ai-streaming-setup

Set up AI Streaming Implementation

Create a robust streaming AI implementation with the Vercel AI SDK for: $ARGUMENTS

Current Project Analysis

Project structure: !find . -type f -name "*.ts" -o -name "*.tsx" | grep -E "(api|components|lib)" | head -10

Existing AI SDK setup: !grep -r "from 'ai'" . --include="*.ts" --include="*.tsx" | head -5

Package dependencies: !cat package.json | jq '.dependencies | to_entries[] | select(.key | contains("ai")) | "\(.key): \(.value)"' -r 2>/dev/null || echo "No AI dependencies found"

Streaming Type Analysis

Text Streaming: Real-time text generation with token-by-token updates Object Streaming: Structured data streaming with partial object updates
Chat Streaming: Conversational interfaces with message history Completion Streaming: Single-turn completions with progressive updates

Your Task

1. Assess current streaming setup and identify gaps
2. Implement the appropriate streaming pattern based on the specified type
3. Create robust error handling for stream interruptions and failures
4. Add proper loading states and user feedback
5. Implement stream cancellation for better UX
6. Set up proper TypeScript types for streaming responses
7. Add performance optimizations (chunking, backpressure handling)
8. Include comprehensive testing for edge cases

Implementation Requirements

Server-Side Streaming

• Proper route handler setup with maxDuration
• Model configuration with appropriate parameters
• Stream response formatting with toUIMessageStreamResponse() or toTextStreamResponse()
• Abort signal handling for stream cancellation
• Error boundaries and fallback responses

Client-Side Streaming

• React hooks for stream management (useChat, useCompletion, useObject)
• Progressive UI updates with optimistic rendering
• Loading states and stream status indicators
• Error handling with retry mechanisms
• Stream interruption and cancellation