Q-RICE API 🌾

Welcome to the Q-RICE API! This API serves as the backend for the Q-RICE project, providing endpoints for machine learning predictions related to rice varieties, diseases, nutrient deficiencies, and seed quality.

Getting Started

To get started with the Q-RICE API, follow these steps:

Clone the Repository

git clone https://github.com/amrimuf/qrice
cd qrice

Download Machine Learning Models

Download the required machine learning models from here and place them into the ./models folder.

Set Up the Machine Learning Server

Navigate to the ml-server directory and install the required Python dependencies:

cd ml-server
pip install -r requirements.txt

Start the ML server by running:

python main.py

Set Up the API

Navigate to the api directory and install the required Node.js dependencies:

cd ../api
npm install

Copy the .env.example file and configure the .env file with your environment variables:

cp .env.example .env

Run Sequelize commands to create, migrate, and seed the database:

sequelize db:create
sequelize db:migrate
sequelize db:seed:all

Run the API server in development mode, use:

npm run dev

GCP Architecture