Digital Krishi Officer - AI-Based Farmer Query Support System

An AI-powered agricultural advisory system designed specifically for Kerala farmers. This system provides expert farming advice in Malayalam, helping farmers with crop diseases, weather decisions, input management, and more.

🌾 Project Overview

The Digital Krishi Officer serves as a "Digital Krishi Officer" that provides instant, accurate, and context-aware agricultural advice to farmers in their native language, primarily Malayalam. It bridges the critical gap between farmers and agricultural expertise through AI technology.

Key Features

• Malayalam Language Support: Native language processing for Kerala farmers
• Multimodal Input: Text, voice, and image support for comprehensive queries
• AI-Powered Responses: Using Google's Gemini 2.5 Flash Lite model via OpenRouter
• Crop Disease Detection: Image analysis for disease identification and treatment
• Expert Escalation: Automatic escalation to human experts for complex issues
• 24/7 Availability: Round-the-clock agricultural support

🛠️ Tech Stack

Frontend

• Next.js 14+ - React framework with App Router
• TypeScript - Type safety and better development experience
• Tailwind CSS - Utility-first CSS framework

Backend & Database

• Appwrite - Backend-as-a-Service for authentication and database
• Appwrite Database - NoSQL document database
• Appwrite Auth - Email/password authentication

AI Integration

• OpenRouter - AI model routing and management
• Vercel AI SDK - Streaming AI responses
• Google Gemini 2.5 Flash Lite - Primary AI model for agricultural advice

State Management

• Zustand - Lightweight state management solution

🚀 Getting Started

Prerequisites

• Node.js 18+
• pnpm (recommended) or npm
• Appwrite account and project
• OpenRouter API key

Installation

1. Clone the repository

   git clone <repository-url>
   cd iic2025

2. Install dependencies

   pnpm install

3. Set up environment variables

   cp .env.example .env.local

   Update .env.local with your actual values:

   # Appwrite Configuration
   NEXT_PUBLIC_APPWRITE_ENDPOINT=https://cloud.appwrite.io/v1
   NEXT_PUBLIC_APPWRITE_PROJECT_ID=your_project_id
   APPWRITE_API_KEY=your_api_key
   NEXT_PUBLIC_APPWRITE_DATABASE_ID=iic-db
   NEXT_PUBLIC_APPWRITE_USER_COLLECTION_ID=user
   NEXT_PUBLIC_APPWRITE_THREAD_COLLECTION_ID=thread
   NEXT_PUBLIC_APPWRITE_MESSAGE_COLLECTION_ID=message
   
   # OpenRouter Configuration
   OPENROUTER_API_KEY=your_openrouter_api_key
   NEXT_PUBLIC_OPENROUTER_BASE_URL=https://openrouter.ai/api/v1
   
   # Weather API Configuration (Optional)
   NEXT_PUBLIC_OPENWEATHER_API_KEY=your_openweathermap_api_key
   
   # Application Configuration
   NEXT_PUBLIC_APP_URL=http://localhost:3000
   NEXT_PUBLIC_APP_NAME=Digital Krishi Officer

4. Set up Appwrite Database

   Create the following collections in your Appwrite database:

   User Collection (user)

   • username (string, required, size: 100)
   • location (string, required, size: 200)
   • farmsize (string, size: 60)
   • crop (string array, size: 50)
   • experience (string, size: 100)
   • language (string, size: 100)

   Thread Collection (thread)

   • userId (string, required, size: 100)
   • title (string, required, size: 256)
   • description (string, size: 500)
   • category (string, size: 100)
   • priority (string, size: 50)
   • status (string, size: 50)
   • tags (string array, size: 50)
   • messageCount (number)
   • lastMessageAt (datetime)

   Message Collection (message)

   • threadId (string, required, size: 100)
   • userId (string, required, size: 100)
   • content (string, required, size: 20000)
   • role (string, required, size: 50)
   • contentType (string, required, size: 100)
   • attachment (string, size: 500)

5. Run the development server

   pnpm dev

6. Open your browser Navigate to http://localhost:3000

📁 Project Structure

iic2025/
├── src/
│   ├── app/                          # Next.js App Router
│   │   ├── (auth)/                   # Authentication pages
│   │   │   └── login/
│   │   ├── api/                      # API Routes
│   │   │   ├── auth/                 # Authentication endpoints
│   │   │   └── chat/                 # Chat streaming endpoints
│   │   ├── globals.css
│   │   ├── layout.tsx
│   │   └── page.tsx
│   ├── components/                   # React components (to be implemented)
│   ├── services/                     # Zustand stores
│   │   ├── authStore.ts
│   │   └── chatStore.ts
│   ├── utils/                        # Utility functions & configurations
│   │   ├── aiModels/                 # AI model configurations
│   │   ├── appwrite/                 # Appwrite configurations
│   │   ├── openrouter/               # OpenRouter configurations
│   │   └── types/                    # TypeScript type definitions
│   └── hooks/                        # Custom React hooks (to be implemented)
├── public/                           # Static assets
├── .env.example                      # Environment variables template
├── .env.local                        # Local environment variables
└── README.md

🔧 Configuration

AI Model Configuration

The system is configured to use Google's Gemini 2.5 Flash Lite model through OpenRouter:

const MODELS = {
  "google/gemini-2.5-flash-lite": {
    id: "google/gemini-2.5-flash-lite",
    name: "Gemini 2.5 Flash Lite",
    provider: "Google",
    description:
      "Lightweight and fast Gemini model optimized for quick responses and cost-effectiveness",
    contextLength: 1000000,
    inputCost: 0.05,
    outputCost: 0.15,
    capabilities: ["text", "vision", "reasoning", "code", "multimodal"],
    recommended: true,
  },
};

Database Schema

The application uses three main collections:

1. Users: Store farmer profiles and preferences
2. Threads: Organize conversations by topic
3. Messages: Store individual messages in conversations

🚀 API Endpoints

Authentication

• POST /api/auth/login - User login
• POST /api/auth/register - User registration
• POST /api/auth/logout - User logout

Chat

• POST /api/chat/stream - Stream AI responses

🌟 Key Features Implementation

Malayalam Language Support

The system is specifically designed for Malayalam-speaking farmers with:

• Native language processing
• Cultural context awareness
• Local farming practice knowledge

AI-Powered Advisory

• Specialized agricultural prompts
• Context-aware responses
• Crop-specific advice
• Weather-based recommendations

Multimodal Input (Planned)

• Text queries in Malayalam/English
• Voice message support
• Image upload for crop disease detection
• GPS location for region-specific advice

🔄 Development Workflow

Available Scripts

# Development
pnpm dev          # Start development server
pnpm build        # Build for production
pnpm start        # Start production server

# Code Quality
pnpm lint         # Run ESLint
pnpm type-check   # Run TypeScript checks

Development Guidelines

1. Code Style: Follow TypeScript and ESLint configurations
2. Components: Use functional components with hooks
3. State Management: Use Zustand for global state
4. Styling: Use Tailwind CSS utility classes
5. API: Follow RESTful conventions for API routes

🚀 Deployment

Vercel Deployment (Recommended)

1. Connect your GitHub repository to Vercel
2. Configure environment variables in Vercel dashboard
3. Deploy automatically on push to main branch

Environment Variables for Production

Ensure all environment variables are properly set in your deployment platform:

• Appwrite endpoint and credentials
• OpenRouter API key
• Application URLs and configuration

🤝 Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

📝 License

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

🙏 Acknowledgments

• Kerala farmers and agricultural experts for domain knowledge
• Appwrite team for the excellent BaaS platform
• OpenRouter for AI model access
• Vercel team for the AI SDK and deployment platform

📞 Support

For support and questions:

• Create an issue in the GitHub repository
• Contact the development team
• Check the documentation in the docs/ folder (coming soon)

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Digital Krishi Officer - Empowering Kerala farmers with AI-driven agricultural expertise. 🌾