LABINTERMEDIATE
Multi-Provider LLM Integration
Build a production-ready FastAPI service with provider abstraction, streaming responses, and automatic failover between LLM providers.
60 minutes
ai-infrastructure/llm-integration
Lab Overview
This hands-on lab teaches you to build a multi-provider LLM integration service using FastAPI and Python.
You'll learn to:
- Create an abstract LLM client interface for provider-agnostic code
- Implement OpenAI and Ollama providers with a unified interface
- Build automatic failover when the primary provider fails
- Implement streaming responses for better user experience
- Add structured JSON output with Pydantic validation
- Test the complete service with multiple scenarios
This lab builds the foundation for the AI Gateway you'll deploy in the next lab.
Prerequisites
python-async-patterns
fastapi-basics
ollama-local-llm
Technologies Covered
llmfastapipythonollamaopenaistreamingfailover
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Hands-On Labs
- Browser-based cloud labs
- Pre-configured VMs ready to use
- Playgrounds for experiments
- Multi-VM realistic scenarios
AWS Integration
- Managed AWS Account included
- Pre-configured environments
- Real-world cloud scenarios
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- Priority support
- Active community forum
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- No software installation needed
- Automatic environment provisioning
- Works on any device
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