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GatewaysIntermediate30 minVerified 17 days ago

LiteLLM Proxy for Multi-Provider Routing

Put one OpenAI-compatible proxy in front of OpenAI, Anthropic, Gemini, and local endpoints so agents can switch models with config, not code rewrites.

litellmgatewaymulti-provideropenai-compatibleagents
The promise

Agents and tools speak OpenAI-style APIs. Providers do not. LiteLLM proxy gives you a single base URL and model aliases across clouds and local servers.

What you will get
  • One endpoint for mixed providers
  • Model aliases like smart, cheap, local-coder
  • A place to attach logging and spend limits later
Prerequisites
  • API keys for the providers you will route to
  • Optional local OpenAI-compatible server (vLLM, Ollama-compatible gateway, etc.)
  • Python environment or Docker for LiteLLM proxy
Steps
  1. Install LiteLLM proxy via the current upstream recommended method.
  2. Create a config mapping model aliases to provider model ids.
  3. Export provider keys in the environment (never commit them).
  4. Start the proxy on a local port.
  5. Point one agent client at the proxy base URL and call an alias.

Illustrative config shape:

model_list:
  - model_name: cheap
    litellm_params:
      model: openai/gpt-4o-mini
  - model_name: smart
    litellm_params:
      model: anthropic/claude-opus-4-8
Verification
  • curl chat completion against an alias
  • Confirm the upstream provider dashboard shows the request
  • Fail closed when a key is missing (do not silently fall through to the wrong model)
Troubleshooting
  • 401/403: wrong key or org permissions
  • Model not found: alias vs upstream id mismatch
  • Tool calls fail for one provider only: schema differences — test tool-use per provider
Honest notes

A proxy is not governance. Approval gates, allowlists, and spend caps still belong in the agent broker or gateway policy layer.

Recipe verified 2026-07-13. Commands are tested but your environment may differ.

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