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A cross-platform code review tool using Gemini AI for GitHub, GitLab, and Azure DevOps.

Project description

Gemini AI Code Reviewer

A GitHub Action that automatically reviews pull requests using Google's Gemini AI.

Features

  • Review your PRs using Gemini API
  • Give use comments and suggestions to improve the source codes

Setup

  1. To use this GitHub Action, you need an Gemini API key. If you don't have one, sign up for an API key at Google AI Studio.

  2. Add the Gemini API key as a GitHub Secret in your repository with the name GEMINI_API_KEY. You can find more information about GitHub Secrets here.

  3. Create a .github/workflows/code-reviewer-action.yml file in your repository and add the following content:

  • Github action:

    name: Gemini AI Code Reviewer
    
    on:
      issue_comment:
        types: [created]
    permissions: write-all
    jobs:
      gemini-code-review:
        runs-on: ubuntu-latest
        if: |
          github.event.issue.pull_request &&
          contains(github.event.comment.body, '/ai-review')
        steps:
          - name: Checkout Repo
            uses: actions/checkout@v3
    
          - name: Run Gemini AI Code Reviewer
            uses: HoangNguyen0403/ai_code_reviewer@latest
            with:
              GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
              GEMINI_API_KEY: ${{ secrets.GEMINI_API_KEY }}
              AI_MODEL: 'gemini-2.5-flash-preview-05-20' # Optional
              FILES_EXCLUDE: ['**/node_modules/**', '**/dist/**', '**/build/**'] # Optional
    
  • Gitlab CI:

    workflow:
      rules:
        - if: '$CI_PIPELINE_SOURCE == "merge_request_event" && $CI_MERGE_REQUEST_EVENT_TYPE == "opened"' # Or synchronize etc.
          when: always # Trigger on PR open/update if you want baseline analysis
    stages:
      - code-review
    
    gemini_code_review:
      stage: code-review
      image: python:3.10
      before_script:
        - python -m pip install --upgrade pip
        - pip install --no-cache-dir --upgrade ai-pr-reviewer
      variables:
        GITLAB_API_URL: "https://gitlab.com/api/v4"
        CI_PROJECT_NAMESPACE: "$CI_PROJECT_NAMESPACE"
        CI_PROJECT_ID: "$CI_PROJECT_ID"
        CI_MERGE_REQUEST_IID: "$CI_MERGE_REQUEST_IID"
        GITLAB_TOKEN: "$CI_JOB_TOKEN"
        GEMINI_API_KEY: "$GEMINI_API_KEY"
        AI_MODEL: "gemini-2.5-flash-preview-05-20" # Optional
        FILES_EXCLUDE: "['**/node_modules/**', '**/dist/**', '**/build/**']" # Optional
      script:
        - |
          latest_comment=$(python -c "import gitlab; gl = gitlab.Gitlab('$GITLAB_URL', private_token='$GITLAB_TOKEN'); mr = gl.projects.get($CI_PROJECT_ID).mergerequests.get($CI_MERGE_REQUEST_IID); notes = mr.notes.list(order_by='created_at', sort='desc'); print(notes[0].body if notes else '')")
          echo "Latest comment: $latest_comment"
          if [[ "$latest_comment" != *"/ai-pr-reviewer"* ]]; then
            echo "No /ai-pr-reviewer comment found. Skipping job."
            exit 0
          fi
        - ai-pr-reviewer gitlab
    
  • Azure Devops CI:

    trigger: none  # Prevents automatic triggers; pipeline is run manually or via REST API
    pr: none
    
    pool:
      vmImage: 'ubuntu-latest'
    
    steps:
      - task: UsePythonVersion@0
        inputs:
          versionSpec: '3.10'
      - script: |
          python -m pip install --upgrade pip
          pip install --no-cache-dir --upgrade ai-pr-reviewer
          ai-pr-reviewer azure
        displayName: 'Run AI PR Reviewer'
        env:
          AZURE_ORG_URL: $(AZURE_ORG_URL)
          AZURE_PROJECT: $(AZURE_PROJECT)
          AZURE_REPO_ID: $(AZURE_REPO_ID)
          AZURE_PULL_REQUEST_ID: $(AZURE_PULL_REQUEST_ID)
          AZURE_PAT: $(AZURE_PAT)
          GEMINI_API_KEY: $(GEMINI_API_KEY)
          AI_MODEL: "gemini-2.5-flash-preview-05-20" # Optional
          FILES_EXCLUDE: "['**/node_modules/**', '**/dist/**', '**/build/**']" # Optional      
    

if you don't set GEMINI_MODEL, the default model is gemini-2.0-flash. gemini-2.0-flash can be used for generating code, extracting data, edit text, and more. Best for tasks balancing performance and cost. For the detailed information about the models, please refer to Gemini models.

  1. Commit codes to your repository, and working on your pull requests.

  2. When you're ready to review the PR, you can trigger the workflow by commenting /ai-review in the PR.

How It Works

This GitHub Action uses the Gemini AI API to provide code review feedback. It works by:

  1. Analyzing the changes: It grabs the code modifications from your pull request and filters out any files you don't want reviewed.
  2. Consulting the Gemini model: It sends chunks of the modified code to the Gemini for analysis.
  3. Providing feedback: Gemini AI examines the code and generates review comments.
  4. Delivering the review: The Action adds the comments directly to your pull request on GitHub.

License

This project is licensed under the MIT License. See the LICENSE file for more information.

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