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making <h3> font lighter for better visibility and moving some copy

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Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>
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Francisco Javier Arceo 2025-04-09 10:32:30 -04:00
parent 3366937765
commit 72cc19a2c1
2 changed files with 14 additions and 7 deletions
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4
docs/_static/css/my_theme.css vendored
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@ -16,3 +16,7 @@
.hide-title h1 {
display: none;
}
h3 {
font-weight: normal;
}

17
docs/source/getting_started/index.md
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@ -71,6 +71,7 @@ The config file is a YAML file that specifies the providers and their configurat
::::{tab-set}
:::{tab-item} Using Python
You can use Python to build and run the Llama Stack server. This is useful for testing and development purposes.
```bash
INFERENCE_MODEL=llama3.2:3b llama stack build --template ollama --image-type venv --run
```
@ -82,11 +83,12 @@ INFO: Uvicorn running on http://['::', '0.0.0.0']:8321 (Press CTRL+C to quit
:::
:::{tab-item} Using a Container
To get started quickly, we provide various container images for the server component that work with different inference
providers out of the box. For this guide, we will use `llamastack/distribution-ollama` as the container image. If you'd
like to build your own image or customize the configurations, please check out [this guide](../references/index.md).
You can use a container image to run the Llama Stack server. We provide several container images for the server
component that works with different inference providers out of the box. For this guide, we will use
`llamastack/distribution-ollama` as the container image. If you'd like to build your own image or customize the
configurations, please check out [this guide](../references/index.md).
Lets setup some environment variables and create a local directory to mount into the container’s file system.
First lets setup some environment variables and create a local directory to mount into the container’s file system.
```bash
export INFERENCE_MODEL="meta-llama/Llama-3.2-3B-Instruct"
export LLAMA_STACK_PORT=8321
@ -130,13 +132,13 @@ docker run -it \
:::
::::
Now you can use the Llama Stack client to run inference and build agents!
### ii. Using the Llama Stack Client
Now you can use the llama stack client to run inference and build agents!
You can reuse the server setup or use the [Llama Stack Client](https://github.com/meta-llama/llama-stack-client-python/).
Note that the client package is already included in the `llama-stack` package.
### ii. Using the Llama Stack Client
Open a new terminal and navigate to the same directory you started the server from. Then set up a new or activate your
existing server virtual environment.
@ -144,6 +146,7 @@ existing server virtual environment.
:::{tab-item} Reuse the Server Setup
```bash
# As mentioned, the client is included in the llama-stack package so we can just activate the server virtual environment
source .venv/bin/activate
```
:::