🌾 ArgoVision (AgroVision)

ArgoVision is a comprehensive, AI-powered Progressive Web App (PWA) designed to empower farmers by providing actionable insights, predictive analytics, and real-time data to maximize agricultural yield and profitability.

🔗 Live Demo: https://agro-vision-frontend.vercel.app/

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✨ Key Features

• 🤖 Agentic AI Assistant
  An intelligent, context-aware AI agent that connects all predictive models and data sources to answer farmers' queries intuitively.

• 🌱 Crop Prediction
  Recommends the most suitable crops based on soil metrics and environmental conditions.

• 🧪 Fertilizer Prediction
  Suggests optimal fertilizers to improve soil health and crop growth.

• 📈 Market Price Prediction
  Forecasts future market prices for crops to help farmers make informed selling decisions.

• 🌦️ Real-Time Weather
  Provides accurate, up-to-date weather forecasts to plan farming activities.

• 🌍 Multilingual Support
  Accessible to farmers across different regions in their native languages.

• 📱 PWA Ready
  Installable on any mobile device for a seamless, app-like experience even with spotty internet connectivity.

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📁 Project Structure

The repository is organized into three main directories:

1. /frontend

• Framework: React.js
• Deployment: Vercel
• Role: Handles user interactions, displays PWA features, multilingual UI, and presents AI predictions & weather data seamlessly.

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2. /backend

• Framework: FastAPI (Python)
• Deployment: Hugging Face Spaces
• Role: Manages the Agentic AI logic, fetches real-time weather data, and acts as a gateway to specialized machine learning models.

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3. /website

• Role: Serves as the informational landing page for the project, explaining benefits, PWA installation, and documentation.

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🛠️ Tech Stack

• Frontend: React, Progressive Web App (PWA) APIs
• Backend: FastAPI, Python
• AI / Machine Learning: Custom Models (Crop, Fertilizer, Market) deployed on Hugging Face
• Orchestration: Agentic AI workflow for seamless tool usage
• Hosting: Vercel (Frontend), Hugging Face (Backend & Models)

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🌐 Backend API Endpoints

The backend is hosted on Hugging Face Spaces and exposes several key RESTful APIs powered by FastAPI.

🔗 API Docs (Swagger UI): View Interactive Docs

Core Features & Integrations

🔹 POST /chat (Agentic AI)

• Description:
  The main conversational endpoint that connects farmers to the Agentic AI.
  Interprets queries in multiple languages and dynamically routes them to appropriate predictive models.

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🔹 POST /predict/crop

• Description:
  Accepts soil and environmental data:

  • Nitrogen
  • Phosphorous
  • Potassium
  • Temperature
  • Humidity
  • pH
  • Rainfall

  Returns the most optimal crop recommendation.

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🔹 POST /predict/fertilizer

• Description:
  Suggests the best fertilizer based on:
  • Current crop type
  • Soil nutrient levels

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🔹 GET /predict/market-price

• Description:
  Returns:

  • Market price forecasts
  • Historical trends

  Helps farmers with financial planning.

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🔹 GET /weather

• Description:
  Fetches real-time localized weather data and forecasts for better farming decisions.

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Note: Exact endpoint paths and payload structures can be verified via the interactive /docs endpoint.

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🚀 Getting Started (Local Development)

🔧 Prerequisites

• Node.js (v16+)
• Python (3.9+)

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1. Clone the Repository

git clone https://github.com/your-username/ArgoVision.git
cd ArgoVision

2. Setup Backend

cd backend
python -m venv venv
source venv/bin/activate  # On Windows use `venv\Scripts\activate`
pip install -r requirements.txt
uvicorn main:app --reload

3. Setup Frontend

cd ../frontend
npm install
npm start

🤝 Contributing

We welcome contributions! Feel free to submit a Pull Request.

For major changes, please open an issue first to discuss what you would like to change.

📄 License

This project is licensed under the MIT License — see the LICENSE file for details.