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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/67. (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
SourceryAI approved these changes Apr 23, 2024
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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: 2 issues found
  • 🟢 Security: all looks good
  • 🟢 Testing: all looks good
  • 🟢 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.

ttt.py
@@ -71,9 +68,7 @@ def transcribe_whispercpp(calljson, audiofile):
response = requests.post(f"{whisper_url}/inference", files=files)
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suggestion (code_refinement): Consider using logging instead of print for error messages.

Using logging allows for better control over logging levels and is more suitable for production environments than print statements.

Suggested change
response = requests.post(f"{whisper_url}/inference", files=files)
import logging
logging.error(f"A request error occurred while trying to post to whisper.cpp: {e}")

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Is this comment correct?

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Is this comment helpful?

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Is the comment type correct?

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Is the comment area correct?

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Should this comment become an LLM test?

ttt.py
@@ -318,15 +313,15 @@ def main():

# If the queue is empty, pause for 5 seconds and then restart polling
if not jsonlist:
logging.debug("Empty queue. Sleep 5 seconds and check again.")
print("Empty queue. Sleep 5 seconds and check again.")
time.sleep(5)
return

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suggestion (code_refinement): Maintain use of logging for operational information.

Using logging for operational information such as processing files helps in tracking application behavior without cluttering the console output.

Suggested change
import logging
logging.basicConfig(level=logging.INFO)
logging.info(f"Processing: {audiofile}")

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Is this comment correct?

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Is this comment helpful?

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Is the comment type correct?

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Is the comment area correct?

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Should this comment become an LLM test?

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@sourcery-ai-experiments-bot @SourceryAI @jquagga