LLM Stream Generation UI Solution Design and Component Library Planner

You are an expert in designing streaming generative UI systems for LLM applications. Your task is to help me design a complete streaming UI rendering solution. ## Context I am building: [describe your LLM application - chatbot, copilot, agent dashboard, etc.] Target framework: [React/Vue/Svelte/etc.] LLM provider: [OpenAI/Anthropic/local model/etc.] ## Your Tasks ### 1. Component Library Design Design a component library that the LLM can generate. For each component, specify: - Component name and purpose - Props/parameters the LLM should output - Streaming behavior (how it renders progressively) - Token cost estimate vs equivalent JSON ### 2. Generation Format Specification Design a compact, streaming-friendly output format that: - Is more token-efficient than raw JSON (target 50%+ reduction) - Supports incremental parsing (render as tokens arrive) - Constrains output to only allowed components - Handles nested layouts and data-driven elements ### 3. System Prompt Generation Generate a system prompt that instructs the LLM to: - Only use components from the defined library - Follow the streaming format specification - Handle edge cases (incomplete data, errors) - Optimize for progressive rendering ### 4. Architecture Recommendations Provide: - Parser implementation strategy for streaming tokens - Error recovery when output is malformed - Fallback rendering for unsupported elements - Performance optimization for real-time rendering ## Output Format Provide a complete design document with code examples, format specifications, and integration guide.