Build

Build locally

Requirements:

Either Docker/podman, or

Golang >= 1.21
Cmake/make
GCC

In order to build the LocalAI container image locally you can use docker:

# build the image
docker build -t localai .
docker run localai

Or you can build the manually binary with make:

git clone https://github.com/go-skynet/LocalAI
cd LocalAI
make build

To run: ./local-ai

Note

CPU flagset compatibility

LocalAI uses different backends based on ggml and llama.cpp to run models. If your CPU doesn’t support common instruction sets, you can disable them during build:

CMAKE_ARGS="-DLLAMA_F16C=OFF -DLLAMA_AVX512=OFF -DLLAMA_AVX2=OFF -DLLAMA_AVX=OFF -DLLAMA_FMA=OFF" make build

To have effect on the container image, you need to set REBUILD=true:

docker run  quay.io/go-skynet/localai
docker run --rm -ti -p 8080:8080 -e DEBUG=true -e MODELS_PATH=/models -e THREADS=1 -e REBUILD=true -e CMAKE_ARGS="-DLLAMA_F16C=OFF -DLLAMA_AVX512=OFF -DLLAMA_AVX2=OFF -DLLAMA_AVX=OFF -DLLAMA_FMA=OFF" -v $PWD/models:/models quay.io/go-skynet/local-ai:latest

Build on mac

Building on Mac (M1 or M2) works, but you may need to install some prerequisites using brew.

The below has been tested by one mac user and found to work. Note that this doesn’t use Docker to run the server:

# install build dependencies
brew install abseil cmake go grpc protobuf wget

# clone the repo
git clone https://github.com/go-skynet/LocalAI.git

cd LocalAI

# build the binary
make build

# Download gpt4all-j to models/
wget https://gpt4all.io/models/ggml-gpt4all-j.bin -O models/ggml-gpt4all-j

# Use a template from the examples
cp -rf prompt-templates/ggml-gpt4all-j.tmpl models/

# Run LocalAI
./local-ai --models-path=./models/ --debug=true

# Now API is accessible at localhost:8080
curl http://localhost:8080/v1/models

curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/json" -d '{
     "model": "ggml-gpt4all-j",
     "messages": [{"role": "user", "content": "How are you?"}],
     "temperature": 0.9 
   }'

Build with Image generation support

Requirements: OpenCV, Gomp

Image generation is experimental and requires GO_TAGS=stablediffusion to be set during build:

make GO_TAGS=stablediffusion build

Build with Text to audio support

Requirements: piper-phonemize

Text to audio support is experimental and requires GO_TAGS=tts to be set during build:

make GO_TAGS=tts build

Acceleration

List of the variables available to customize the build:

Variable	Default	Description
`BUILD_TYPE`	None	Build type. Available: `cublas`, `openblas`, `clblas`, `metal`,`hipblas`
`GO_TAGS`	`tts stablediffusion`	Go tags. Available: `stablediffusion`, `tts`
`CLBLAST_DIR`		Specify a CLBlast directory
`CUDA_LIBPATH`		Specify a CUDA library path

OpenBLAS

Software acceleration.

Requirements: OpenBLAS

make BUILD_TYPE=openblas build

CuBLAS

Nvidia Acceleration.

Requirement: Nvidia CUDA toolkit

Note: CuBLAS support is experimental, and has not been tested on real HW. please report any issues you find!

make BUILD_TYPE=cublas build

More informations available in the upstream PR: https://github.com/ggerganov/llama.cpp/pull/1412

Hipblas (AMD GPU)

AMD GPU Acceleration

Requirement: ROCm

make BUILD_TYPE=hipblas build

Specific GPU targets can be specified with GPU_TARGETS:

make BUILD_TYPE=hipblas GPU_TARGETS=gfx90a build

ClBLAS

AMD/Intel GPU acceleration.

Requirement: OpenCL, CLBlast

make BUILD_TYPE=clblas build

To specify a clblast dir set: CLBLAST_DIR

Metal (Apple Silicon)

make BUILD_TYPE=metal build

# Set `gpu_layers: 1` to your YAML model config file and `f16: true`
# Note: only models quantized with q4_0 are supported!

Windows compatibility

Make sure to give enough resources to the running container. See https://github.com/go-skynet/LocalAI/issues/2