Use Bifrost as a drop-in proxy for LiteLLM applications with zero code changes.
Since LiteLLM already provides multi-provider abstraction, Bifrost adds enterprise features like governance, semantic caching, MCP tools, observability, etc, on top of your existing setup.Endpoint:/litellm
Provider Compatibility: This integration only works for AI providers that both LiteLLM and Bifrost support. If you’re using a provider specific to LiteLLM that Bifrost doesn’t support (or vice versa), those requests will fail.
from litellm import completion# Configure client to use Bifrostresponse = completion( model="gpt-4o-mini", messages=[{"role": "user", "content": "Hello!"}], base_url="http://localhost:8080/litellm" # Point to Bifrost)print(response.choices[0].message.content)
The LiteLLM integration supports all features that are available in both the LiteLLM SDK and Bifrost core functionality. Your existing LiteLLM code works seamlessly with Bifrost’s enterprise features. 😄