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code-aura

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CLI tool for semantic code search and exploration

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  • code-aura
  • code-aura/index.js

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Readme

Code Aura 🔍✨

A powerful CLI tool for semantic code search and exploration using AI-powered embeddings and GROQ's lightning-fast inference.

Code Aura Node.js GROQ

Features

  • Semantic Code Search: Find code using natural language queries
  • AI-Powered Explanations: Get detailed explanations of code snippets
  • Visualization: Generate HTML and image visualizations of search results
  • Multi-language Support: Works with JavaScript, TypeScript, Python, Java, C++, and more
  • Smart Chunking: Intelligent code splitting for better search results

Installation

npm install -g code-aura

Or use directly with npx:

npx code-aura@latest <command>

Quick Start

  1. Get a GROQ API Key:

  2. Setup your codebase:

    code-aura setup /path/to/your/codebase
  3. Search your code:

    code-aura search

Usage

Setup a Codebase

code-aura setup /path/to/your/project
code-aura search

Generate HTML Visualization

code-aura html "your search query"

Explain a File

code-aura explain path/to/file.js

Debug Information

code-aura debug

Clear Cache

code-aura clear

Commands

  • setup <path> - Process a codebase for semantic search
  • search - Interactive semantic search
  • html <query> - Generate HTML visualization for a query
  • explain <file> - Get explanation of a specific file
  • debug - Show debug information
  • clear - Clear cached data
  • reprocess - Reprocess codebase with improved chunking

API Key Setup

The tool will automatically prompt you for your GROQ API key on first run. You can:

  1. Enter it interactively when prompted
  2. Create a .env file with GROQ_API_KEY=your_key_here
  3. Set it as an environment variable

Supported Languages

  • JavaScript/TypeScript (.js, .jsx, .ts, .tsx)
  • Python (.py)
  • Java (.java)
  • C/C++ (.c, .cpp, .h, .hpp)
  • Ruby (.rb)
  • Go (.go)
  • Rust (.rs)
  • PHP (.php)
  • C# (.cs)

How It Works

  1. Code Processing: Splits your code into semantic chunks
  2. Embedding Generation: Creates vector embeddings for each chunk
  3. Semantic Search: Uses cosine similarity to find relevant code
  4. AI Explanation: Leverages GROQ's LLM for intelligent code explanations

Performance

  • Fast processing with optimized chunking
  • Efficient similarity search
  • Low memory footprint
  • Quick response times with GROQ's accelerated inference

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

MIT License - feel free to use this tool for your projects!

Support

For issues and questions:

Star History

If you find this tool useful, please give it a star ⭐ on GitHub!


Developed by Harjas Singh
LinkedIn | GitHub ```