Agricultural AI Frontend

PRAGATI: Precision Retrieval & AI for Generative Agricultural Technology & Insights

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PRAGATI is a pioneering RAG-powered Multi-Agent Orchestrator System tailored for agricultural domain knowledge. Our vision is to empower the agricultural sector with:

• Specialized AI Agents: Deliver precise, timely, and context-aware recommendations for crop selection, irrigation, fertilizer use, pest detection etc.
• Query Complexity Assessment: Optimizes retrieval and generation, ensuring the right expertise is applied to each query.
• Multi-Agent Orchestration: Coordinates specialized agents for comprehensive, expert-backed answers.
• Multi-Lingual & Multi-Modal Support: Accessible via text, image, and voice inputs, making PRAGATI an AI truly "For the Farmers".
• Deep Research Pipelines: Enhance coverage and depth of recommendations.
• Human-in-the-Loop (HITL) Validation: Ensures factual accuracy and reliable decision support for farmers and stakeholders.
• Retrieval-Augmented Generation (RAG) Pipeline: Integrates semantic search with domain-specific knowledge base retrieval, ensuring all AI-generated responses are grounded in verified agricultural data.

PRAGATI is accurate, fast, and reliable—driving progress and growth in agriculture, just as its name means!

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A modern Next.js front-end application for Agricultural AI solutions, including chat, crop recommendations, disease prediction, and more.

Features

The dashboard provides the following AI-powered features and tools:

• AI Specialists Tab

  • Crop Yield Prediction
  • Crop Health Analysis & Disease Prediction
  • Pest Control & Prediction
  • Crop Recommendations (Soil-based)
  • Fertilizer Guide
  • Irrigation Planning
  • Weather Advisory
  • Market Prices (Real-time)
  • Credit Policy & Market Intelligence
  • Risk Management
  • Agriculture News & Updates

• Chat History Tab

  • Access and revisit all your previous chat sessions with AI agents.

• QR Scanner

  • Scan QR codes for quick access to agri-data, resources, or field records.

• Profile & Sign Out

  • Manage your user profile and securely sign out.

All features are accessible via a sidebar for seamless navigation between AI agents, chat history, and tools.

Table of Contents

Prerequisites

• Node.js v18 or higher
• pnpm package manager (optional but recommended)
• A PostgreSQL-compatible database (Neon, Supabase, or local Postgres)
• Git for version control

Getting Started

1. Clone the repository:

   git clone https://github.com/Ecolash/Agricultural-AI-Frontend.git
   cd Agricultural-AI-Frontend

2. Install dependencies:

   pnpm install

3. Create a .env file in the project root based on the example below.

Environment Variables

Create a .env file with the following variables: In the project root:

DATABASE_URL=""           # PostgreSQL connection string
NEXTAUTH_SECRET=""        # Secret key for NextAuth.js
NEXTAUTH_URL=""           # Deployed frontend URL
NEXT_PUBLIC_API_URL=""    # Public API endpoint for the backend

Prisma Setup

Prisma ORM is used for database schema migrations and client generation.

1. Generate Prisma client (runs automatically after install):

   pnpm prisma generate

2. Apply migrations to your database:

   pnpm prisma migrate dev --name init

3. (Optional) To reset your database and reapply all migrations:

   pnpm prisma migrate reset

Available Scripts

In the project directory, you can run:

• pnpm dev or pnpm run dev:frontend
  Runs the development server at http://localhost:3000.

• pnpm run build
  Builds the application for production and generates the Prisma client.

• pnpm start
  Runs the production build with next start.

• pnpm run lint
  Lints code with ESLint.

• pnpm run type-check
  Runs TypeScript type checking.

• pnpm run dev:setup
  Helpful scripts for local development (see scripts/dev-setup.sh help).

Project Structure

├── app/                        # Next.js app directory (routing, pages, API routes)
│   ├── api/                    # API route handlers (auth, chat-history, etc.)
│   ├── dashboard/              # Dashboard UI and subpages
│   ├── qr-scanner/             # QR scanner feature pages
│   ├── signin/, signup/        # Auth pages
│   └── ...                     # Other feature pages and layouts
│
├── components/                 # Reusable React components
│   ├── agent-interfaces/       # Specialized agent UI interfaces
│   ├── lib/                    # Component-specific utilities
│   ├── types/                  # Component-specific types
│   └── ui/                     # UI primitives (buttons, dialogs, etc.)
│
├── data/                       # Static data, language lists, agent configs
├── docs/                       # Project and API documentation
├── hooks/                      # Custom React hooks
├── lib/                        # API wrappers, utilities, and services
│   └── actions/                # Server actions and helpers
├── prisma/                     # Prisma schema and migrations
│   └── migrations/             # Database migration files
├── public/                     # Static assets (images, icons, etc.)
├── scripts/                    # Utility scripts for setup and development
├── styles/                     # Global and component styles
├── types/                      # Global TypeScript type definitions
├── assets/                     # Project assets (logo, images)
├── .env                        # Environment variables
├── package.json                # Project metadata and scripts
├── tsconfig.json               # TypeScript configuration
├── README.md                   # Project documentation
└── ...                         # Other config and dotfiles

Contributing

Contributions are welcome! Please open an issue or submit a pull request.

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

License

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