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# What does this PR do? Includes SambaNova safety adaptor to use the sambanova cloud served Meta-Llama-Guard-3-8B minor updates in sambanova docs ## Test Plan pytest -s -v tests/integration/safety/test_safety.py --stack-config=sambanova --safety-shield=sambanova/Meta-Llama-Guard-3-8B
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SambaNova Distribution
:maxdepth: 2
:hidden:
self
The llamastack/distribution-sambanova
distribution consists of the following provider configurations.
API | Provider(s) |
---|---|
agents | inline::meta-reference |
inference | remote::sambanova , inline::sentence-transformers |
safety | remote::sambanova |
telemetry | inline::meta-reference |
tool_runtime | remote::brave-search , remote::tavily-search , inline::rag-runtime , remote::model-context-protocol , remote::wolfram-alpha |
vector_io | inline::faiss , remote::chromadb , remote::pgvector |
Environment Variables
The following environment variables can be configured:
LLAMASTACK_PORT
: Port for the Llama Stack distribution server (default:8321
)SAMBANOVA_API_KEY
: SambaNova API Key (default: ``)
Models
The following models are available by default:
sambanova/Meta-Llama-3.1-8B-Instruct (aliases: meta-llama/Llama-3.1-8B-Instruct)
sambanova/Meta-Llama-3.1-405B-Instruct (aliases: meta-llama/Llama-3.1-405B-Instruct-FP8)
sambanova/Meta-Llama-3.2-1B-Instruct (aliases: meta-llama/Llama-3.2-1B-Instruct)
sambanova/Meta-Llama-3.2-3B-Instruct (aliases: meta-llama/Llama-3.2-3B-Instruct)
sambanova/Meta-Llama-3.3-70B-Instruct (aliases: meta-llama/Llama-3.3-70B-Instruct)
sambanova/Llama-3.2-11B-Vision-Instruct (aliases: meta-llama/Llama-3.2-11B-Vision-Instruct)
sambanova/Llama-3.2-90B-Vision-Instruct (aliases: meta-llama/Llama-3.2-90B-Vision-Instruct)
sambanova/Llama-4-Scout-17B-16E-Instruct (aliases: meta-llama/Llama-4-Scout-17B-16E-Instruct)
sambanova/Llama-4-Maverick-17B-128E-Instruct (aliases: meta-llama/Llama-4-Maverick-17B-128E-Instruct)
sambanova/Meta-Llama-Guard-3-8B (aliases: meta-llama/Llama-Guard-3-8B)
Prerequisite: API Keys
Make sure you have access to a SambaNova API Key. You can get one by visiting SambaNova.ai.
Running Llama Stack with SambaNova
You can do this via Conda (build code) or Docker which has a pre-built image.
Via Docker
LLAMA_STACK_PORT=8321
llama stack build --template sambanova --image-type container
docker run \
-it \
-p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
-v ~/.llama:/root/.llama \
distribution-sambanova \
--port $LLAMA_STACK_PORT \
--env SAMBANOVA_API_KEY=$SAMBANOVA_API_KEY
Via Venv
llama stack build --template sambanova --image-type venv
llama stack run --image-type venv ~/.llama/distributions/sambanova/sambanova-run.yaml \
--port $LLAMA_STACK_PORT \
--env SAMBANOVA_API_KEY=$SAMBANOVA_API_KEY
Via Conda
llama stack build --template sambanova --image-type conda
llama stack run --image-type conda ~/.llama/distributions/sambanova/sambanova-run.yaml \
--port $LLAMA_STACK_PORT \
--env SAMBANOVA_API_KEY=$SAMBANOVA_API_KEY