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# 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>
70 lines
2.2 KiB
Python
70 lines
2.2 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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from pathlib import Path
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from llama_stack.distribution.datatypes import ModelInput, Provider
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from llama_stack.providers.remote.inference.nvidia import NVIDIAConfig
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from llama_stack.templates.template import DistributionTemplate, RunConfigSettings
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def get_distribution_template() -> DistributionTemplate:
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providers = {
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"inference": ["remote::nvidia"],
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"memory": ["inline::faiss"],
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"safety": ["inline::llama-guard"],
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"agents": ["inline::meta-reference"],
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"telemetry": ["inline::meta-reference"],
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"eval": ["inline::meta-reference"],
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"datasetio": ["remote::huggingface", "inline::localfs"],
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"scoring": ["inline::basic", "inline::llm-as-judge", "inline::braintrust"],
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"tool_runtime": [
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"remote::brave-search",
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"remote::tavily-search",
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"inline::code-interpreter",
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"inline::memory-runtime",
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],
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}
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inference_provider = Provider(
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provider_id="nvidia",
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provider_type="remote::nvidia",
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config=NVIDIAConfig.sample_run_config(),
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)
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inference_model = ModelInput(
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model_id="${env.INFERENCE_MODEL}",
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provider_id="nvidia",
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)
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return DistributionTemplate(
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name="nvidia",
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distro_type="remote_hosted",
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description="Use NVIDIA NIM for running LLM inference",
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docker_image=None,
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template_path=Path(__file__).parent / "doc_template.md",
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providers=providers,
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default_models=[inference_model],
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run_configs={
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"run.yaml": RunConfigSettings(
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provider_overrides={
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"inference": [inference_provider],
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},
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default_models=[inference_model],
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),
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},
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run_config_env_vars={
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"LLAMASTACK_PORT": (
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"5001",
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"Port for the Llama Stack distribution server",
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),
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"NVIDIA_API_KEY": (
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"",
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"NVIDIA API Key",
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),
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},
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)
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