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Integrations

Olla supports various backends (endpoints) and front-ends integrations powered by Olla Profiles.

Backend Endpoints

Olla natively supports the following backends:

Backend Type Description
Ollama ollama Native support for Ollama, including model unification
LM Studio lm-studio Native support for LM Studio, including model unification
llama.cpp llamacpp Native support for llama.cpp lightweight C++ inference server with GGUF models, including slot management, code infill, and CPU-first design for edge deployment
vLLM vllm Native support for vLLM, including model unification
SGLang sglang Native support for SGLang with RadixAttention and Frontend Language, including model unification and vision support
Lemonade SDK lemonade Native support for Lemonade SDK, AMD's local inference solution with Ryzen AI optimisation, including model unification
LiteLLM litellm Native support for LiteLLM, providing unified gateway to 100+ LLM providers
OpenAI Compatible openai Generic support for any OpenAI-compatible API

You can use the type in Endpoint Configurations when adding new endpoints.

Frontend Support

OpenWebUI

Native support for OpenWebUI with Olla via:

Claude-Compatible Clients

Olla provides Anthropic Messages API translation, enabling Claude-compatible clients to work with any OpenAI-compatible backend:

Client Description Integration Guide
Claude Code Anthropic's official CLI coding assistant Full Anthropic API support
OpenCode Open-source AI coding assistant (SST fork) OpenAI or Anthropic API
Crush CLI Modern terminal AI assistant by Charmbracelet Dual OpenAI/Anthropic support

These clients can use local models (Ollama, LM Studio, vLLM, llama.cpp) through Olla's API translation layer.

API Translation

Olla can translate between different LLM API formats:

Translation Status Use Case
Anthropic → OpenAI ✅ Available Use Claude Code with local models

See API Translation concept for how this works.

Profiles

Profiles provide an easy way to customise the behaviours of existing supported integrations (instead of writing Go code, compiling etc).

  • You can customise existing behaviours
  • You can extend existing functionality

You can also create a custom profile to add new capabilities or backend support until native support is added.