Build fluency in LiteLLM's unified proxy for many LLM providers.
0 / 5 completed
1 / 5
At standup, the team wants one OpenAI-style endpoint in front of many providers. Which LiteLLM component does this?
The LiteLLM router (proxy) exposes a unified OpenAI-compatible endpoint that dispatches to many backend providers. Clients call one URL and the proxy handles provider differences. This centralizes access across models.
2 / 5
During a design review, a dev configures which models the proxy serves. Where is this declared?
LiteLLM's model list in the proxy config maps friendly model names to provider-specific deployments and keys. The router uses it to know what it can serve and how to route. It is the heart of proxy configuration.
3 / 5
In a code review, the team adds two deployments of the same model to spread traffic. What capability is this?
Listing multiple deployments under one model name enables load balancing across them by the router. It distributes requests to manage rate limits and throughput. This is a core reliability feature of the proxy.
4 / 5
An incident report shows the primary provider was down but requests still succeeded. Which feature did that?
LiteLLM supports fallbacks, where the router retries a request on an alternate model or provider when the primary fails. You configure ordered fallback lists. This improves resilience to provider outages.
5 / 5
During a PR review, finance wants per-team spend limits and isolated keys. Which two LiteLLM features apply?
LiteLLM provides cost tracking to record spend per request and virtual keys to issue per-team keys with budgets and limits. Together they enable governance over LLM usage. Finance teams rely on both for accountability.