Crop Recommendation System

This project is an AI-powered web application designed to assist farmers in making informed crop choices based on various inputs such as region, soil type, investment amount, and available resources.

Usage: https://agrivision-innovators.streamlit.app/

Features

• User Authentication (Sign up and Login)
• Region and Soil Type Selection
• Seasonal and Financial Inputs (investment, area, ROI expectations)
• Resource Specification (water, fertilizers, machinery, labor)
• Real-time Weather Data Integration (OpenWeather API)
• Static Agricultural Data (Historical crop prices and stats for India and Pakistan)
• AI-powered Crop Recommendations (Meta-Llama 3.1 LLM)
• Detailed Suggestions on Projected Return, Investment Ratio, and Risk Level
• Interactive UI with expandable recommendation sections

Technologies Used

• Streamlit for building the web interface
• Meta-Llama 3.1 hosted on the Together platform for generating crop recommendations
• OpenWeather API for real-time weather data
• Python for backend logic and data processing

How it Works

1. Users provide region, soil type, and resources available.
2. The application uses real-time weather data and static agricultural data to generate personalized crop recommendations.
3. Each recommendation includes projected returns, investment ratios, and associated risks.