Transform how you access district information with AI-powered intelligence

Kattal AI is a cutting-edge web application that revolutionizes the way users interact with district information. Using advanced AI technologies including Retrieval Augmented Generation (RAG), vector search, and natural language processing, users can chat with their PDF documents to instantly understand development data, government services, and statistical information.

• Natural Language Processing: Ask questions in plain English or Malayalam
• Context-Aware Responses: AI understands context and provides relevant answers
• Multi-language Support: Built-in support for English and Malayalam
• Real-time Chat: Instant responses with typing indicators

• PDF Analysis: Intelligent parsing and chunking of PDF documents
• Smart Chunking: Context-aware text splitting for optimal retrieval
• Vector Embeddings: High-dimensional representations for semantic search
• Quality Validation: Ensures data integrity and relevance

• Vector Search: Pinecone-powered similarity search
• Semantic Understanding: Goes beyond keyword matching
• Adaptive Retrieval: Learns from user interactions
• Performance Optimization: Fast and efficient data retrieval

• Responsive Design: Works seamlessly on all devices
• Dark/Light Mode: User preference-based theming
• Accessibility: WCAG compliant interface
• Progressive Web App: Installable on mobile devices

• AI-Specific Meta Tags: Optimized for Gemini, Claude, ChatGPT, and Perplexity
• Enhanced Structured Data: AI-friendly schema markup
• AI Search Directives: Specific instructions for AI crawlers
• Semantic Content: Better AI understanding and categorization

• Next.js 14+: App Router with server-side rendering
• TypeScript: Type-safe development
• Tailwind CSS: Utility-first CSS framework
• shadcn/ui: High-quality React components
• Framer Motion: Smooth animations and transitions

• LangChain: RAG pipeline and document processing
• Pinecone: Vector database for embeddings
• OpenAI: GPT models for chat completions
• Node.js: Server-side runtime

• Vercel Analytics: Performance monitoring
• Speed Insights: Core Web Vitals tracking
• SEO Optimized: Meta tags, Open Graph, structured data
• PWA Ready: Service worker and manifest support
• GenAI Optimized: AI search engine optimization

• Comprehensive Meta Tags: Title, description, keywords
• Open Graph Protocol: Rich social media sharing
• Twitter Cards: Optimized Twitter previews
• Structured Data: Schema.org markup ready
• Canonical URLs: Prevents duplicate content issues

• AI-Specific Meta Tags: Optimized for AI search engines
• AI Search Directives: Gemini, Claude, ChatGPT, Perplexity support
• Enhanced Structured Data: AI-friendly properties and capabilities
• AI Content Classification: Clear categorization for AI understanding
• AI Performance Metrics: AI-specific optimization data

• robots.txt: Clear crawling instructions for all engines
• sitemap.xml: Automated page discovery with AI metadata
• Meta Robots: Index and follow directives
• Google Bot Optimization: Enhanced crawling settings
• AI Crawler Support: Gemini, Claude, ChatGPT, Perplexity optimization
• Social Media Bots: Facebook, Twitter, LinkedIn support

• Core Web Vitals: LCP, FID, CLS optimization
• Mobile-First: Responsive design approach
• Accessibility: WCAG 2.1 AA compliance
• Progressive Enhancement: Graceful degradation
• AI Performance: AI search engine optimization metrics

• Node.js 18+
• npm or yarn package manager
• OpenAI API key
• Pinecone API key and environment

1. Clone the repository

   git clone https://github.com/yourusername/kattal-ai.git
   cd kattal-ai

2. Install dependencies

   npm install

3. Set up environment variables

   cp .env.example .env.local

   Update .env.local with your API keys:

   OPENAI_API_KEY=your_openai_api_key
   PINECONE_API_KEY=your_pinecone_api_key
   PINECONE_ENVIRONMENT=your_pinecone_environment
   PINECONE_INDEX_NAME=your_pinecone_index

4. Run the development server

   npm run dev

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

• npm run dev - Start development server with Turbopack
• npm run build - Build for production
• npm run start - Start production server
• npm run lint - Run ESLint

• npm run prepare:data - Prepare and upload documents to Pinecone
• npm run delete:index - Delete Pinecone index
• npm run reset:data - Reset and re-prepare data
• npm run clear:data - Clear Pinecone namespace
• npm run refill:data - Clear and refill data

• npm run analyze:database - Analyze database performance
• npm run optimize:database - Optimize database configuration
• npm run test:reasoning - Test AI reasoning capabilities

• npm run generate:sitemap - Generate sitemap.xml
• npm run postbuild - Automatically generate sitemap after build

1. Upload: Users upload PDF documents through the web interface
2. Parsing: LangChain processes and extracts text content
3. Chunking: Smart text splitting maintains context and meaning
4. Embedding: OpenAI generates vector embeddings for each chunk
5. Storage: Pinecone stores vectors with metadata for retrieval

1. User Input: Natural language questions in English or Malayalam
2. Query Processing: OpenAI generates query embeddings
3. Vector Search: Pinecone finds most relevant document chunks
4. Context Assembly: Relevant chunks are assembled with context
5. AI Response: OpenAI generates human-like responses with sources

• Adaptive Retrieval: Learns from user interactions
• Smart Caching: Reduces API calls and improves response times
• Quality Validation: Ensures response accuracy and relevance
• Performance Monitoring: Real-time analytics and optimization

• District Information: Access development data and statistics
• Policy Documents: Understand government policies and procedures
• Service Discovery: Find available government services
• Data Analysis: Interpret complex statistical information

• Academic Research: Process and analyze research documents
• Student Learning: Interactive learning with document analysis
• Knowledge Discovery: Uncover insights from large document collections
• Data Interpretation: Understand complex datasets and reports

• Document Analysis: Process business documents and reports
• Compliance Review: Analyze regulatory and compliance documents
• Market Research: Extract insights from market reports
• Competitive Intelligence: Analyze competitor documents and data

• Information Access: Easy access to complex government information
• Document Understanding: Simplified understanding of technical documents
• Service Navigation: Find and understand available services
• Data Literacy: Improve understanding of statistical information

• Secure Storage: All data encrypted in transit and at rest
• API Security: Secure API key management and validation
• User Privacy: No personal data collection or storage
• Access Control: Secure document access and management

• GDPR Ready: European data protection compliance
• Data Privacy: Minimal data collection and processing
• Security Standards: Industry-standard security practices
• Regular Audits: Ongoing security and privacy assessments

1. Connect Repository: Link your GitHub repository to Vercel
2. Set Environment Variables: Configure API keys in Vercel dashboard
3. Deploy: Automatic deployment on every push to main branch
4. Custom Domain: Configure your domain with SSL

• Netlify: Similar deployment process with environment variables
• AWS Amplify: Full-stack deployment with AWS services
• Docker: Containerized deployment for any platform
• Self-hosted: Deploy on your own infrastructure

# Required
OPENAI_API_KEY=your_openai_api_key
PINECONE_API_KEY=your_pinecone_api_key
PINECONE_ENVIRONMENT=your_pinecone_environment
PINECONE_INDEX_NAME=your_pinecone_index

# Optional: Custom Domain
NEXT_PUBLIC_SITE_URL=https://kattal-ai.vercel.app

• Code Splitting: Automatic route-based code splitting
• Image Optimization: Next.js Image component with WebP support
• Font Optimization: Google Fonts with display swap
• Bundle Analysis: Webpack bundle analyzer for optimization

• Vector Indexing: Optimized Pinecone index configuration
• Caching Strategy: Intelligent caching for improved performance
• API Optimization: Efficient API design and response handling
• Database Optimization: Optimized vector search and retrieval

• LCP: Optimized for Largest Contentful Paint
• FID: Minimized First Input Delay
• CLS: Stable Cumulative Layout Shift
• Performance Monitoring: Real-time Core Web Vitals tracking

• Vercel Analytics: Real-time performance metrics
• Speed Insights: Core Web Vitals monitoring
• Error Tracking: Comprehensive error monitoring and reporting
• User Experience: Real user performance data

• Search Console: Google Search Console integration
• Bing Webmaster: Bing Webmaster Tools monitoring
• AI Search Metrics: GenAI search engine performance tracking
• Content Performance: Content engagement and ranking metrics

• User Behavior: Understanding user interaction patterns
• Feature Usage: Tracking feature adoption and usage
• Performance Metrics: User experience performance data
• Conversion Tracking: Goal completion and success metrics

• Code Quality: Follow TypeScript and ESLint standards
• Testing: Comprehensive testing for all new features
• Documentation: Update documentation for all changes
• Performance: Ensure new features don't impact performance

1. Fork Repository: Create your own fork of the project
2. Create Branch: Make changes in a feature branch
3. Submit PR: Create pull request with detailed description
4. Code Review: Address feedback and make necessary changes
5. Merge: Merge approved changes to main branch

• Local Development: Full local development environment
• Testing Environment: Comprehensive testing setup
• Code Quality: Automated code quality checks
• Performance Testing: Performance regression testing

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

• OpenAI: For providing the GPT models and API
• Pinecone: For vector database infrastructure
• LangChain: For RAG pipeline and document processing
• Next.js Team: For the excellent React framework
• Vercel: For hosting and deployment platform

• Documentation: Comprehensive documentation and guides
• Issues: GitHub Issues for bug reports and feature requests
• Discussions: GitHub Discussions for community support
• Email: [email protected] for direct support

• Partnerships: [email protected]
• Enterprise: [email protected]
• General: [email protected]