{"id":25065664,"url":"https://github.com/programming-sai/fertilizer-recommendation-system-client-server","last_synced_at":"2026-05-09T05:31:40.591Z","repository":{"id":275123909,"uuid":"925141669","full_name":"Programming-Sai/Fertilizer-Recommendation-System-Client-Server","owner":"Programming-Sai","description":"The Fertilizer Recommendation System is a web-based application designed to provide tailored fertilizer recommendations for different crops based on various factors like growth stage, soil properties, climate, and more. 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It consists of a **frontend** built with React and a **backend** powered by Flask, using Prolog for inference.\n\n### Features\n\n- **Real-time Fertilizer Recommendations** based on multiple parameters.\n- **Interactive UI** allowing users to input their crop and environmental data.\n- **Backend Inference Engine** using Prolog to calculate optimal fertilizer recommendations.\n\n## Tech Stack\n\n- **Frontend**: React, JSX, Vite (with `fetch` for API requests)\n- **Backend**: Flask, Python, SWI-Prolog\n- **Docker**: For containerization and deployment\n\n## Installation\n\nTo get started with the project locally, follow the steps below:\n\n### 1. Clone the Repository\n\n```bash\ngit clone --recurse-submodules https://github.com/Programming-Sai/Fertilizer-Recommendation-System-Client-Server.git\ncd Fertilizer-Recommendation-System-Client-Server\n```\n\n\u003e [!NOTE]\n\u003e If you have already cloned the repository without --recurse-submodules, you can initialize the submodules separately with:\n\n```bash\ngit submodule update --init --recursive\n```\n\n## Repositories\n\n- **Frontend**: [Fertilizer Recommendation System Client](https://github.com/Programming-Sai/Fertilizer-Recommendation-System.git)\n- **Backend**: [Fertilizer Recommendation System Server](https://github.com/Programming-Sai/Fertilizer-Recommendation-Engine-PROLOG.git)\n\n### 2. Set Up the Backend\n\n1. Navigate to the `server` directory.\n\n   ```bash\n   cd server\n   ```\n\n2. Install the necessary dependencies:\n\n   ```bash\n   pip install -r requirements.txt\n   ```\n\n3. Start the backend server:\n\n   ```bash\n   python scripts/server.py\n   ```\n\n   The backend should now be running at `http://localhost:5000`.\n\n### 3. Set Up the Frontend\n\n1. Navigate to the `client` directory.\n\n   ```bash\n   cd client\n   ```\n\n2. Install dependencies:\n\n   ```bash\n   npm install\n   ```\n\n3. Start the frontend:\n\n   ```bash\n   npm run dev\n   ```\n\n   The frontend should now be accessible at `http://localhost:3000`.\n\n### 4. Running the Full Application Using Docker\n\n1. From the root directory, run:\n\n   ```bash\n   docker-compose up --build\n   ```\n\n   - To stop it you can run\n\n   ```bash\n     # Ctrl + C  # If running in the foreground\n     docker-compose down  # To stop and remove containers\n   ```\n\n   This will build and run the frontend and backend containers.\n\n## Usage\n\nOnce both the frontend and backend are running, you can navigate to `http://localhost:3000` in your browser and start using the application.\n\n### How to Use\n\n- Navigate to `Predict` from the Navbar to get to the parameters form\n- Input the required crop, environmental and soil parameters.\n- Click **Get Recommendations** to receive fertilizer recommendations tailored to your inputs.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fprogramming-sai%2Ffertilizer-recommendation-system-client-server","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fprogramming-sai%2Ffertilizer-recommendation-system-client-server","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fprogramming-sai%2Ffertilizer-recommendation-system-client-server/lists"}