Herbez/DigitalAgri_Advisory

A Flask-based web application that provides machine learning-powered crop recommendations for Rwandan farmers. # DigitalAgri — Smart Farming for Rwanda DigitalAgri is a platform designed to empower Rwandan agricultural cooperatives and farmers with data-driven insights. By leveraging machine learning and real-time weather data, the platform provides tailored crop recommendations, planting calendars, and analytical tools to optimize agricultural productivity across Rwanda's 30 districts. --- ## Getting Started Follow these steps to set up the project on your local machine. ### 1. Clone the Repository ```bash git clone cd DigitalAgri ``` ### 2. Create a Virtual Environment It is recommended to use a virtual environment to manage dependencies. ```bash # Windows python -m venv venv .\venv\Scripts\activate # macOS/Linux python3 -m venv venv source venv/bin/activate ``` ### 3. Install Requirements Install the necessary Python packages using pip. ```bash pip install -r requirements.txt ``` ### 4. Run the Application Start the Flask development server. ```bash python app.py ``` The application will be available at `localhost`. > Note: If you want the weather feature to work with OpenWeatherMap, add this line below line 15. Add `OPENWEATHER_API_KEY at line 17 in `app.py` and configure your OpenWeather API key. --- ## User Guide ### 1. Signup as a Cooperative - Navigate to the **Sign Up** page from the landing screen. - Enter your cooperative name, email, phone number, and select your district. - Once registered, you will be redirected to the Cooperative Dashboard. ### 2. Register a Farmer - From the sidebar, click on **Farmers**. - Use the "Add New Farmer" form to register farmers in your cooperative. - Provide their name, phone number, district, farm size (Ha), and gender. ### 3. Look for Weather Forecast - Navigate to the **Weather Forecast** section in the sidebar. - Select a district to view real-time weather conditions and a 7-day forecast. - This tool helps you advise farmers on the best time for planting and harvesting based on predicted rainfall a …