Groq Code Completion for VSCode

AI-powered code completion using Groq's lightning-fast inference API. Get intelligent code suggestions with low latency using models like Mixtral, Llama 3, and more.

Features

• Smart Context Detection: Automatically detects where to complete code

  • Completion markers (// TODO:, // COMPLETE:, etc.)
  • Empty function bodies
  • Empty code blocks
  • Current cursor position

• Multi-file Context: Analyzes all open tabs to understand your project structure

• Fast Streaming: See code being generated in real-time

• Multiple Models: Choose from various Groq models optimized for different use cases

Quick Start

Prerequisites

1. Groq API Key: Get one from console.groq.com
2. Node.js: Version 16.x or higher
3. VSCode: Version 1.85.0 or higher

Installation

1. Clone this repository:

   git clone <repository-url>
   cd groq-code-completion
   

2. Install dependencies:

   npm install
   

3. Compile the extension:

   npm run compile
   

4. Open in VSCode:

   code .
   

5. Press F5 to launch a new Extension Development Host window

6. Configure your API key in VSCode settings:

   • Open Settings (Ctrl/Cmd + ,)
   • Search for "Groq"
   • Enter your API key

Usage

Method 1: Using Markers

Add a marker where you want AI to complete code:

function calculateTotal(items) {
    // TODO: implement calculation logic
}

Then press Ctrl+Shift+G (Cmd+Shift+G on Mac)

Method 2: Empty Functions

def process_data(data):
    # Place cursor here and press Ctrl+Shift+G

Method 3: Empty Blocks

if (user.isAuthenticated) {
    // Cursor here + Ctrl+Shift+G
}

Method 4: Anywhere

Just place your cursor and press the hotkey!

Configuration

Access settings through VSCode Settings (search for "Groq"):

Available Models

• mixtral-8x7b-32768: Best for code (32k context) - Recommended
• llama3-70b-8192: Large, powerful model (8k context)
• llama3-8b-8192: Fast, efficient model (8k context)
• gemma-7b-it: Lightweight model
• gemma2-9b-it: Improved lightweight model

Tips for Best Results

1. Use descriptive markers:

   // TODO: implement binary search with error handling
   

2. Keep related files open: The AI uses all open tabs for context

3. Define function signatures first:

   def merge_sort(arr: List[int]) -> List[int]:
       # AI will implement based on signature
   

4. Adjust temperature:

   • Low (0.1-0.3): Predictable, conventional code
   • High (0.5-0.7): More creative solutions

Development

Building from Source

# Install dependencies
npm install

# Compile TypeScript
npm run compile

# Watch mode (auto-compile)
npm run watch

# Run linter
npm run lint

Packaging

To create a .vsix file for distribution:

npm install -g vsce
vsce package

Publishing

vsce publish

Troubleshooting

"No completion generated"

• Try a different model (mixtral-8x7b-32768 is most reliable)
• Increase maxTokens in settings
• Provide more context with comments

"API key not set"

• Check VSCode settings (Groq Code Completion section)
• Or set environment variable: export GROQ_API_KEY=your_key

Slow responses

• Try llama3-8b-8192 for faster inference
• Reduce contextFileLimit in settings
• Disable streaming for single-shot completion

Incorrect completions

• Add comments explaining what you need
• Open related files for better context
• Use more specific markers

Contributing

Contributions are welcome! Please:

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Submit a pull request

License

MIT License - see LICENSE file for details

Acknowledgments

• Built with the Groq SDK
• Inspired by GitHub Copilot and similar tools
• Thanks to the VSCode extension API documentation