Practical AI Mini Program Development: Refactoring User Experience with Large Models

As a lightweight application carrier, mini programs have become an important channel for connecting enterprises and users. Integrating AI capabilities into mini programs can significantly improve user experience and operational efficiency.

1、 Typical application scenarios of AI+mini programs

  • intelligent searchSupport natural language queries to understand user intent rather than simple keyword matching
  • intelligent customer serviceDialogue based customer service based on knowledge base, with a resolution rate of over 85%
  • Content GenerationAutomatically generate product descriptions, marketing copy, and user review summaries
  • Image RecognitionVisual AI capabilities such as photo recognition, document recognition, and product recognition
  • personalized recommendationIntelligent recommendation engine based on user profile

2、 Technical architecture design

  1. Front end interaction layerResponsible for showcasing AI capabilities and user interaction
  2. API Gateway LayerUnified management of AI service calls, including flow limiting, caching, downgrade, and other strategies
  3. AI service layerIntegrate with the big model API, handle Prompt projects, context management, etc
  4. data layer: Store user conversation history, knowledge base data, vector indexes, etc

3、 Key points of performance optimization

  • First screen loading time control: AI functions are loaded as needed without blocking the main process
  • Streaming response processing: using SSE or WebSocket to achieve typewriter effects
  • Cache strategy: Cache the results of high-frequency queries to reduce API call costs

recommend adoptionHierarchical call strategySimple tasks use lightweight models, while complex tasks only call on large models.