🌾 SmartAgri Agentic AI

SmartAgri Agentic AI is an intelligent farming assistant that uses AWS and NVIDIA Agentic AI technologies to help farmers make data-driven decisions about soil, irrigation, and crop management.

🚀 Tech Stack

Frontend: Streamlit
Backend: FastAPI
Model: Llama-3 NIM, Retrieval Embedding NIM
Infrastructure: AWS EKS + NVIDIA NIM microservices

🧠 Architecture

Architecture

🧩 Features

Crop yield prediction based on soil and weather data
Real-time advice using Llama-3 reasoning
Data retrieval from agricultural knowledge base (Retrieval NIM)
User-friendly interface built in Streamlit

⚙️ Setup Instructions

Clone repo:
bash git clone https://github.com/Kesava09-gif/SmartAgri-AgenticAI.git
Run backend (FastAPI):
bash cd backend/app uvicorn main:app --reload
Run frontend (Streamlit):
bash cd frontend streamlit run app.py markdown banner block

🌾 SmartAgri Agentic AI 🌾

AI that grows with the farmer — built on AWS × NVIDIA
Empowering farmers with real-time intelligence, sustainability, and autonomous decision-making.

🌱 SmartAgri Agentic AI is an autonomous agriculture assistant that leverages LLM intelligence, IoT data, and agentic reasoning to help farmers make smarter, faster, and more sustainable decisions.

🌾 AI-powered farming assistant built with AWS & NVIDIA Agentic AI. Visit Project Repository

🌾 SmartAgri Agentic AI

🚀 Your AI-powered Farming Assistant

SmartAgri Agentic AI helps farmers make smart crop and soil decisions using artificial intelligence.
It provides personalized recommendations for crops, fertilizers, and soil management based on input data.

🧠 Features

🌱 AI-based crop recommendation system
🧪 Soil-type analysis (Loamy, Sandy, Clay, etc.)
💧 Smart irrigation & fertilizer suggestions
📊 Interactive Streamlit dashboard
☁️ Hosted online via Streamlit Cloud

🏗️ Tech Stack

Technology	Purpose
🐍 Python	Core development
⚡ Streamlit	Front-end UI
🤖 OpenAI / Agentic Models	AI logic
☁️ GitHub + Streamlit Cloud	Hosting & Deployment

🧩 Folder Structure

SmartAgri-Agentic-AI/
│
├── streamlit_app.py        # Main Streamlit app
├── requirements.txt        # Dependencies
├── README.md               # Project documentation
├── data/                   # Sample datasets (optional)
└── LICENSE

⚙️ Installation (For Local Run)

# Clone the repository
git clone https://github.com/kesava09-gif/smart-agri-agentic-ai.git
cd smart-agri-agentic-ai

# Install dependencies
pip install -r requirements.txt

# Run the app
streamlit run app.py