Case Study: LLM Server
Multi-Provider API Infrastructure for Mobile Apps
A FastAPI backend that gives mobile apps unified access to multiple LLM providers. Pipeline processing for multi-step workflows, circuit breaker patterns for resilient failure handling, and seamless model switching across OpenAI, Anthropic, Google, and Hugging Face.
The Problem
Mobile apps that use LLMs need a backend layer. The server provides unified LLM access for mobile applications through RESTful APIs, acting as the bridge between mobile clients and multiple LLM providers.
Architecture
Unified Provider Interface
- Multi-provider support — OpenAI GPT-4, Anthropic Claude, Google Gemini, and Hugging Face models behind a single API
- Circuit breaker pattern — resilient API failure handling
- Seamless model switching — standardized interface enabling failover across providers
Pipeline Processing
- Multi-step workflows — chain operations like image → text extraction → structured data in a single request
- DSPy integration — structured data extraction pipelines, including contact information extraction from images
- Versioning middleware — track which program version and model produced each result
Deployment
- Modal.com deployment with Cloudflare tunnels
- Prometheus monitoring
- GitHub Actions CI/CD
Results
- Production-ready deployment with Modal.com and Cloudflare integration
- Supports OpenAI GPT-4, Anthropic Claude, Google Gemini, and Hugging Face models
- Pipeline processing architecture supporting image → text → structured data workflows
- Comprehensive versioning system for program and model tracking
View the Source
The server code is available on GitHub.