llama-stack/docs/source/distributions/remote_hosted_distro/nvidia.md

NVIDIA Distribution

The llamastack/distribution-nvidia distribution consists of the following provider configurations.

API	Provider(s)
agents	inline::meta-reference
datasetio	inline::localfs
eval	inline::meta-reference
inference	remote::nvidia
safety	remote::nvidia
scoring	inline::basic
telemetry	inline::meta-reference
tool_runtime	inline::rag-runtime
vector_io	inline::faiss

Environment Variables

The following environment variables can be configured:

• NVIDIA_API_KEY: NVIDIA API Key (default: ``)
• GUARDRAILS_SERVICE_URL: URL for the NeMo Guardrails Service (default: http://0.0.0.0:7331)
• INFERENCE_MODEL: Inference model (default: Llama3.1-8B-Instruct)
• SAFETY_MODEL: Name of the model to use for safety (default: meta/llama-3.1-8b-instruct)

Models

The following models are available by default:

• meta/llama3-8b-instruct (aliases: meta-llama/Llama-3-8B-Instruct)
• meta/llama3-70b-instruct (aliases: meta-llama/Llama-3-70B-Instruct)
• meta/llama-3.1-8b-instruct (aliases: meta-llama/Llama-3.1-8B-Instruct)
• meta/llama-3.1-70b-instruct (aliases: meta-llama/Llama-3.1-70B-Instruct)
• meta/llama-3.1-405b-instruct (aliases: meta-llama/Llama-3.1-405B-Instruct-FP8)
• meta/llama-3.2-1b-instruct (aliases: meta-llama/Llama-3.2-1B-Instruct)
• meta/llama-3.2-3b-instruct (aliases: meta-llama/Llama-3.2-3B-Instruct)
• meta/llama-3.2-11b-vision-instruct (aliases: meta-llama/Llama-3.2-11B-Vision-Instruct)
• meta/llama-3.2-90b-vision-instruct (aliases: meta-llama/Llama-3.2-90B-Vision-Instruct)
• nvidia/llama-3.2-nv-embedqa-1b-v2
• nvidia/nv-embedqa-e5-v5
• nvidia/nv-embedqa-mistral-7b-v2
• snowflake/arctic-embed-l

Prerequisite: API Keys

Make sure you have access to a NVIDIA API Key. You can get one by visiting https://build.nvidia.com/.

Running Llama Stack with NVIDIA

You can do this via Conda (build code) or Docker which has a pre-built image.

Via Docker

This method allows you to get started quickly without having to build the distribution code.

LLAMA_STACK_PORT=5001
docker run \
  -it \
  --pull always \
  -p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
  -v ./run.yaml:/root/my-run.yaml \
  llamastack/distribution-nvidia \
  --yaml-config /root/my-run.yaml \
  --port $LLAMA_STACK_PORT \
  --env NVIDIA_API_KEY=$NVIDIA_API_KEY

Via Conda

llama stack build --template nvidia --image-type conda
llama stack run ./run.yaml \
  --port 5001 \
  --env NVIDIA_API_KEY=$NVIDIA_API_KEY
  --env INFERENCE_MODEL=$INFERENCE_MODEL