phoenix-oss/llama-stack-mirror
0
0
Fork 1
mirror of https://github.com/meta-llama/llama-stack.git synced 2025-08-03 09:21:45 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions

Add link to public docs

Browse source
This commit is contained in:
Jash Gulabrai 2025-04-17 08:44:21 -04:00
parent 88aa70add7
commit 6c77d7f693
2 changed files with 4 additions and 4 deletions
Download patch file Download diff file Expand all files Collapse all files

4
docs/source/distributions/self_hosted_distro/nvidia.md
View file

@ -57,7 +57,7 @@ The following models are available by default:
Make sure you have access to a NVIDIA API Key. You can get one by visiting [https://build.nvidia.com/](https://build.nvidia.com/). Use this key for the `NVIDIA_API_KEY` environment variable. Make sure you have access to a NVIDIA API Key. You can get one by visiting [https://build.nvidia.com/](https://build.nvidia.com/). Use this key for the `NVIDIA_API_KEY` environment variable.
### Deploy NeMo Microservices Platform ### Deploy NeMo Microservices Platform
The NVIDIA NeMo microservices platform supports end-to-end microservice deployment of a complete AI flywheel on your Kubernetes cluster through the NeMo Microservices Helm Chart. Please reference the [NVIDIA NeMo Microservices documentation](https://aire.gitlab-master-pages.nvidia.com/microservices/documentation/latest/nemo-microservices/latest-early_access/set-up/deploy-as-platform/index.html) for platform prerequisites and instructions to install and deploy the platform. The NVIDIA NeMo microservices platform supports end-to-end microservice deployment of a complete AI flywheel on your Kubernetes cluster through the NeMo Microservices Helm Chart. Please reference the [NVIDIA NeMo Microservices documentation](https://docs.nvidia.com/nemo/microservices/documentation/latest/nemo-microservices/latest-early_access/set-up/deploy-as-platform/index.html) for platform prerequisites and instructions to install and deploy the platform.
## Supported Services ## Supported Services
Each Llama Stack API corresponds to a specific NeMo microservice. The core microservices (Customizer, Evaluator, Guardrails) are exposed by the same endpoint. The platform components (Data Store) are each exposed by separate endpoints. Each Llama Stack API corresponds to a specific NeMo microservice. The core microservices (Customizer, Evaluator, Guardrails) are exposed by the same endpoint. The platform components (Data Store) are each exposed by separate endpoints.
@ -117,7 +117,7 @@ curl --location "$NEMO_URL/v1/deployment/model-deployments" \
} }
}' }'
``` ```
This NIM deployment should take approximately 10 minutes to go live. [See the docs](https://aire.gitlab-master-pages.nvidia.com/microservices/documentation/latest/nemo-microservices/latest-early_access/get-started/tutorials/deploy-nims.html#) for more information on how to deploy a NIM and verify it's available for inference. This NIM deployment should take approximately 10 minutes to go live. [See the docs](https://docs.nvidia.com/nemo/microservices/documentation/latest/nemo-microservices/latest-early_access/get-started/tutorials/deploy-nims.html#) for more information on how to deploy a NIM and verify it's available for inference.
You can also remove a deployed NIM to free up GPU resources, if needed. You can also remove a deployed NIM to free up GPU resources, if needed.
```sh ```sh

4
llama_stack/templates/nvidia/doc_template.md
View file

@ -31,7 +31,7 @@ The following models are available by default:
Make sure you have access to a NVIDIA API Key. You can get one by visiting [https://build.nvidia.com/](https://build.nvidia.com/). Use this key for the `NVIDIA_API_KEY` environment variable. Make sure you have access to a NVIDIA API Key. You can get one by visiting [https://build.nvidia.com/](https://build.nvidia.com/). Use this key for the `NVIDIA_API_KEY` environment variable.
### Deploy NeMo Microservices Platform ### Deploy NeMo Microservices Platform
The NVIDIA NeMo microservices platform supports end-to-end microservice deployment of a complete AI flywheel on your Kubernetes cluster through the NeMo Microservices Helm Chart. Please reference the [NVIDIA NeMo Microservices documentation](https://aire.gitlab-master-pages.nvidia.com/microservices/documentation/latest/nemo-microservices/latest-early_access/set-up/deploy-as-platform/index.html) for platform prerequisites and instructions to install and deploy the platform. The NVIDIA NeMo microservices platform supports end-to-end microservice deployment of a complete AI flywheel on your Kubernetes cluster through the NeMo Microservices Helm Chart. Please reference the [NVIDIA NeMo Microservices documentation](https://docs.nvidia.com/nemo/microservices/documentation/latest/nemo-microservices/latest-early_access/set-up/deploy-as-platform/index.html) for platform prerequisites and instructions to install and deploy the platform.
## Supported Services ## Supported Services
Each Llama Stack API corresponds to a specific NeMo microservice. The core microservices (Customizer, Evaluator, Guardrails) are exposed by the same endpoint. The platform components (Data Store) are each exposed by separate endpoints. Each Llama Stack API corresponds to a specific NeMo microservice. The core microservices (Customizer, Evaluator, Guardrails) are exposed by the same endpoint. The platform components (Data Store) are each exposed by separate endpoints.
@ -91,7 +91,7 @@ curl --location "$NEMO_URL/v1/deployment/model-deployments" \
} }
}' }'
``` ```
This NIM deployment should take approximately 10 minutes to go live. [See the docs](https://aire.gitlab-master-pages.nvidia.com/microservices/documentation/latest/nemo-microservices/latest-early_access/get-started/tutorials/deploy-nims.html#) for more information on how to deploy a NIM and verify it's available for inference. This NIM deployment should take approximately 10 minutes to go live. [See the docs](https://docs.nvidia.com/nemo/microservices/documentation/latest/nemo-microservices/latest-early_access/get-started/tutorials/deploy-nims.html#) for more information on how to deploy a NIM and verify it's available for inference.
You can also remove a deployed NIM to free up GPU resources, if needed. You can also remove a deployed NIM to free up GPU resources, if needed.
```sh ```sh