Krishi-Setu 🌾 - AI-Powered Agricultural Intelligence Platform

📋 Table of Contents

Overview
Features
Screens & Navigation
Architecture
Tech Stack
Project Structure
Installation & Setup
Environment Configuration
API Documentation
Supabase Backend
Development Guide
Testing
Deployment
Contributing
License

🌟 Overview

Krishi-Setu (meaning "Farmer's Bridge" in Hindi) is a comprehensive agricultural intelligence platform built with Flutter that empowers farmers with AI-driven insights. The application provides real-time disease detection, soil health analysis, market intelligence, weather forecasting, and yield prediction to enhance agricultural productivity and decision-making.

🎯 Vision

To bridge the gap between traditional farming practices and modern technology, making agricultural intelligence accessible to every farmer.

🚀 Key Value Propositions

Real-time Disease Detection: Instant plant disease identification using computer vision
Soil Health Analytics: Comprehensive soil diagnostics with actionable recommendations
Market Intelligence: Real-time commodity prices and trend analysis
Hyperlocal Weather: Accurate weather forecasts for specific farm locations with reverse geocoding
Yield Prediction: ML-based yield forecasting for better planning
Crop Management: Complete crop cycle tracking and timeline management
AI Agricultural Consultant: Context-aware AI assistant with hyper-local weather intelligence

✨ Features

🏠 Dashboard & Navigation

Interactive Dashboard: Personalized overview with weather, soil health, market trends, and crop status
Bottom Navigation: Four main sections - Home, Crops, Health, Market
App Shell: Consistent navigation structure with stateful shell routing
Theme Support: Light/dark mode with dynamic theme switching

🌱 Crop Management

Crop Selection: Multi-crop support with detailed information
Crop Timeline: Visual crop cycle tracking with growth stages
Yield Prediction: Machine learning-based yield forecasting
Crop Rotation Suggestions: AI-powered crop rotation recommendations

🩺 Health & Diagnostics

Soil Health Analysis: Comprehensive soil diagnostics with NPK values, pH, organic matter
Disease Detection: Real-time plant disease identification using camera
Krishi Lens: Custom computer vision module for plant scanning
Health Reports: Detailed diagnostic reports with recommendations

📊 Market Intelligence

Real-time Prices: Live commodity prices from agricultural markets
Price Trends: Historical price analysis and trend visualization
Market Alerts: Price change notifications and alerts
Demand Forecasting: Market demand predictions

🌤️ Weather Services

Hyperlocal Forecast: Weather predictions for specific farm locations using Open-Meteo API
Reverse Geocoding: Converts GPS coordinates to human-readable location names (village/town/city)
Rainfall Prediction: Precipitation forecasts for irrigation planning
Weather Alerts: Severe weather warnings and notifications
Historical Data: Past weather patterns analysis

🤖 AI & Recommendations

Setu AI Assistant: AI-powered agricultural consultant with hyper-local context
Personalized Recommendations: Context-aware farming recommendations using location-specific data
Deep Scan Analysis: Advanced analysis using multiple data sources
Learning System: AI that learns from user interactions and outcomes
Real-time Weather Intelligence: AI uses location names for precise weather queries

👤 User Management

Authentication: Email/Google sign-in with Supabase Auth
User Profiles: Complete farmer profiles with farm details
Farm Management: Multiple farm support with geolocation
Data Synchronization: Offline-first with PowerSync real-time sync

📱 Screens & Navigation

Authentication Flow

Splash Screen (/splash) - App initialization and branding
Onboarding Screen (/onboarding) - Feature introduction and walkthrough
Auth Screen (/auth) - Login/Signup with email or Google
Profiling Screen (/profiling) - Initial user and farm setup

Main App Navigation (Shell)

The app uses a stateful shell with 4 main sections:

🏠 Home/Dashboard Branch

Dashboard Screen (/dashboard) - Main overview with widgets
Weather Screen (/weather) - Detailed weather forecasts with hyper-local location display
Crop Timeline Screen (/crop-timeline) - Visual crop cycle tracking
Yield Prediction Screen (/yield-prediction) - Yield forecasting
Crop Selection Screen (/crop-selection) - Crop management

🌱 Crops Branch

Crop Selection Screen (/crops) - Crop management and selection

🩺 Health Branch

Soil Health Screen (/health) - Soil diagnostics and analysis
Disease Landing Screen (/scan-crop) - Disease detection interface
Lens Screen (/camera-viewfinder) - Camera-based plant scanning

📊 Market Branch

Market Screen (/market) - Market intelligence and prices

Additional Screens

Profile Screen (/profile) - User profile and settings
Farm Update Screen (/farm-update) - Farm details management
AI Recommendations Screen (/recommendations) - AI-powered farming advice
Creators Screen (/creators) - Team and contributors information

🏗️ Architecture

Clean Architecture Pattern

The app follows a modified Clean Architecture with clear separation of concerns:

Presentation Layer (UI)
├── Screens
├── Widgets
└── Providers (Riverpod)

Domain Layer (Business Logic)
├── Models
├── Use Cases
└── Interfaces

Data Layer (Data Sources)
├── Repositories
├── Local (SQLite)
└── Remote (Supabase, APIs)

State Management

Riverpod 3.3.1: Modern, reactive state management
Provider Scope: Global provider scope at root level
State Notifiers: For complex state management
Async Value: Handling loading, error, and data states

Navigation

Go Router: Declarative routing with nested navigation
Stateful Shell: Bottom navigation with preserved state
Route Guards: Authentication and profile completion guards
Deep Linking: Support for deep links and URL navigation

🛠️ Tech Stack

Frontend

Flutter 3.9.2: Cross-platform UI framework
Dart 3.9.2: Programming language
Riverpod 3.3.1: State management
Go Router 17.1.0: Navigation and routing

Backend & Database

Supabase: Backend-as-a-Service (PostgreSQL, Auth, Storage, Edge Functions)
PowerSync 1.18.0: Real-time data synchronization
SQLite Async 0.13.1: Local database operations
PostgreSQL: Primary database with Row Level Security

UI & Design

Material Design 3: Modern design system
Google Fonts: Custom typography
Lottie 3.3.2: Animations and illustrations
Flutter Map 8.2.2: Interactive maps
FL Chart 0.70.2: Data visualization

APIs & Services

Dio 5.9.2: HTTP client for API calls
Camera 0.12.0+1: Camera access for disease detection
Image Picker 1.2.1: Image selection and capture
Google Sign-In 6.2.4: Authentication
URL Launcher 6.3.0: External link handling
Open-Meteo API: Weather forecasting service
OpenStreetMap Nominatim API: Reverse geocoding service
Tavily API: Real-time agricultural search and intelligence
OpenRouter API: LLM-powered AI recommendations

Development Tools

Build Runner: Code generation
Envied: Environment variable management
Flutter Launcher Icons: App icon generation
Flutter Lints 5.0.0: Code quality and linting

📁 Project Structure

krishi_setu/
├── lib/
│   ├── core/                    # Core application infrastructure
│   │   ├── router/             # Navigation and routing (app_router.dart)
│   │   ├── theme/              # App themes and design tokens
│   │   ├── utils/              # Utilities and helpers
│   │   └── widgets/            # Reusable widgets (app_shell.dart)
│   │
│   ├── data/                   # Data layer
│   │   ├── models/             # Data models (DTOs)
│   │   └── repositories/       # Repository implementations
│   │
│   ├── domain/                 # Business logic layer
│   │   └── models/             # Domain models
│   │
│   ├── features/               # Feature modules
│   │   └── krishi_lens/        # Computer vision feature
│   │       ├── models/         # Vision models
│   │       ├── presentation/   # UI screens
│   │       ├── providers/      # State management
│   │       ├── services/       # Business logic
│   │       └── utils/          # Utilities
│   │
│   ├── presentation/           # UI layer
│   │   ├── ai_recommendations/ # AI recommendations
│   │   ├── auth/              # Authentication screens
│   │   ├── crops/             # Crop management
│   │   ├── dashboard/         # Dashboard and home
│   │   ├── health/            # Health and diagnostics
│   │   ├── market/            # Market intelligence
│   │   ├── onboarding/        # Onboarding flow
│   │   ├── profile/           # User profile
│   │   ├── profiling/         # Initial setup
│   │   ├── splash/            # Splash screen
│   │   ├── weather/           # Weather forecasts
│   │   └── yield/             # Yield prediction
│   │
│   ├── providers/             # Riverpod providers
│   │   ├── location_provider.dart      # Reverse geocoding and location display
│   │   ├── market_intelligence_provider.dart
│   │   ├── onboarding_provider.dart
│   │   ├── profile_completion_provider.dart
│   │   ├── recommendation_provider.dart
│   │   ├── setu_ai_provider.dart
│   │   ├── soil_diagnostic_provider.dart
│   │   ├── theme_provider.dart
│   │   ├── user_data_provider.dart
│   │   └── weather_provider.dart
│   │
│   └── main.dart              # Application entry point
│
├── assets/                    # Static assets
│   ├── images/               # Images and icons
│   │   ├── onboarding/       # Onboarding illustrations
│   │   └── app_icon.jpg     # Application icon
│   └── lotties/             # Lottie animations
│       ├── Scan.json        # Scanning animation
│       └── plantscan.json   # Plant scan animation
│
├── supabase/                 # Backend configuration
│   ├── functions/           # Edge Functions
│   │   ├── ai-consultant/   # AI consultation service with hyper-local context
│   │   ├── analyze-soil-health/ # Soil analysis
│   │   ├── calculate-yield/ # Yield calculation
│   │   ├── generate-crop-timeline/ # Crop timeline
│   │   ├── get-weather/     # Weather data from Open-Meteo API
│   │   ├── krishi-lens-proxy/ # Vision API proxy
│   │   ├── krishi-recommendations/ # Recommendations
│   │   ├── reverse-geocode/ # Reverse geocoding service (new)
│   │   └── sync-global-market-data/ # Market data synchronization
│   ├── migrations/          # Database migrations
│   └── config.toml          # Supabase configuration
│
├── android/                  # Android-specific files
├── ios/                     # iOS-specific files
├── web/                     # Web-specific files
├── windows/                 # Windows-specific files
├── linux/                   # Linux-specific files
├── macos/                   # macOS-specific files
│
├── pubspec.yaml             # Dependencies and metadata
├── pubspec.lock             # Locked dependencies
├── analysis_options.yaml    # Static analysis rules
└── README.md                # Project documentation

🚀 Installation & Setup

Prerequisites

Flutter SDK 3.9.2 or later
Dart SDK 3.9.2 or later
Android Studio / VS Code with Flutter extension
Git
Supabase CLI (for backend deployment)

Clone the Repository

git clone https://github.com/TapanTalukdar004/Krishi-Setu.git
cd Krishi-Setu/krishi_setu

Install Dependencies

flutter pub get

Run the Application

# For Android
flutter run

# For iOS
flutter run -d ios

# For Web
flutter run -d chrome

Build for Release

# Android APK
flutter build apk --release

# Android App Bundle
flutter build appbundle --release

# iOS
flutter build ios --release

# Web
flutter build web --release

🔧 Environment Configuration

Required Environment Variables

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

# Supabase Configuration
SUPABASE_URL=https://your-project.supabase.co
SUPABASE_ANON_KEY=your-anon-key

# API Keys (Optional for development)
OPENROUTER_API_KEY=your-openrouter-api-key
TAVILY_API_KEY=your-tavily-api-key

Environment Setup

Copy the example environment file:
```
cp .env.example .env
```
Update the values with your actual API keys

Run code generation:

flutter pub run build_runner build --delete-conflicting-outputs

📡 API Documentation

Supabase Edge Functions

1. AI Consultant with Hyper-local Context

Endpoint: /ai-consultant
Method: POST
Description: AI-powered agricultural consultant that uses location-specific context for weather and farming advice
Features: Uses location_name from farm data for precise weather queries, combines with district for hyper-local context

Request Body:

{
  "message": "What's the weather like today?",
  "farm_id": "farm-uuid"
}

2. Reverse Geocoding Service

Endpoint: /reverse-geocode
Method: POST
Description: Converts latitude/longitude coordinates to human-readable location names using OpenStreetMap Nominatim API
Request Body:
```
{
  "lat": 26.1445,
  "lon": 91.7362
}
```

Response:

{
  "location_name": "Guwahati",
  "coordinates": { "lat": 26.1445, "lon": 91.7362 }
}

3. Weather Data with Hyper-local Display

Endpoint: /get-weather
Method: POST
Description: Fetches hyperlocal weather data from Open-Meteo API
Parameters: lat, lon, days (optional)
Response: Includes weather forecasts, temperature, precipitation, and farming recommendations

4. Soil Health Analysis

Endpoint: /analyze-soil-health
Method: POST
Description: Analyzes soil samples and provides health recommendations

Request Body:

{
  "crop": "rice",
  "district": "Kamrup",
  "soil_data": {
    "ph": 6.5,
    "nitrogen": 25,
    "phosphorus": 15,
    "potassium": 150,
    "organic_matter": 2.5
  }
}

5. Yield Calculation

Endpoint: /calculate-yield
Method: POST
Description: Predicts crop yield based on various factors

6. Crop Timeline Generation

Endpoint: /generate-crop-timeline
Method: POST
Description: Generates crop growth timeline based on crop type and region

7. Krishi Lens Proxy

Endpoint: /krishi-lens-proxy
Method: POST
Description: Proxy for computer vision plant disease detection

8. Market Data Sync

Endpoint: /sync-global-market-data
Method: POST
Description: Synchronizes global market data for commodities

External APIs Used

Open-Meteo API: Weather data and forecasts (replaces OpenWeather)
OpenStreetMap Nominatim API: Reverse geocoding service
Tavily API: Agricultural research and real-time search
OpenRouter API: LLM-powered AI recommendations
Government APIs: Market prices and agricultural data

🗄️ Supabase Backend

Database Schema

The application uses PostgreSQL with the following main tables:

Users & Authentication

profiles: Extended user profiles with farm details
auth.users: Supabase Auth managed users

Farm Management

farms: Farm details with geolocation (latitude, longitude, district, location_name)
farm_crops: Crops grown on each farm
crop_cycles: Crop growth cycle tracking

Soil Health

soil_health_logs: Historical soil test results
soil_diagnostic_reports: Detailed diagnostic reports

Market Data

market_prices: Commodity price data
price_alerts: User price alerts

Weather Data

weather_forecasts: Cached weather forecasts
weather_alerts: Severe weather alerts

Row Level Security (RLS)

All tables have RLS policies enabled for data security:

Users can only access their own data
Public read access for market data
Admin-only access for system tables

Storage

soil-reports: Soil health report PDFs
crop-images: Plant disease images
farm-documents: Farm-related documents

💻 Development Guide

Code Style & Conventions

Follow Dart style guide (effective-dart)
Use meaningful variable and function names
Add comments for complex logic
Write unit tests for business logic

Adding a New Feature

Create feature module in lib/features/
Add models in lib/data/models/ and lib/domain/models/
Create repository in lib/data/repositories/
Add provider in lib/providers/
Create screens in lib/presentation/[feature]/
Update routing in lib/core/router/app_router.dart

State Management Best Practices

Use ConsumerWidget for simple state consumption
Use ConsumerStatefulWidget for complex state
Keep providers focused and single-responsibility
Use family providers for parameterized state

Navigation Guidelines

Use named routes defined in app_router.dart
Pass data via route parameters or provider state
Use GoRouter for navigation operations
Implement proper route guards for protected routes

🧪 Testing

Unit Tests

# Run all unit tests
flutter test

# Run tests for specific file
flutter test test/unit/soil_health_test.dart

Widget Tests

# Run widget tests
flutter test test/widget_test.dart

Integration Tests

# Run integration tests
flutter test integration_test/app_test.dart

Test Coverage

# Generate test coverage report
flutter test --coverage
genhtml coverage/lcov.info -o coverage/html

🚢 Deployment

Android Deployment

Update android/app/build.gradle.kts with proper signing config
Generate signed APK/AAB:
```
flutter build appbundle --release
```
Upload to Google Play Console

iOS Deployment

Update iOS bundle identifier in ios/Runner/Info.plist
Configure code signing in Xcode
Build and archive:
```
flutter build ios --release
```
Upload to App Store Connect

Web Deployment

Build for production:
```
flutter build web --release
```
Deploy build/web to hosting service (Netlify, Vercel, Firebase)

Supabase Deployment

Apply database migrations:
```
supabase db push
```

Deploy edge functions:

supabase functions deploy [function-name]

🤝 Contributing

We welcome contributions! Please follow these steps:

Fork the repository
Create a feature branch
```
git checkout -b feature/amazing-feature
```

Commit your changes

git commit -m 'Add some amazing feature'

Push to the branch
```
git push origin feature/amazing-feature
```
Open a Pull Request

Contribution Guidelines

Follow the existing code style and architecture
Write tests for new features
Update documentation accordingly
Ensure no breaking changes without migration plan

📄 License

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

🙏 Acknowledgments

Flutter Team for the amazing cross-platform framework
Supabase for the powerful backend platform
Riverpod for excellent state management
OpenStreetMap for free geocoding services
Open-Meteo for free weather API
Open Source Community for various packages and tools

📞 Support

For support, feature requests, or bug reports:

Open an issue on GitHub Issues
Email: [Your Contact Email]
Join our community: [Community Link]

Krishi-Setu - Bridging Farmers with Technology for Sustainable Agriculture 🌾🚀

"Empowering every farmer with AI-driven agricultural intelligence and hyper-local weather insights"

🔄 Recent Updates (April 2026)

Enhanced Location Intelligence

Reverse Geocoding: Added new Edge Function to convert GPS coordinates to human-readable location names
Hyper-local Weather Display: Weather screen now shows area name + district (e.g., "Guwahati, Kamrup, IN")
AI Consultant Improvements: AI now uses specific location names for weather queries, not just district-level data

Technical Improvements

CORS Configuration: Fixed CORS issues in Edge Functions for proper browser compatibility
Location Providers: Created new Riverpod providers for location name fetching and display
Weather API Integration: Enhanced Open-Meteo integration with better error handling

User Experience

More Precise Weather Data: Farmers get weather information specific to their exact location
Better AI Responses: AI assistant provides more relevant advice based on hyper-local context
Improved UI: Weather page displays both area name and district for better location context

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