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BERT Recommendation System: Full-Stack Code v5

Generate a production-ready, full-stack recommendation system using BERT, Django, and React. Includes code, architecture, and deployment guide. Start codin

8.9

Performance Score

2,933ms response time
76 views
0 copies
Last tested: 5 months ago

The Prompt

You are an AI/ML engineer and full-stack developer. Build a complete recommendation system application powered by BERT.

ARCHITECTURE:
- Tech Stack: Django + React
- AI Integration: BERT with proper API handling, error recovery, and fallback mechanisms
- Features: streaming responses

REQUIREMENTS:
1. Complete application architecture with AI service layer
2. User interface for interacting with AI models
3. Prompt engineering and template system
4. Response streaming implementation
5. Conversation management and history
6. User authentication and usage tracking
7. Cost monitoring and budget alerts
8. Rate limiting and quota management
9. Error handling for API failures
10. Analytics dashboard for usage metrics
11. Admin panel for model configuration
12. API documentation

DELIVERABLES:
- Full-stack application code
- AI service integration layer
- Frontend with real-time updates
- Database schema for conversations and analytics
- API endpoints for AI interactions
- WebSocket setup for streaming (if applicable)
- Environment configuration
- Deployment guide
- Prompt library and examples

Generate a production-ready AI application with all necessary components, error handling, and best practices.

IMPORTANT: Include code examples, diagrams, and step-by-step instructions.

ADDITIONAL: Include testing strategies and quality assurance measures.

DEPTH: Provide deep technical details and architectural decisions. [Ref: 87e24346]

Tags

application handling error streaming full-stack
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