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Tr/parallel calls #644

Merged
merged 2 commits into from
Feb 7, 2024
Merged

Tr/parallel calls #644

merged 2 commits into from
Feb 7, 2024

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mrT23
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@mrT23 mrT23 commented Feb 7, 2024

Type

enhancement


Description

  • Introduced parallel processing for AI predictions in the PR code suggestions tool, improving performance.
  • Added a new asyncio import to enable asynchronous operations.
  • Modified methods to support and utilize the new parallel processing feature based on the parallel_calls configuration.
  • Introduced a new configuration option parallel_calls in configuration.toml to toggle parallel processing of AI predictions.

Changes walkthrough

Relevant files
Enhancement
pr_code_suggestions.py
Enhance AI Prediction Processing with Parallel Calls         

pr_agent/tools/pr_code_suggestions.py

  • Introduced asyncio for parallel execution.
  • Modified _prepare_prediction and _get_prediction methods to support
    parallel processing of AI predictions.
  • Added parallel processing of AI predictions in
    _prepare_prediction_extended method based on a new configuration
    setting.
  • +17/-12 
    Configuration changes
    configuration.toml
    Add Configuration Option for Parallel AI Prediction Calls

    pr_agent/settings/configuration.toml

  • Added a new configuration option parallel_calls to enable parallel
    processing of AI predictions.
  • +2/-1     

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    @codiumai-pr-agent-pro codiumai-pr-agent-pro bot added the enhancement New feature or request label Feb 7, 2024
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    PR Description updated to latest commit (b077873)

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    PR Analysis

    • 🎯 Main theme: Enhancement of AI prediction calls with parallel execution support
    • 📝 PR summary: This PR introduces asyncio for asynchronous operations, enhancing the performance of AI prediction calls. It refactors prediction methods for better readability and maintainability. It also implements parallel execution of AI prediction calls when 'parallel_calls' is set to 'true', significantly reducing the time required for processing multiple predictions. A new configuration option 'parallel_calls' is added to enable or disable parallel AI prediction calls.
    • 📌 Type of PR: Enhancement
    • 🧪 Relevant tests added: No
    • ⏱️ Estimated effort to review [1-5]: 3, because the PR involves changes to core functionality and introduces parallelism, which requires careful review to ensure correct implementation. However, the changes are not extensive and are well explained.
    • 🔒 Security concerns: No

    PR Feedback

    💡 General suggestions: The changes made in this PR are well structured and the use of asyncio for parallel execution is a good approach to improve performance. However, it would be beneficial to add some error handling or fallback mechanism in case the parallel execution fails. Also, it would be good to add some tests to ensure the new functionality works as expected.


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    PR Code Suggestions

    Suggestions                                                                                                                                                     
    enhancement
    Use list comprehension for appending predictions in non-parallel execution.  

    Consider using a list comprehension for more concise and readable code when appending
    predictions to prediction_list in the non-parallel execution path.

    pr_agent/tools/pr_code_suggestions.py [241-244]

    -for i, patches_diff in enumerate(patches_diff_list):
    -    get_logger().info(f"Processing chunk {i + 1} of {len(patches_diff_list)}")
    -    prediction = await self._get_prediction(model, patches_diff)
    -    prediction_list.append(prediction)
    +prediction_list = [await self._get_prediction(model, patches_diff) for patches_diff in patches_diff_list]
     
    best practice
    Add exception handling for parallel tasks.                                   

    To ensure that exceptions in parallel tasks are handled properly, consider wrapping the
    asyncio.gather call with a try-except block.

    pr_agent/tools/pr_code_suggestions.py [236]

    -prediction_list = await asyncio.gather(*[self._get_prediction(model, patches_diff) for patches_diff in patches_diff_list])
    +try:
    +    prediction_list = await asyncio.gather(*[self._get_prediction(model, patches_diff) for patches_diff in patches_diff_list])
    +except Exception as e:
    +    get_logger().error(f"Error getting predictions: {e}")
    +    raise
     
    Use .update() for dictionary updates.                           

    Instead of manually updating the variables dictionary with the patches_diff, consider
    using the .update() method for clarity and potential future extensions.

    pr_agent/tools/pr_code_suggestions.py [126]

    -variables["diff"] = patches_diff  # update diff
    +variables.update({"diff": patches_diff})
     
    maintainability
    Dynamically fetch configuration settings.                                    

    For better scalability and to avoid hardcoding the configuration keys, consider fetching
    the configuration settings (parallel_calls, max_number_of_calls) dynamically within the
    function.

    pr_agent/tools/pr_code_suggestions.py [234]

    -if get_settings().pr_code_suggestions.parallel_calls:
    +settings = get_settings().pr_code_suggestions
    +if settings.parallel_calls:
     
    Document new configuration options.                                          

    Consider documenting the new configuration options (parallel_calls,
    rank_extended_suggestions) in the configuration file to improve maintainability and
    usability for new users.

    pr_agent/settings/configuration.toml [86-87]

    +# Enable parallel calls for AI predictions. Improves performance but requires more resources.
     parallel_calls = true
    +# Rank extended suggestions based on certain criteria. Currently disabled.
     rank_extended_suggestions = false
     

    ✨ Usage guide:

    Overview:
    The improve tool scans the PR code changes, and automatically generates suggestions for improving the PR code. The tool can be triggered automatically every time a new PR is opened, or can be invoked manually by commenting on a PR.
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    Emphasize the following aspects:
    - Does the code logic cover relevant edge cases?
    - Is the code logic clear and easy to understand?
    - Is the code logic efficient?
    ...
    """
    

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    @mrT23 mrT23 merged commit e4f1779 into main Feb 7, 2024
    2 checks passed
    @mrT23 mrT23 deleted the tr/parallel_calls branch February 7, 2024 18:29
    @sprihagautam12
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    Preparing review...

    1 similar comment
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    mrT23 commented Feb 8, 2024

    Preparing review...

    @mrT23
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    mrT23 commented Feb 8, 2024

    Persistent review updated to latest commit b077873

    3 similar comments
    @mrT23
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    mrT23 commented Feb 8, 2024

    Persistent review updated to latest commit b077873

    @mrT23
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    mrT23 commented Feb 8, 2024

    Persistent review updated to latest commit b077873

    @mrT23
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    mrT23 commented Feb 8, 2024

    Persistent review updated to latest commit b077873

    @mrT23
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    mrT23 commented Feb 8, 2024

    Persistent review updated to latest commit b077873

    1 similar comment
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    mrT23 commented Feb 8, 2024

    Persistent review updated to latest commit b077873

    @mrT23
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    mrT23 commented Feb 9, 2024

    PR Review

    (review updated until commit b077873)

         PR feedback                    
    ⏱️ Estimated effort to review [1-5]

    2, because the changes are focused on introducing asynchronous operations and refactoring for better readability. The logic seems straightforward, but understanding the asynchronous flow and ensuring it works as expected with the rest of the system might require some effort.

    🧪 Relevant tests added

    No

    🔍 Possible issues

    Yes, while the introduction of asyncio and parallel execution can significantly improve performance, it also introduces complexity. There's a potential issue with error handling in asynchronous calls that isn't addressed. If one of the asyncio.gather calls fails, it might not be clear how the system will handle it. Additionally, the change from instance variable self.patches_diff to local variable patches_diff could impact other methods if they rely on self.patches_diff.

    🔒 Security concerns

    No


    ✨ Usage guide:

    Overview:
    The review tool scans the PR code changes, and generates a PR review. The tool can be triggered automatically every time a new PR is opened, or can be invoked manually by commenting on any PR.
    When commenting, to edit configurations related to the review tool (pr_reviewer section), use the following template:

    /review --pr_reviewer.some_config1=... --pr_reviewer.some_config2=...
    

    With a configuration file, use the following template:

    [pr_reviewer]
    some_config1=...
    some_config2=...
    
    Utilizing extra instructions

    The review tool can be configured with extra instructions, which can be used to guide the model to a feedback tailored to the needs of your project.

    Be specific, clear, and concise in the instructions. With extra instructions, you are the prompter. Specify the relevant sub-tool, and the relevant aspects of the PR that you want to emphasize.

    Examples for extra instructions:

    [pr_reviewer] # /review #
    extra_instructions="""
    In the 'general suggestions' section, emphasize the following:
    - Does the code logic cover relevant edge cases?
    - Is the code logic clear and easy to understand?
    - Is the code logic efficient?
    ...
    """
    

    Use triple quotes to write multi-line instructions. Use bullet points to make the instructions more readable.

    How to enable\disable automation
    • When you first install PR-Agent app, the default mode for the review tool is:
    pr_commands = ["/review", ...]
    

    meaning the review tool will run automatically on every PR, with the default configuration.
    Edit this field to enable/disable the tool, or to change the used configurations

    Auto-labels

    The review tool can auto-generate two specific types of labels for a PR:

    • a possible security issue label, that detects possible security issues (enable_review_labels_security flag)
    • a Review effort [1-5]: x label, where x is the estimated effort to review the PR (enable_review_labels_effort flag)
    Extra sub-tools

    The review tool provides a collection of possible feedbacks about a PR.
    It is recommended to review the possible options, and choose the ones relevant for your use case.
    Some of the feature that are disabled by default are quite useful, and should be considered for enabling. For example:
    require_score_review, require_soc2_ticket, and more.

    Auto-approve PRs

    By invoking:

    /review auto_approve
    

    The tool will automatically approve the PR, and add a comment with the approval.

    To ensure safety, the auto-approval feature is disabled by default. To enable auto-approval, you need to actively set in a pre-defined configuration file the following:

    [pr_reviewer]
    enable_auto_approval = true
    

    (this specific flag cannot be set with a command line argument, only in the configuration file, committed to the repository)

    You can also enable auto-approval only if the PR meets certain requirements, such as that the estimated_review_effort is equal or below a certain threshold, by adjusting the flag:

    [pr_reviewer]
    maximal_review_effort = 5
    
    More PR-Agent commands

    To invoke the PR-Agent, add a comment using one of the following commands:

    • /review: Request a review of your Pull Request.
    • /describe: Update the PR title and description based on the contents of the PR.
    • /improve [--extended]: Suggest code improvements. Extended mode provides a higher quality feedback.
    • /ask <QUESTION>: Ask a question about the PR.
    • /update_changelog: Update the changelog based on the PR's contents.
    • /add_docs 💎: Generate docstring for new components introduced in the PR.
    • /generate_labels 💎: Generate labels for the PR based on the PR's contents.
    • /analyze 💎: Automatically analyzes the PR, and presents changes walkthrough for each component.

    See the tools guide for more details.
    To list the possible configuration parameters, add a /config comment.

    See the review usage page for a comprehensive guide on using this tool.

    @mrT23
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    mrT23 commented Feb 9, 2024

    Persistent review updated to latest commit b077873

    yochail pushed a commit to yochail/pr-agent that referenced this pull request Feb 11, 2024
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    /describe

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    codiumai-pr-agent-pro bot commented Feb 17, 2024

    PR Description updated to latest commit (b077873)

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    Changes walkthrough

                             Relevant files
    Enhancement
    pr_code_suggestions.py (+17/-12)
    Enhance AI Prediction Processing with Parallel Calls         

    pr_agent/tools/pr_code_suggestions.py

  • Introduced asyncio for parallel execution.
  • Modified _prepare_prediction and _get_prediction methods to support
    parallel processing of AI predictions.
  • Added parallel processing of AI predictions in
    _prepare_prediction_extended method based on a new configuration
    setting.
  • Configuration changes
    configuration.toml (+2/-1)
    Add Configuration Option for Parallel AI Prediction Calls

    pr_agent/settings/configuration.toml

  • Added a new configuration option parallel_calls to enable parallel
    processing of AI predictions.
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