Code Converter App

Description

The Code Converter App is a versatile tool that allows users to convert, debug, and analyze code written in various programming languages. It utilizes the OpenAI GPT-3.5 turbo model to provide dynamic code conversion, debugging assistance, and code analysis.

Deployed Links

• Live Demo
• Backend

Tech Stack

• Frontend: HTML, CSS, JavaScript
• Backend: Node.js, Express.js, OpenAI API

Functionalities

• Code Conversion: Convert code from one programming language to another, supporting a variety of languages.
• Code Debugging: Get debugging assistance by submitting code and receiving error analysis and potential solutions.
• Code Quality Analysis: Receive an analysis of code quality, consistency, performance, and documentation.
• User-Friendly Interface: Intuitive interface for inputting code and choosing functionalities.
• Real-Time Interaction: Communicate with the OpenAI GPT-3.5 turbo model in real time for interactive code-related tasks.

Route Endpoints

1. Base Endpoint: /

   • Description: Base endpoint of the application.

2. Code Conversion Endpoint: /convert

   • Description: Convert code from one language to another.
   • Method: POST
   • Request Body:

     {
         "code": "code snippet",
         "language": "target language"
     }
     

3. Code Debugging Endpoint: /debug

   • Description: Provide debugging assistance for code.
   • Method: POST
   • Request Body:

     {
         "code": "code snippet",
         "language": "programming language"
     }
     

4. Code Quality Check Endpoint: /qc

   • Description: Analyze code quality, consistency, and performance.
   • Method: POST
   • Request Body:

     {
         "code": "code snippet",
         "language": "programming language"
     }
     

Screenshots

• To be added

Areas of Improvement

• Enhanced User Experience: Improve the user interface and provide clearer instructions for each functionality.
• Support More Languages: Expand the range of supported programming languages for conversion and analysis.
• Error Handling: Implement robust error handling and provide meaningful error messages to users.
• Optimize Performance: Optimize backend performance to handle concurrent requests efficiently.
• Real-time Interaction: Explore real-time chat interaction with the GPT-3 model for a more interactive experience.

How to Run Locally

1. Clone the repository: git clone repository-url
2. Install dependencies: npm install
3. Configure environment variables: Create a .env file and set up the required variables.
4. Run the backend: npm start
5. Clone and set up the frontend repository: git clone frontend-repo-url && npm install && npm start

Feel free to contribute to the project by submitting issues and pull requests!