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.

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

5. 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.