We've all been there: you need your app to switch from Claude to ChatGPT, but they're on separate clouds. This means configuring cross-cloud permissions, managing different API formats, and wrestling with vendor-specific authentication - but what if you could just proxy those prompts to the appropriate cloud and avoid all the additional setup headaches? Welcome to LiteLLM, your new best friend in the multi-model world.

LiteLLM acts as a universal translator for over 100 LLM providers (OpenAI, Claude, Bedrock, Azure, Cohere, Hugging Face, and more), converting everything to a unified OpenAI API format so your code doesn't have to know whether it's talking to GPT-4 or Llama running locally on your laptop. Notice your AI spend creeping up and want to understand what's burning through your budget? LiteLLM provides detailed cost tracking, spending limits per user or project, and can even load balance across multiple models to optimize for cost and performance. It handles the nitty-gritty of rate limiting, failover logic, and streaming responses while providing enterprise-grade logging and monitoring.

This session will cover what LiteLLM is, how it simplifies multi-cloud AI architecture, and practical setup strategies including cost management, load balancing, and security considerations. In our brave new world of model diversity, technology like LiteLLM isn't just convenient - it's crucial for maintaining sanity while building production AI applications. Get ready to take your LLM consumption game to the next level without losing your mind (or your budget) in the process.