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Work with LLMs on a local environment using containers
| Date | Stars |
|---|---|
| 2026-07-31 | 294 |
| 2026-08-06 | 294 |
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# Podman AI Lab Podman AI Lab is an open source extension for Podman Desktop to work with LLMs (Large Language Models) on a local environment. Featuring a recipe catalog with common AI use cases, a curated set of open source models, and a playground for learning, prototyping and experimentation, Podman AI Lab helps you to quickly and easily get started bringing AI into your applications, without depending on infrastructure beyond your laptop ensuring data privacy and security. ## Topics - [Technology](#technology) - [Extension features](#extension-features) - [Requirements](#requirements) - [Installation](#installation) - [Usage](#usage) - [Contributing](#contributing) - [Feedback](#feedback) ## Technology Podman AI Lab uses [Podman](https://podman.io) machines to run inference servers for LLM models and AI applications. The AI models can be downloaded, and common formats like [GGUF](https://github.com/ggerganov/ggml/blob/master/docs/gguf.md), [Pytorch](https://pytorch.org) or [Tensorflow](https://www.tensorflow.org) are supported. ## Extension features ### AI models Podman AI Lab provides a curated list of open source AI models and LLMs. Once downloaded, the models are available to be used for AI applications, model services and playgrounds. #### Model services Once a model is downloaded, a model service can be started. A model service is an inference server that is running in a container and exposing the model through the well-known chat API common to many providers. #### Playgrounds The integrated Playground environments allow for experimenting with available models in a local environment. An intuitive user prompt helps in exploring the capabilities and accuracy of various models and aids in finding the best model for the use case at hand. The Playground interface further allows for parameterizing models to further optimize the settings and attributes of each model. ### AI applications Once an AI model is available through a well-known endpoint, it's easy to imagine a new world of applications that will connect and use the AI model. Podman AI Lab supports AI applications as a set of containers that are connected together. Podman AI Lab ships with a so-called Recipes Catalog that helps you navigate a number of core AI use cases and problem domains such as Chat Bots, Code Generators and Text Summarizers. Each recipe comes with detailed explanations and sample applications that can be run with various large language models (LLMs). Experimenting with multiple models allows finding the optimal one for your use case. ## Requirements ### Software - [Podman Desktop 1.8.0+](https://github.com/containers/podman-desktop) - [Podman 4.9.0+](https://github.com/podman-container-tools/podman) - Compatible with Windows, macOS & Linux ### Hardware LLMs AI models are heavy resource consumers both in terms of memory and CPU. Each of the provided models consumes about 4GiB of memory and requires at least 4 CPUs to run. We recommend a minimum of 12GB of memory and at least 4 CPUs for the Podman machine. On Windows, the podman machine shares memory and CPU with all the Windows Subsystem for Linux (WSL) machines. By default, WSL is set to 50% of total memory and all logical processors. This can be changed in the WSL Settings (See [WSL Config](https://learn.microsoft.com/en-us/windows/wsl/wsl-config#wslconfig)). As an additional recommended practice, do not run more than 3 models simultaneously. ## Installation You can install the Podman AI Lab extension directly inside Podman Desktop. Go to Extensions > Catalog > Install Podman AI Lab.  To install a development version, use the `Install custom...` action as shown in the recording below. The name of the image to use is `ghcr.io/containers/podman-desktop-extension-ai-lab`. You can get released tags for the image at https://github.com/containers/podman-desktop-extension-ai-lab/pkgs/con
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matched fp:458068f14475c0de, llm:Repository topics: ai, containers, inference-server, llms, local, podman; description: 'Work with LLMs on a local environment using containers'
matched fp:458068f14475c0de, llm:Repository topics: ai, containers, inference-server, llms, local, podman; description: 'Work with LLMs on a local environment using containers'
matched fp:458068f14475c0de, llm:Repository topics: ai, containers, inference-server, llms, local, podman; description: 'Work with LLMs on a local environment using containers'