AI Integration Overview

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Key Features

• Unified AI SDK: Built on top of Vercel’s AI SDK for consistent AI interactions
• OpenRouter Integration: Access multiple LLMs through a single API
• Server Actions: Type-safe AI operations with Next.js server actions
• Streaming Support: Real-time AI responses with streaming capabilities
• Type Safety: Full TypeScript support for AI operations
• RAG Support: Built-in Retrieval Augmented Generation capabilities
• Embeddings: Text embeddings and semantic search functionality
• Custom Models: Extensible model registry for custom AI providers

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Getting Started

1. Set up your environment variables
2. Configure OpenRouter
3. Use the AI SDK components
4. Implement server actions for AI operations

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Available AI Features

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Basic Features

• Chat interfaces
• Text generation
• Image generation
• Structured data extraction

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Advanced Features

• RAG (Retrieval Augmented Generation)
• Semantic search with embeddings
• Custom model integration
• Advanced streaming with progress tracking
• Circuit breaker and retry patterns

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Architecture

lib/ai/
├── openrouter.ts     # OpenRouter client
├── sdk.ts           # AI SDK configuration
├── embeddings.ts    # Text embeddings
├── rag.ts          # RAG implementation
├── vector-store.ts  # Vector storage
└── models/         # Custom model implementations

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Best Practices

1. Model Selection
   • Choose models based on your use case
   • Consider cost and performance trade-offs
   • Use the most efficient model for your needs
2. Error Handling
   • Implement proper error boundaries
   • Use retry logic for transient failures
   • Monitor API usage and errors
3. Performance
   • Use streaming for long-running operations
   • Implement proper caching strategies
   • Monitor response times and costs
4. Security
   • Validate all inputs and outputs
   • Implement proper access controls
   • Monitor for abuse and rate limiting

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Next Steps

• Setup Guide
• OpenRouter Integration
• AI Components
• Use Cases
• Advanced Features