Table of Contents

• Introduction
• Demo
• File Structure
• Technologies Used
• Installation Guide
• Usage

Bevo-Bud-The-GPT

Current and prospective students at UT Austin often struggle to find specific information efficiently through traditional university resources, such as the website or official channels. Bevo Bud The GPT aims to easily solve this issue by empowering students with the information they need seamlessly.

Bevo Bud The GPT is a full-stack web application where users can ask UT-related questions and get answers from the AI chatbot. Bevo Bud, the AI chatbot, was fined-tuned on archived reddit posts from the the r/UTAustin subreddit (see the model-src folder to learn more its development).

Demo

File Structure

├── COE379_Project_4_Report.pdf
├── Demo.gif
├── Project Proposal.pdf
├── README.md
├── client
│   ├── Dockerfile
│   ├── docker-compose.yaml
│   ├── index.html
│   ├── package-lock.json
│   ├── package.json
│   ├── pnpm-lock.yaml
│   ├── public
│   │   └── bevo.png
│   ├── src
│   │   ├── App.css
│   │   ├── App.tsx
│   │   └── *and others
│   └── *and others
├── docker-compose.yaml
├── model-src
│   ├── previewing.ipynb
│   ├── processing.ipynb
│   └── finetuning.ipynb
├── requirements.txt
├── server
│   ├── Dockerfile
│   ├── data
│   │   └── dump.rdb
│   ├── docker-compose.yaml
│   └── server.py

Technologies Used

• Frontend
  • React + Typescript (Mantine UI)
  • Node.js
• Backend
  • Python
  • Flask
  • HuggingFace
• Database
  • Redis
• Services
  • Docker
  • Docker-Compose

Installation

You can easily start this application on your local machine by following the steps below:

• Note: You will need to have the latest version of Docker installed and at 8GB of storage to run this project locally. This application also uses ports 3000 (client) and 5000 (server).

1. To run this application, first clone the repository

   git clone

2. Next, change into the directory of this repository

   cd Bevo-Bud-The-GPT

3. Run the following docker-compose command to start the application!

   • Note: This step may take a while

   docker-compose up -d

4. And that's it! Now you can access the application by visiting http://localhost:3000 in your browser.

   • Additional Notes:

     • If you would like to stop the application, you can run the following command:

       docker-compose down

     • Each stack of the application is running in a separate container. If you would like to stop a specific container, you can change into the directory of the container and run docker-compose up within that directory. This is because both client and server folders have their own docker-compose files.

     • If you would like to see the logs of the application, you can run the following command:

       docker-compose logs -f

     • You only need to run the docker-compose up ... command with the --build flag once as the image will. After that, you can re-run docker-compose up without the --build flag to start the application.

Usage:

Requests supported to the inference server:

	Route	Method	Returns
1	/	GET	Info regarding the model
2	/info	GET	Metadata regarding the model
3	/question	POST	Inference response to message query
4	/conversations	GET, DELETE	Stored conversation queries from Redis database