SmartKrishi - AI-Powered Agricultural Assistant

A comprehensive full-stack platform providing intelligent agricultural guidance through AI-powered chat, real-time assistance, and advanced farming insights.

🌾 Overview

SmartKrishi is a modern agricultural assistant that combines cutting-edge AI technology with practical farming knowledge. The platform provides farmers with instant access to agricultural expertise, crop management advice, weather insights, and farming best practices through an intuitive chat interface.

✨ Key Features

• 🤖 AI-Powered Chat: Advanced conversational AI with agricultural domain expertise
• 📱 Multi-Platform Access: Web app, mobile-responsive design, and SMS fallback
• 📂 File Analysis: Upload and analyze farm photos, soil reports, and documents
• 🔄 Real-time Streaming: Instant AI responses with step-by-step reasoning
• 🔐 Secure Authentication: Firebase-based phone authentication
• 📊 Smart Insights: Crop recommendations, disease identification, and yield optimization
• 🌐 Offline Support: SMS/WhatsApp fallback for areas with limited internet
• 📈 Conversation History: Persistent chat history and knowledge base

🏗️ System Architecture

graph TB
    subgraph "Frontend Applications"
        WEB[Web Application<br/>React + TypeScript]
        MOB[Mobile Web<br/>PWA Ready]
        SMS[SMS Interface<br/>WhatsApp Bot]
    end
    
    subgraph "API Gateway & Load Balancer"
        LB[Nginx/Cloudflare<br/>Load Balancer]
        CORS[CORS Handler]
        RATE[Rate Limiter]
    end
    
    subgraph "Backend Services"
        API[FastAPI Server<br/>Python 3.12]
        AUTH[Auth Service<br/>JWT + Firebase]
        CHAT[Chat Service<br/>Streaming WebSocket]
        FILE[File Service<br/>Upload & Analysis]
        SMS_SVC[SMS Service<br/>Twilio/WhatsApp]
    end
    
    subgraph "AI & External Services"
        GEMINI[Google Gemini<br/>AI Model]
        AGENT[Agent API<br/>Advanced Reasoning]
        FIREBASE[Firebase Auth<br/>Phone Verification]
        STORAGE[Cloud Storage<br/>File Storage]
    end
    
    subgraph "Data Layer"
        POSTGRES[(PostgreSQL<br/>Primary Database)]
        REDIS[(Redis<br/>Cache & Sessions)]
        FILES[(File Storage<br/>Images & Documents)]
    end
    
    subgraph "Infrastructure"
        DOCKER[Docker Containers]
        MONITOR[Monitoring<br/>Logs & Metrics]
        BACKUP[Backup Systems]
    end
    
    WEB --> LB
    MOB --> LB
    SMS --> LB
    
    LB --> CORS
    CORS --> RATE
    RATE --> API
    
    API --> AUTH
    API --> CHAT
    API --> FILE
    API --> SMS_SVC
    
    AUTH --> FIREBASE
    CHAT --> GEMINI
    CHAT --> AGENT
    FILE --> STORAGE
    
    API --> POSTGRES
    API --> REDIS
    FILE --> FILES
    
    API --> DOCKER
    DOCKER --> MONITOR
    MONITOR --> BACKUP

Loading

🛠️ Tech Stack

Frontend

• Framework: React 19.1+ with TypeScript 5.8+
• Build Tool: Vite 7.1+ with hot module replacement
• UI Library: Radix UI + Tailwind CSS 3+
• State Management: React Context + Custom Hooks
• Authentication: Firebase Auth with phone verification
• HTTP Client: Axios with interceptors
• Real-time: Server-Sent Events (SSE)
• PWA: Progressive Web App capabilities

Backend

• Framework: FastAPI 0.115+ with Python 3.12+
• Database: PostgreSQL 15+ with SQLAlchemy 2.0+
• Authentication: JWT + Firebase Admin SDK
• API Documentation: OpenAPI 3.0 with Swagger UI
• File Processing: Pillow + Multi-format support
• Streaming: WebSocket + Server-Sent Events
• Deployment: Gunicorn + Docker

AI & External Services

• AI Model: Google Gemini Pro for agricultural intelligence
• Agent API: Advanced reasoning and tool usage
• Phone Auth: Firebase Authentication
• SMS/WhatsApp: Twilio integration
• File Storage: Cloud storage with CDN
• Monitoring: Application performance monitoring

Infrastructure

• Database: PostgreSQL with connection pooling
• Caching: Redis for session and response caching
• Containerization: Docker with multi-stage builds
• Load Balancing: Nginx reverse proxy
• SSL/TLS: Automatic HTTPS with Let's Encrypt
• Monitoring: Structured logging and health checks

🚀 Quick Start

Prerequisites

• Node.js: 18+ (for frontend)
• Python: 3.12+ (for backend)
• PostgreSQL: 15+ (database)
• Firebase Project: With phone authentication
• Google AI: Gemini API key

1. Clone Repository

git clone https://github.com/Neural-Knight/SmartKrishi.git
cd SmartKrishi

2. Backend Setup

cd backend

# Create virtual environment
python -m venv venv
source venv/bin/activate  # Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Setup environment
cp .env.example .env
# Edit .env with your configuration

# Run database migrations
alembic upgrade head

# Start backend server
uvicorn app.main:app --reload --host 0.0.0.0 --port 8000

3. Frontend Setup

cd frontend

# Install dependencies
pnpm install  # or npm install

# Setup environment
cp .env.example .env
# Edit .env with your configuration

# Start development server
pnpm dev  # or npm run dev

4. Access Application

• Frontend: http://localhost:5173
• Backend API: http://localhost:8000
• API Documentation: http://localhost:8000/docs

🔧 Configuration

Environment Variables

Backend (.env)

DATABASE_URL=postgresql://user:pass@localhost:5432/smartkrishi
SECRET_KEY=your-jwt-secret-key
GEMINI_API_KEY=your-google-gemini-api-key
FIREBASE_CREDENTIALS=/path/to/serviceAccountKey.json

Frontend (.env)

VITE_API_BASE_URL=http://localhost:8000
VITE_FIREBASE_API_KEY=your-firebase-api-key
VITE_FIREBASE_PROJECT_ID=your-project-id

Database Setup

# Create PostgreSQL database
createdb smartkrishi

# Run migrations
cd backend
alembic upgrade head

# Optional: Add sample data
python -c "from app.db.init_db import init_db; init_db()"

📱 Features Deep Dive

AI-Powered Agricultural Assistant

• Crop Management: Personalized advice for different crops and seasons
• Disease Identification: Photo-based plant disease diagnosis
• Weather Integration: Weather-aware farming recommendations
• Soil Analysis: Soil report interpretation and improvement suggestions
• Pest Control: Integrated pest management strategies
• Market Insights: Crop pricing and market trend analysis

Multi-Channel Access

• Web Application: Full-featured browser-based interface
• Mobile Web: Responsive design optimized for smartphones
• SMS Fallback: Text-message based interaction for offline areas
• WhatsApp Bot: Integration with popular messaging platform
• Voice Input: Speech-to-text for hands-free operation

Advanced AI Features

• Reasoning Visualization: Step-by-step AI decision process
• Context Awareness: Remembers previous conversations and farm details
• Multi-modal Input: Text, images, documents, and voice
• Real-time Streaming: Instant responses with typing indicators
• Confidence Scoring: AI confidence levels for recommendations

🤝 Contributing

We welcome contributions! Please see our contributing guidelines:

1. Fork the repository
2. Create feature branch (git checkout -b feature/amazing-feature)
3. Follow code style guidelines
4. Add tests for new features
5. Update documentation
6. Commit changes (git commit -m 'Add amazing feature')
7. Push to branch (git push origin feature/amazing-feature)
8. Open Pull Request