🧠 AI Code Review

An AI-powered VS Code extension that automatically reviews your JavaScript and TypeScript files using Google's Gemini model.

🚀 Features

• 🔍 Reviews your changed files automatically after each Git commit
• ⚙️ Highlights potential errors and improvements
• 💬 Displays AI review results in VS Code Output panel
• 🤖 Uses Gemini API for intelligent code insights

🧩 Usage

🪜 Step-by-step Guide

1. Clone or open your project in VS Code

   git clone <your-repo-url>
   cd <your-repo-folder>
   code .
   

2. Install dependencies

   npm install
   

3. Compile TypeScript (if the extension is written in TypeScript)

   npm run compile
   

4. Run the extension in the Extension Development Host

   • Press F5 (or select Run → Start Debugging)
   • A new VS Code window (Extension Development Host) will open

5. Trigger a review

   Make a code change, then stage and commit it to trigger the automatic review hook:

   git add .
   git commit -m "Test AI Review"
   

   The extension detects the commit and starts the AI Code Review. Results appear in View → Output → AI Code Review.

⚙️ Commands

🛠 Requirements

• ✅ Internet connection (for Gemini API)
• ✅ Node.js >= 16
• ✅ Git initialized in the workspace (git init)
• ✅ Valid Gemini API key configured inside your extension code or environment

🔐 Configuring the Gemini API Key

⚠️ Never commit your API keys to source control. Use environment variables or a secrets manager.

1. Create a .env file at the root of the extension project (not checked into Git):

   GEMINI_API_KEY=YOUR_GEMINI_API_KEY_HERE
   

2. In your extension code, load the key with dotenv (example):

   // src/extension.ts (example)
   import dotenv from "dotenv";
   dotenv.config();
   
   const GEMINI_API_KEY = process.env.GEMINI_API_KEY;
   

3. If you prefer other secure methods, configure the key in your CI environment or use OS-level environment variables instead.

📦 Installation (VSIX)

To package and install the extension manually:

1. Build and package the extension:

   npm run package
   # this should produce a .vsix file
   

2. Install the resulting .vsix in VS Code:

   • Open Extensions → the ... menu → Install from VSIX...
   • Select the generated .vsix file

🧩 Example: How the extension triggers reviews

The extension watches for local commits (or a Git hook) and then:

1. Collects changed files from the commit
2. Sends code snippets / diffs to the Gemini API
3. Receives AI suggestions and formats them
4. Writes the results to the Output panel under the AI Code Review channel

Implementation details vary — the above is a typical flow. See src/ for the actual implementation.

🐞 Troubleshooting

• No output visible

  • Open View → Output and choose AI Code Review from the dropdown.
  • Ensure the extension is running in the Extension Development Host (when debugging).
  • Confirm your Gemini API key is set and reachable.
  • Check the extension logs in the Debug Console for errors.

• Command appears but does nothing

  • Ensure your extension has been activated (open a workspace file in the Extension Development Host).
  • Verify package.json contains the command contribution and activationEvents required to register the command.

• Extension runs only in host mode

  • If the extension behaves differently in host vs. packaged mode, check platform-specific paths and permissions (e.g., where .env is loaded from).

✅ Recommended package.json snippets

• contributes (commands):

"contributes": {
  "commands": [
    {
      "command": "aiCodeReview.startReview",
      "title": "AI Code Review: Start Review"
    }
  ]
}

• activationEvents (example):

"activationEvents": [
  "onCommand:aiCodeReview.startReview",
  "onStartupFinished"
]

🧪 Running tests (if available)

npm test

🤝 Contributing

Contributions are welcome. Please open issues and PRs for bugs, feature requests, or improvements.

1. Fork the repository
2. Create a branch: git checkout -b feat/your-feature
3. Make your changes and add tests
4. Submit a PR with a clear description and screenshots if applicable

📝 License

MIT © Pankaj Shahare

Made with ❤️ — happy coding!