forked from phoenix-oss/llama-stack-mirror
09ed0e9c9f
This PR moves some content from [the recent blog post](https://blog.vllm.ai/2025/01/27/intro-to-llama-stack-with-vllm.html) to here as a more official guide for users who'd like to deploy Llama Stack on Kubernetes. --------- Signed-off-by: Yuan Tang <terrytangyuan@gmail.com>
34 lines
1.6 KiB
Markdown
34 lines
1.6 KiB
Markdown
# Starting a Llama Stack Server
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You can run a Llama Stack server in one of the following ways:
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**As a Library**:
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This is the simplest way to get started. Using Llama Stack as a library means you do not need to start a server. This is especially useful when you are not running inference locally and relying on an external inference service (eg. fireworks, together, groq, etc.) See [Using Llama Stack as a Library](importing_as_library)
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**Container**:
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Another simple way to start interacting with Llama Stack is to just spin up a container (via Docker or Podman) which is pre-built with all the providers you need. We provide a number of pre-built images so you can start a Llama Stack server instantly. You can also build your own custom container. Which distribution to choose depends on the hardware you have. See [Selection of a Distribution](selection) for more details.
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**Conda**:
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If you have a custom or an advanced setup or you are developing on Llama Stack you can also build a custom Llama Stack server. Using `llama stack build` and `llama stack run` you can build/run a custom Llama Stack server containing the exact combination of providers you wish. We have also provided various templates to make getting started easier. See [Building a Custom Distribution](building_distro) for more details.
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**Kubernetes**:
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If you have built a container image and want to deploy it in a Kubernetes cluster instead of starting the Llama Stack server locally. See [Kubernetes Deployment Guide](kubernetes_deployment) for more details.
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```{toctree}
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:maxdepth: 1
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:hidden:
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importing_as_library
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building_distro
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configuration
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selection
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kubernetes_deployment
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```
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