Codera AI 🚀

Introduction 📜

This project aims to modernize legacy codebases by transforming them into modern, efficient, and maintainable code. Through an AI-driven analysis and transformation process, legacy systems can be upgraded to meet current standards and technologies.

Product demo: https://codera-ai.vercel.app/chat

Google Colab AI Prototype: https://colab.research.google.com/drive/1XaA3BmUssSqr9G4l3EeKW05fx0eOYf8V?usp=sharing

Implementation Plan 🛠️

1. Parser 📑

• Creates a single file (e.g., JSON) containing all code from the legacy project.

2. Code Analyser 🔍

• Reads the code archive.
• Summarizes the code to create a prompt for further actions.

3. Code Suggestions 💡

• Generates code suggestions based on the summary, which can either be presented as text or used to directly overwrite the existing files.

4. Personalized Prompts 👤

• Tailors prompts based on the user's role (Developer, DevOps) and experience.

5. Authentication and WebClient 🔐

• Manages user sessions and interactions through a web interface.

6. Image Design from Code Summary 🎨

• Converts code summaries into visual representations.

7. Textual Advice from Code Summary 📝

• Provides written advice based on the code analysis.

Workflow 🔄

1. User Registration: Users sign up on the platform and set their role and experience level.
2. Repository Upload: Users upload their GitHub repository (archive or files) to the platform.
3. Code Segmentation: The system creates a JSON file containing the entire codebase, which is then used for analysis.
4. Code Analysis: The code is analyzed by the Code Analyser, interacting with an LLM to produce a logic summary.
5. Agent Creation: Based on the logic summary, various agents (Developer, UX/UI, etc.) are created to provide specific recommendations and actions.
6. Personalized Recommendations: Users receive suggestions tailored to their role, which can be used to directly modify and update the code.

Getting Started 🌟

Follow these instructions to set up and run the project on your local machine for development and testing purposes.

Prerequisites 📋

• Node.js and npm (for the Next.js project)
• Docker (for running Dockerized services)

Setting up and running the React project 🖥️

1. Clone the repository to your local machine.
2. Install the dependencies.

       npm install

3. Start the development server.

       npm run dev

Building and running the Server Docker image 🐳

1. Navigate to the directory containing the Server Dockerfile.
2. Build the Docker image.

       docker build -t server-image .

3. Run the Docker container.

       docker run -p 8000:8000 server-image

Building and running the LLM Docker image 🐳

1. Navigate to the directory containing the LLM Dockerfile.
2. Build the Docker image.

       docker build -t llm-image .

3. Run the Docker container.

       docker run -p 11434:11434 llm-image

Contributing 🤝

Guidelines for contributing to the project, including coding standards, pull request process, etc.

License 📄

Information about the project's license.

Contact 📬

How to get in touch with the project team.