DevOps

litellm

Operate and troubleshoot the LiteLLM proxy and Python SDK, including provider routing, authentication, budgets, reliability, caching, guardrails, observability, deployment, and public-hosting security.

★ 88 GitHub Stars
95 Score de qualité
16 Fichiers

About this Skill

Operate, configure, secure, and troubleshoot the LiteLLM AI gateway (proxy) and Python SDK: run the proxy (litellm --config), route to 100+ providers through one OpenAI-compatible API, configure model lists and routing/reliability, virtual keys, teams, budgets, rate limits, caching, guardrails, observability, and spend, and diagnose request failures. Use when deploying or running a LiteLLM proxy or gateway (config.yaml, ghcr.io/berriai/litellm), wiring the Python SDK or OpenAI SDK through it, or hardening a public-facing deployment. Do not use for operating a single inference engine (vllm, llama-cpp), for engine-selection methodology (ml-engineering), or for building applications on top of an LLM API (backend/frontend engineering).

Cas d’usage

  • Deploy a LiteLLM proxy
  • Configure multi-provider model routing
  • Manage keys, teams, budgets, and rate limits
  • Diagnose gateway and provider failures
  • Harden public-facing deployments

Fonctionnalités

  • OpenAI-compatible proxy and Python SDK guidance
  • Model routing, retries, fallbacks, and cooldowns
  • Virtual keys, teams, budgets, and spend management
  • Caching, guardrails, callbacks, and logging configuration
  • Health probing and evidence-based troubleshooting

Prérequis

  • LiteLLM (pip package or proxy image)
  • Python 3.10+ for the pip package and SDK

Agents compatibles

Not specified

Skill files

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