goose-local-inference

On-device model inference for goose. Runs GGUF models through llama.cpp (via llama-cpp-2), with an optional MLX backend on Apple silicon.

Reach it through goose-providers with the local-inference feature, which exposes LocalInferenceProvider as an ordinary Provider. Depend on this crate directly only when you need model management.

Features

Default is [] — CPU inference.

cuda, vulkan — GPU acceleration via the corresponding llama-cpp-2 backend.
mlx — the MLX backend for Apple silicon.

What it handles

Runtime and placement — InferenceRuntime describes the machine; available_inference_memory_bytes and recommend_local_model pick a model that will actually fit.
Model lifecycle — is_model_loaded, loaded_model_ids, and evict_model manage what's resident. management, local_model_registry, hf_models, and paths cover discovery, on-disk layout, and the Hugging Face catalog; huggingface_auth handles gated repos. Downloads go through goose-download-manager, re-exported here as download_manager.
Prompt formatting — prompt_template applies the model's chat template; builtin_chat_template_names() lists the bundled ones.
Tool calling — native_tool_parsing and tool_parsing extract tool calls from model output, and tool_emulation (toolshim) fills in for models with no native tool support.
Richer outputs — thinking_output separates reasoning blocks from the answer; multimodal handles image input.
Config — config_resolver and provider_utils resolve settings such as LOCAL_LLM_MODEL.

Building

The llama.cpp backends compile native code, so a C/C++ toolchain is required, plus the CUDA or Vulkan SDK when selecting those features.

bash

cargo build -p goose-local-inference
cargo build -p goose-local-inference --features mlx