GAN-LLM

A web application that allows users to interact with Large Language Model and recognize the importance of privacy protection in large language model. You can experience the web frontend here: https://artessay.github.io/GAN-LLM/ .

Features

• User-friendly interface for making requests to the Large Language Model
• Responses are displayed in a chat-like format
• Select Models (GPT, GAN-LLM) based on your needs
• Highlight code syntax

Technologies Used

• For client, I used React.
• For server, I used Flask.

Setup Introduction

This guide will help you set up the repository on your local machine. Please follow these steps carefully to ensure a smooth setup process.

Cloning the repository

Use the following command to clone the repository:

git clone https://github.com/Artessay/GAN-LLM.git

Backend Setup

• Navigate to server directory

cd server # Navigate to the server directory:

• Install dependencies

pip install -r requirements.txt #install the backend dependencies

• Start the backend server by running the following command:

python app.py

Frontend Setup

• Navigate to the client directory:

cd client

• Run the following command to install the frontend dependencies:

npm install

• Set the REACT_APP_BACKEND_URL in the .env file to the URL of your backend server. For local development, use the following URL. Note: if you want to deploy it on the website, you should use your public IP address.

REACT_APP_BACKEND_URL=http://localhost:3080/

• Start the frontend app by running the following command:

npm start

Hosting Backend and Frontend in Same Port/URL

If you wish to host both the backend and frontend on the same port/URL, follow these steps:

• Build the frontend by running the following command in the client directory:

npm run build

• Copy the build directory to the server directory and rename it to frontend.

• Start the backend server using the instructions in the "Backend Setup" section.

• Once the setup process is complete, the frontend will be accessible at the URL of your backend server.

Usage

• Type in the input field and press enter or click on the send button to make a request to the Large Language Model
• Use control+enter to add line breaks in the input field
• Responses are displayed in the chat-like format on top of the page
• Generate code, including translating natural language to code

Contributing

This project welcomes contributions and suggestions for improvements. If you have any ideas, please feel free to open an issue or create a pull request.

Thank you for your consideration.