forked from phoenix-oss/llama-stack-mirror
b76bef169c
# What does this PR do? - fixes to nvidia inference provider to account for strategy update - update nvidia templates ## Test Plan ``` llama stack run ./llama_stack/templates/nvidia/run.yaml --port 5000 LLAMA_STACK_BASE_URL="http://localhost:5000" pytest -v tests/client-sdk/inference/test_inference.py --html=report.html --self-contained-html ``` <img width="1288" alt="image" src="https://github.com/user-attachments/assets/d20f9aea-525e-47de-a5be-586e022e0d55" /> **NOTE** - vision inference broken - tool calling broken - /completion broken cc @mattf @cdgamarose-nv for improving NVIDIA inference adapter ## Sources Please link relevant resources if necessary. ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Ran pre-commit to handle lint / formatting issues. - [ ] Read the [contributor guideline](https://github.com/meta-llama/llama-stack/blob/main/CONTRIBUTING.md), Pull Request section? - [ ] Updated relevant documentation. - [ ] Wrote necessary unit or integration tests.
80 lines
2.6 KiB
Python
80 lines
2.6 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_models.sku_list import all_registered_models
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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.providers.remote.inference.nvidia.nvidia import _MODEL_ALIASES
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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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core_model_to_hf_repo = {
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m.descriptor(): m.huggingface_repo for m in all_registered_models()
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}
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default_models = [
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ModelInput(
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model_id=core_model_to_hf_repo[m.llama_model],
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provider_model_id=m.provider_model_id,
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provider_id="nvidia",
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)
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for m in _MODEL_ALIASES
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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=default_models,
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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=default_models,
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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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