diff --git a/docs/index.md b/docs/index.md index 2c492a89..2631e18c 100644 --- a/docs/index.md +++ b/docs/index.md @@ -44,12 +44,55 @@ permalink: / # Install llmware +{: .note} +> New wheels are built generally on PyPy on a weekly basis and updated on PyPy versioning. +> The development repo is updated and current at all times, but may have updates that are not yet in the PyPy wheel. +> All wheels are built and tested on +> - Mac Metal +> - Mac x86 +> - Windows x86 (+ with CUDA) +> - Linux x86 (+ with CUDA) - most testing on Ubuntu 22 and Ubuntu 20 - which are recommended. +> - Linux aarch64 + +{: .note} +> We recommend that you use at least ``llmware >= 0.2.0``. Other than that, make sure that you have the following +> set up. +> - Platforms: Mac M1, Mac x86, Windows, Linux (Ubuntu 22 preferred) +> - Hardware: 16 GB RAM minimum +> - Python versions: 3.9, 3.10, 3.11 + +You can install ``llmware`` via the Python Package Index (PIP), or you can manually download the ``wheel`` files from +the [GitHub repository](https://github.com/llmware-ai/llmware/tree/main/wheel_archives). + +## PIP You can easily install `llmware` via `pip`. ```bash pip install llmware ``` +## Manual install of wheel files +First, go to the [wheel\_archives](https://github.com/llmware-ai/llmware/tree/main/wheel_archives) folder +and download the *wheel* you want to install. +For example, if you want to install ``llmware`` version ``0.2.5`` then choose ``llmware-0.2.5-py3-none-any.whl``. +After downloading, place the ``wheel`` archive in a folder. +Finally, navigate to that folder and and run ``pip3 install llmware-0.2.5-py3-none-any.whl``. +On linux, a typical work flow would be the following. + +```bash +cd Downloads + +mkdir llmware +cd llmware + +wget https://github.com/\ +llmware-ai/llmware/\ +blob/432b5530cda158f57442a3fe4a9f03a20945a41c/\ +wheel_archives/llmware-0.2.5-py3-none-any.whl + +pip3 install llmware-0.2.5-py3-none-any.whl +``` + # When to use llmware ``llmware`` focuses on making it easy to integrate open source small specialized models and connecting enterprise knowledge safely and securely.