forked from phoenix-oss/llama-stack-mirror
b3202bcf77
# What does this PR do? adds nvidia template for creating a distribution using inference adapter for NVIDIA NIMs. ## Test Plan Please describe: Build llama stack distribution for nvidia using the template, docker and conda. ```bash (.venv) local-cdgamarose@a4u8g-0006:~/llama-stack$ llama-stack-client configure --endpoint http://localhost:5000 Done! You can now use the Llama Stack Client CLI with endpoint http://localhost:5000 (.venv) local-cdgamarose@a4u8g-0006:~/llama-stack$ llama-stack-client models list ┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━┓ ┃ identifier ┃ provider_id ┃ provider_resource_id ┃ metadata ┃ ┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━┩ │ Llama3.1-8B-Instruct │ nvidia │ meta/llama-3.1-8b-instruct │ {} │ │ meta-llama/Llama-3.2-3B-Instruct │ nvidia │ meta/llama-3.2-3b-instruct │ {} │ └──────────────────────────────────┴─────────────┴────────────────────────────┴──────────┘ (.venv) local-cdgamarose@a4u8g-0006:~/llama-stack$ llama-stack-client inference chat-completion --message "hello, write me a 2 sentence poem" ChatCompletionResponse( completion_message=CompletionMessage( content='Here is a 2 sentence poem:\n\nThe sun sets slow and paints the sky, \nA gentle hue of pink that makes me sigh.', role='assistant', stop_reason='end_of_turn', tool_calls=[] ), logprobs=None ) ``` ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [x] Ran pre-commit to handle lint / formatting issues. - [x] Read the [contributor guideline](https://github.com/meta-llama/llama-stack/blob/main/CONTRIBUTING.md), Pull Request section? - [x] Updated relevant documentation. - [ ] Wrote necessary unit or integration tests. --------- Co-authored-by: Matthew Farrellee <matt@cs.wisc.edu>
60 lines
1.5 KiB
Markdown
60 lines
1.5 KiB
Markdown
# NVIDIA Distribution
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The `llamastack/distribution-nvidia` distribution consists of the following provider configurations.
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| API | Provider(s) |
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|-----|-------------|
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| agents | `inline::meta-reference` |
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| inference | `remote::nvidia` |
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| memory | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
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| safety | `inline::llama-guard` |
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| telemetry | `inline::meta-reference` |
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### Environment Variables
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The following environment variables can be configured:
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- `LLAMASTACK_PORT`: Port for the Llama Stack distribution server (default: `5001`)
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- `NVIDIA_API_KEY`: NVIDIA API Key (default: ``)
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### Models
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The following models are available by default:
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- `${env.INFERENCE_MODEL} (None)`
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### Prerequisite: API Keys
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Make sure you have access to a NVIDIA API Key. You can get one by visiting [https://build.nvidia.com/](https://build.nvidia.com/).
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## Running Llama Stack with NVIDIA
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You can do this via Conda (build code) or Docker which has a pre-built image.
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### Via Docker
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This method allows you to get started quickly without having to build the distribution code.
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```bash
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LLAMA_STACK_PORT=5001
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docker run \
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-it \
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-p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
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-v ./run.yaml:/root/my-run.yaml \
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llamastack/distribution-nvidia \
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--yaml-config /root/my-run.yaml \
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--port $LLAMA_STACK_PORT \
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--env NVIDIA_API_KEY=$NVIDIA_API_KEY
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```
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### Via Conda
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```bash
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llama stack build --template nvidia --image-type conda
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llama stack run ./run.yaml \
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--port 5001 \
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--env NVIDIA_API_KEY=$NVIDIA_API_KEY
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```
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