Streaming responses provide immediate feedback to users by delivering content token-by-token as it’s generated, dramatically improving perceived performance and user experience.
Overview
Requesty supports streaming responses from all major providers (OpenAI, Anthropic, Google, Mistral) using Server-Sent Events (SSE). Instead of waiting for the complete response, your applications can display content as it’s being generated.Why Use Streaming?
Improved User Experience
Users see responses immediately, reducing perceived wait time by up to 80%
Better Engagement
Real-time content delivery keeps users engaged during longer responses
Reduced Timeouts
Avoid timeout issues on slow or complex requests
Progressive Display
Enable progressive UI updates as content becomes available
Implementation
Basic Streaming Setup
Enable streaming by setting thestream
parameter to true
in your request:
Advanced Streaming Patterns
- Collecting Complete Response
- Function Call Streaming
- Error Handling
Accumulate streaming chunks to build the full response:
Streaming Features
Supported Capabilities
- Text Generation: Standard chat completions
- Function Calling: Streaming function calls and arguments
- Tool Usage: Tool calls with streaming responses
- Multi-turn Conversations: Streaming in conversation contexts
- System Messages: Full prompt template support
- Parameters: Temperature, max_tokens, and other standard parameters
Provider Compatibility
All major providers support streaming through Requesty:- OpenAI: GPT-4, GPT-3.5, and all variants
- Anthropic: Claude 3.5 Sonnet, Claude 3 Haiku/Opus
- Google: Gemini Pro, Gemini Flash
- Mistral: All Mistral models
- Meta: Llama models
Best Practices
Optimize for User Experience
Optimize for User Experience
- Display content immediately as it arrives
- Use typing indicators or progress bars
- Handle partial responses gracefully
- Implement smooth scrolling for long content
Handle Network Issues
Handle Network Issues
- Implement connection retry logic
- Gracefully handle stream interruptions
- Provide fallback to non-streaming mode
- Monitor stream health and performance
Performance Optimization
Performance Optimization
- Use
flush=True
for immediate output display - Batch UI updates for better performance
- Implement efficient chunk processing
- Consider client-side buffering strategies
Production Considerations
Production Considerations
- Implement proper error boundaries
- Log streaming metrics and performance
- Test with various network conditions
- Plan for graceful degradation
Common Use Cases
Chat Applications
Real-time messaging with immediate response display
Content Generation
Progressive article, blog, or document creation
Code Generation
Live code generation with syntax highlighting
Data Analysis
Streaming analysis results and insights
Creative Writing
Story, poem, or creative content generation
Technical Documentation
Progressive documentation and explanation generation
Integration Examples
React Component
Troubleshooting
Always implement proper error handling when using streaming responses, as network interruptions can cause incomplete responses.
Common Issues
- Stream Interruption: Implement retry logic and graceful fallbacks
- Partial Responses: Handle incomplete function calls or content
- Performance: Optimize chunk processing for large responses
- Browser Compatibility: Test streaming across different browsers and devices