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Installing

Installation#

Sibila requires Python 3.9+ and uses the llama-cpp-python package for local models and OpenAI/Mistral/other libraries to access remote models.

Install Sibila from PyPI by running:

pip install --upgrade sibila

If you only plan to use remote models (OpenAI), there's nothing else you need to do. See First Run to get it going.

Installation in edit mode

Alternatively you can install Sibila in edit mode by downloading the GitHub repository and running the following in the base folder of the repository:

pip install -e .

Enabling llama.cpp hardware acceleration for local models#

Local models will run faster with hardware acceleration enabled. Sibila uses llama-cpp-python, a python wrapper for llama.cpp and it's a good idea to make sure it was installed with the best optimization your computer can offer.

See the following sections: depending on which hardware you have, you can run the listed command which will reinstall llama-cpp-python with the selected optimization. If any error occurs you can always install the non-accelerated version, as listed at the end.

For CUDA - NVIDIA GPUs#

For CUDA acceleration in NVIDIA GPUs, you'll need to have the NVIDIA CUDA Toolkit installed. If looking for a specific CUDA version, see here.

CMAKE_ARGS="-DLLAMA_CUDA=on" \
pip install llama-cpp-python --upgrade --force-reinstall --no-cache-dir
The CUDA toolkit can also be installed from your Linux distro's package manager (e.g. apt install nvidia-cuda-toolkit).

$env:CMAKE_ARGS = "-DLLAMA_CUDA=on"
pip install llama-cpp-python --upgrade --force-reinstall --no-cache-dir
Installing llama-cpp-python with NVIDIA GPU Acceleration on Windows: A Short Guide

More info: Installing llama-cpp-python with GPU Support.

For Metal - Apple silicon macs#

CMAKE_ARGS="-DLLAMA_METAL=on" \
pip install llama-cpp-python --upgrade --force-reinstall --no-cache-dir

For ROCm AMD GPUS#

CMAKE_ARGS="-DLLAMA_HIPBLAS=on" \
pip install llama-cpp-python --upgrade --force-reinstall --no-cache-dir

$env:CMAKE_ARGS = "-DLLAMA_HIPBLAS=on"
pip install llama-cpp-python --upgrade --force-reinstall --no-cache-dir

For Vulkan supporting GPUs#

CMAKE_ARGS="-DLLAMA_VULKAN=on" \
pip install llama-cpp-python --upgrade --force-reinstall --no-cache-dir

$env:CMAKE_ARGS = "-DLLAMA_VULKAN=on"
pip install llama-cpp-python --upgrade --force-reinstall --no-cache-dir

CPU acceleration (if none of the above)#

CMAKE_ARGS="-DLLAMA_BLAS=ON -DLLAMA_BLAS_VENDOR=OpenBLAS" \
pip install llama-cpp-python --upgrade --force-reinstall --no-cache-dir

$env:CMAKE_ARGS = "-DLLAMA_BLAS=ON -DLLAMA_BLAS_VENDOR=OpenBLAS"
pip install llama-cpp-python --upgrade --force-reinstall --no-cache-dir

If you get an error running the above commands, please see llama-cpp-python's Installation configuration.

Non-accelerated#

In any case, you can always install llama-cpp-python without acceleration by running:

pip install llama-cpp-python --upgrade --force-reinstall --no-cache-dir