AI-based PR reviewer and summarizer

Overview

CodeRabbit ai-pr-reviewer is an AI-based code reviewer and summarizer for GitHub pull requests using OpenAI's gpt-3.5-turbo and gpt-4 models. It is designed to be used as a GitHub Action and can be configured to run on every pull request and review comments

Reviewer Features:

• PR Summarization: It generates a summary and release notes of the changes in the pull request.
• Line-by-line code change suggestions: Reviews the changes line by line and provides code change suggestions.
• Continuous, incremental reviews: Reviews are performed on each commit within a pull request, rather than a one-time review on the entire pull request.
• Cost-effective and reduced noise: Incremental reviews save on OpenAI costs and reduce noise by tracking changed files between commits and the base of the pull request.
• "Light" model for summary: Designed to be used with a "light" summarization model (e.g. gpt-3.5-turbo) and a "heavy" review model (e.g. gpt-4). For best results, use gpt-4 as the "heavy" model, as thorough code review needs strong reasoning abilities.
• Chat with bot: Supports conversation with the bot in the context of lines of code or entire files, useful for providing context, generating test cases, and reducing code complexity.
• Smart review skipping: By default, skips in-depth review for simple changes (e.g. typo fixes) and when changes look good for the most part. It can be disabled by setting review_simple_changes and review_comment_lgtm to true.
• Customizable prompts: Tailor the system_message, summarize, and summarize_release_notes prompts to focus on specific aspects of the review process or even change the review objective.

To use this tool, you need to add the provided YAML file to your repository and configure the required environment variables, such as GITHUB_TOKEN and OPENAI_API_KEY. For more information on usage, examples, contributing, and FAQs, you can refer to the sections below.

• Overview
• Professional Version of CodeRabbit
• Reviewer Features
• Install instructions
• Conversation with CodeRabbit
• Examples
• Contribute
• FAQs

Install instructions

ai-pr-reviewer runs as a GitHub Action. Add the below file to your repository at .github/workflows/ai-pr-reviewer.yml

name: Code Review

permissions:
  contents: read
  pull-requests: write

on:
  pull_request:
  pull_request_review_comment:
    types: [created]

concurrency:
  group:
    ${{ github.repository }}-${{ github.event.number || github.head_ref ||
    github.sha }}-${{ github.workflow }}-${{ github.event_name ==
    'pull_request_review_comment' && 'pr_comment' || 'pr' }}
  cancel-in-progress: ${{ github.event_name != 'pull_request_review_comment' }}

jobs:
  review:
    runs-on: ubuntu-latest
    steps:
      - uses: coderabbitai/ai-pr-reviewer@latest
        env:
          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
        with:
          debug: false
          review_simple_changes: false
          review_comment_lgtm: false

Environment variables

• GITHUB_TOKEN: This should already be available to the GitHub Action environment. This is used to add comments to the pull request.
• OPENAI_API_KEY: use this to authenticate with OpenAI API. You can get one here. Please add this key to your GitHub Action secrets.
• OPENAI_API_ORG: (optional) use this to use the specified organization with OpenAI API if you have multiple. Please add this key to your GitHub Action secrets.

Models: gpt-4 and gpt-3.5-turbo

Recommend using gpt-3.5-turbo for lighter tasks such as summarizing the changes (openai_light_model in configuration) and gpt-4 for more complex review and commenting tasks (openai_heavy_model in configuration).

Costs: gpt-3.5-turbo is dirt cheap. gpt-4 is orders of magnitude more expensive, but the results are vastly superior. We are typically spending $20 a day for a 20 developer team with gpt-4 based review and commenting.

Prompts & Configuration

See: action.yml

Tip: You can change the bot personality by configuring the system_message value. For example, to review docs/blog posts, you can use the following prompt:

Blog Reviewer Prompt

system_message: |
  You are `@codekittenai` (aka `github-actions[bot]`), a language model
  trained by OpenAI. Your purpose is to act as a highly experienced
  DevRel (developer relations) professional with focus on cloud-native
  infrastructure.

  Company context -
  CodeRabbit is an AI-powered Code reviewer.It boosts code quality and cuts manual effort. Offers context-aware, line-by-line feedback, highlights critical changes,
  enables bot interaction, and lets you commit suggestions directly from GitHub.

  When reviewing or generating content focus on key areas such as -
  - Accuracy
  - Relevance
  - Clarity
  - Technical depth
  - Call-to-action
  - SEO optimization
  - Brand consistency
  - Grammar and prose
  - Typos
  - Hyperlink suggestions
  - Graphics or images (suggest Dall-E image prompts if needed)
  - Empathy
  - Engagement

Conversation with CodeRabbit

You can reply to a review comment made by this action and get a response based on the diff context. Additionally, you can invite the bot to a conversation by tagging it in the comment (@codekittenai).

Example:

@codekittenai Please generate a test plan for this file.

Note: A review comment is a comment made on a diff or a file in the pull request.

Ignoring PRs

Sometimes it is useful to ignore a PR. For example, if you are using this action to review documentation, you can ignore PRs that only change the documentation. To ignore a PR, add the following keyword in the PR description:

@codekittenai: ignore

Examples

Some of the reviews done by ai-pr-reviewer

Any suggestions or pull requests for improving the prompts are highly appreciated.

Contribute

Developing

First, you'll need to have a reasonably modern version of node handy, tested with node 17+.

Install the dependencies

$ npm install

Build the typescript and package it for distribution

$ npm run build && npm run package

FAQs

Review pull requests from forks

GitHub Actions limits the access of secrets from forked repositories. To enable this feature, you need to use the pull_request_target event instead of pull_request in your workflow file. Note that with pull_request_target, you need extra configuration to ensure checking out the right commit:

name: Code Review

permissions:
  contents: read
  pull-requests: write

on:
  pull_request_target:
    types: [opened, synchronize, reopened]
  pull_request_review_comment:
    types: [created]

concurrency:
  group:
    ${{ github.repository }}-${{ github.event.number || github.head_ref ||
    github.sha }}-${{ github.workflow }}-${{ github.event_name ==
    'pull_request_review_comment' && 'pr_comment' || 'pr' }}
  cancel-in-progress: ${{ github.event_name != 'pull_request_review_comment' }}

jobs:
  review:
    runs-on: ubuntu-latest
    steps:
      - uses: coderabbitai/ai-pr-reviewer@latest
        env:
          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
        with:
          debug: false
          review_simple_changes: false
          review_comment_lgtm: false

See also: https://docs.github.com/en/actions/using-workflows/events-that-trigger-workflows#pull_request_target

Inspect the messages between OpenAI server

Set debug: true in the workflow file to enable debug mode, which will show the messages

Disclaimer

• Your code (files, diff, PR title/description) will be sent to OpenAI's servers for processing. Please check with your compliance team before using this on your private code repositories.
• OpenAI's API is used instead of ChatGPT session on their portal. OpenAI API has a more conservative data usage policy compared to their ChatGPT offering.
• This action is not affiliated with OpenAI.