🦇 Terra Intelligence

Precision AI Agricultural Ecosystem

Built for modern farming, Terra Intelligence is a high-performance command center that transforms environmental and biological data into mission-critical insights. Designed with a tactical "Batman-inspired" HUD, the platform prioritizes speed, precision, and actionable intelligence.

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🚀 Core Features

🔍 AI Disease Scanner

• Computer Vision: Powered by OpenAI GPT-4o Vision.
• Function: Real-time diagnostic scanning of crop images to identify pathogens, nutrient deficiencies, and environmental stress.

🌾 Smart Crop Advisor

• Intelligence: Multi-variate recommendation engine.
• Function: Optimizes crop selection by analyzing soil pH, nutrient levels (NPK), and local climate data.

☁️ Weather Intelligence (Intel)

• Integration: Real-time data via OpenWeatherMap API.
• Function: Hyper-local forecasts, environmental tracking, and severe weather alerts integrated into the HUD.

🧪 Precision Fertilizer Engine

• Calculations: Automated NPK ratio computations.
• Function: Minimizes chemical runoff and maximizes yield by calculating exact plant requirements.

🤖 Interactive AI Assistant

• Expertise: 24/7 expert agricultural consultation.
• Function: An LLM-powered interface for troubleshooting, agronomic advice, and rapid system queries.

🛰️ Mission Command Dashboard

• HUD: Centralized real-time hub.
• Function: Displays system health, live weather stats, and rapid module shortcuts in a unified tactical dashboard.

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🛠️ Technology Stack

Frontend (The HUD)

• Core: React 19, Vite v8
• Styling: TailwindCSS v3.4 (Utility-first tactical design)
• Animations: Framer Motion (Fluid "Spring" physics for micro-interactions)
• Icons: Lucide-React (Technical glyphs)
• Navigation: React Router DOM v7

Backend (The Core)

• Architecture: FastAPI (Python 3.11)
• Server: Uvicorn (Asynchronous high-performance ASGI)
• Protocols: RESTful API with modular routing system
• Dependency Management: pip (requirements.txt)

AI & Services

• Primary Vision AI: Groq Vision — meta-llama/llama-4-scout-17b-16e-instruct (ultra-fast inference)
• Fallback LLM: OpenAI GPT-4o-mini
• Weather Data: OpenWeatherMap API
• Knowledge Base: 20+ Kerala crop disease encyclopedia (offline fallback)

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⚙️ Installation & Setup

1. Prerequisites

• Node.js (v18+)
• Python (3.11+)
• API Keys: Groq API Key (free at console.groq.com) & OpenWeatherMap API Key

2. Clone and Install Dependencies

# Install frontend dependencies
npm install

# Install backend dependencies
pip install -r requirements.txt

3. Environment Configuration

Copy the example env file and fill in your keys:

cp .env.example .env

GROQ_API_KEY=your_groq_key_here
OPENAI_API_KEY=your_openai_key_here        # optional fallback
OPENWEATHERMAP_API_KEY=your_key_here
DEFAULT_CITY=Ernakulam
DEFAULT_COUNTRY=IN

Note: .env is gitignored — never commit real API keys. See .env.example for the template.

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⚡ Running the Application

Start the Backend

# Direct command
python -m uvicorn api.main:app --port 8000 --reload

# Or use the provided PowerShell script
./run_backend.ps1

Start the Frontend

npm run dev

The application will be accessible at http://localhost:5173 (Frontend) and http://localhost:8000/docs (API Docs).

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📐 Design Philosophy

• Tactical Aesthetics: Deep Blacks (#020617) and Tactical Cyan highlights.
• High Performance: Minimized latency through asynchronous API handling and Vite's HMR.
• Outdoor Optimized: High-contrast monochromatic UI designed for field visibility.

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🌑 Maintainers

Building at the intersection of Agriculture and Artificial Intelligence.