: all looks good

---

LangSmith trace

_{Help me be more useful! Please click 👍 or 👎 on each comment to tell me if it was helpful.}

[SourceryAI]

suggestion (performance): Review the '8000' Hz cutoff frequency for appropriateness in the VOIP context.

The cutoff frequency of 8000 Hz might not be suitable for all VOIP applications, especially if high-quality audio is required. Consider if a higher cutoff might be necessary.

Suggested change

	"-cutoff",
	"8000",
	"-cutoff",
	"12000",

[SourceryAI]

Is this comment correct?

[SourceryAI]

suggestion (testing): Missing test for the new audio file format change.

The change from FLAC to OPUS format should be accompanied by a test to ensure the new format is handled correctly and that the audio quality meets the expected standards.

[SourceryAI]

suggestion (testing): Consider adding tests for new ffmpeg command options.

The addition of new options like 'libopus', 'voip', 'cutoff', '8000', and 'vbr' in the ffmpeg command suggests a need for tests to verify that these settings are correctly applied and function as intended.