🚀 Devopscode

Welcome to the devopscode’s README! This project integrates backend and frontend services, a VS Code extension, and data processing to help developers streamline code optimization and conversion.

🚀 Authors (sorted in alphabetical order)

• @estarriol43
• @guan404ming
• @lytt925
• @ruby0322

🚀 Running the Project

This project consists of four core components, each responsible for specific functionalities. It uses Nx, uv, and Bun for efficient dependency management.

Here’s an example of the basic commands to get the project running:

uv v
source .venv/bin/activate
bun install
bun dev

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🚀 Project Structure

1. Backend (hack-llm-backend)

The backend is built using FastAPI, a modern web framework for building APIs in Python. It offers code optimization, conversion, language detection, and Kubernetes deployment functionalities. The backend efficiently handles requests and returns results in a structured format.

• Key Features:
  • Code optimization, analysis and erro detection using LLM
  • Deployment of user-provided code to Kubernetes
  • Integration with various LLM tools ex. Langchain, LangGraph and LandSmith

2. Web (hack-web-frontend, hack-web-backend)

The frontend is developed using React and TypeScript, providing a dynamic UI to interact with backend services. Users can input code, view optimization results, and manage deployments.

• Key Features:
  • User-friendly interface for code submission
  • Real-time display of code optimization results
  • Integration with GitHub to fetch code snippets

3. VS Code Extension (hack-vsc-extension)

This VS Code extension brings code conversion and optimization tools directly into the editor, allowing developers to stay within their development environment.

• Key Features:
  • Commands for code conversion and optimization
  • Seamless integration with the backend API

4. Data Processing (hack-data)

Handles data processing tasks, particularly the conversion of TensorFlow TFRecord files into JSONL format, ensuring the data is easy to work with.

• Key Features:
  • Efficient parsing of TFRecord files
  • Conversion to JSONL for easier integration

🚀 Conclusion

Together, these four core components provide a complete solution for code optimization and conversion, helping developers enhance code quality and performance. We hope you enjoy using devopscode, and we welcome any suggestions or feedback you may have!