FénixGPT 🦖

Open-Source Chatbot for ISCTE Sintra Student Course Registration
Forked from DocsGPT

Project structure

• Application - Flask app (main application)

• Extensions - Chrome extension

• Scripts - Script that creates similarity search index and store for other libraries.

• Frontend - Frontend uses Vite and React

QuickStart

Note: Make sure you have docker installed

1. Dowload and open this repository with git clone https://github.com/Sphincz/FenixGPT.git

2. Create an .env file in your root directory and set the env variable OPENAI_API_KEY with your openai api key and VITE_API_STREAMING to true or false, depending on if you want streaming answers or not It should look like this inside:

   OPENAI_API_KEY=Yourkey
   VITE_API_STREAMING=true
   

3. Run ./run-with-docker-compose.sh

4. Navigate to http://localhost:5173/

To stop just run Ctrl + C

Development environments

Spin up mongo and redis

For development only 2 containers are used from docker-compose.yaml (by deleting all services except for redis and mongo). See file docker-compose-dev.yaml.

Run

docker compose -f docker-compose-dev.yaml build
docker compose -f docker-compose-dev.yaml up -d

Run the backend

Make sure you have Python 3.10 or 3.11 installed.

1. Export required environment variables

export CELERY_BROKER_URL=redis://localhost:6379/0   
export CELERY_RESULT_BACKEND=redis://localhost:6379/1
export MONGO_URI=mongodb://localhost:27017/docsgpt

2. Prepare .env file Copy .env_sample and create .env with your OpenAI API token
3. (optional) Create a python virtual environment

python -m venv venv
. venv/bin/activate

4. Change to application/ subdir and install dependencies for the backend

cd application/ 
pip install -r requirements.txt

5. Run the app python wsgi.py
6. Start worker with celery -A app.celery worker -l INFO

Start frontend

Make sure you have Node version 16 or higher.

1. Navigate to /frontend folder
2. Install dependencies npm install
3. Run the app npm run dev

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