CONTRIBUTION.md

Contribution Guidelines

Prerequisites

Architecture

The bot will be implemented using the following technologies:

• Discord.py: A Python library for interacting with the Discord API. Discord.py Documentation
• Text Embeddings: Textual data will be converted into numerical representations for semantic analysis. Introduction to Text Embeddings
• Vector Database: Textual data will be stored in a vector database for efficient semantic search. Vector Database
• FastAPI: For building a web API to interface with the bot. FastAPI Documentation
• Docker: For containerization and deployment. Docker Documentation
• Celery (Optional): For task queue management and asynchronous processing. Celery Documentation -- RabbitMQ (Optional): Message broker for inter-component communication. RabbitMQ Documentation

We follow a 'learn as you do' motto, so don’t hesitate to pick up issues that interest you, even if you're unfamiliar with the details. Support is always available!

Installation

1. Clone the Repository

git clone https://github.com/UB-AICLUB/RagBot.git
cd RagBot

2. Install Dependencies by Module

Each module has its own virtual environment and dependencies. You'll need to set up each environment individually based on the module you're working on.

API Module

Navigate to the API directory:

cd API

Create a virtual environment and install the necessary Python packages:

python -m venv .venv
source .venv/bin/activate  # On Windows use `.venv\Scripts\activate`
pip install -r requirements.txt

Ensure that the .env file is set up with any required environment variables for the API.

Client Module

Navigate to the client directory:

cd client

Create a virtual environment and install the necessary Python packages:

python -m venv .venv
source .venv/bin/activate  # On Windows use `.venv\Scripts\activate`
pip install -r requirements.txt

Set up your Discord bot token and any other necessary configuration by creating a .env file:

DISCORD_TOKEN=your_discord_token

This file is required only if you want to test the bot on your server

Task Queue Module

If you're working with the task queue module, navigate to the directory:

cd task_queue

Set up the environment and install dependencies as needed following the pattern used for the other modules.

This will spin up all services, including the API and client components.

Setting up Pre-Commit Hooks

We use global linting and formatting rules across all modules. Make sure to follow them by running the linters and formatters from the root directory.

After cloning the repository and installing dependencies from requirements.txt, make sure to install pre-commit hooks:

pre-commit install

To check for linting issues:

flake8 .

To automatically format code:

black .

To check all pre-commit issues

pre-commit run --all-files

Ensure you follow these rules before making a pull request.

Run the Modules

Running the API server (FastAPI)

To run the FastAPI server for the API module, navigate to the API directory and run:

uvicorn main:app --reload

The API will now be available at http://127.0.0.1:8000.

Running the Discord Bot

To run the Discord bot, navigate to the client directory and execute:

python main.py

To run the whole app(optional)

You can easily start the entire application using Docker Compose. This will launch all necessary services defined in your docker-compose.yaml file.

From the root directory, execute the following command:

docker-compose up --build

This command will build and start all services, including the API and client components, allowing you to run the application seamlessly.

Make sure you have Docker and Docker Compose installed on your machine before executing this command.