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# What does this PR do? Adds custom model registration functionality to NVIDIAInferenceAdapter which let's the inference happen on: - post-training model - non-llama models in API Catalogue(behind https://integrate.api.nvidia.com and endpoints compatible with AyncOpenAI) ## Example Usage: ```python from llama_stack.apis.models import Model, ModelType from llama_stack.distribution.library_client import LlamaStackAsLibraryClient client = LlamaStackAsLibraryClient("nvidia") _ = client.initialize() client.models.register( model_id=model_name, model_type=ModelType.llm, provider_id="nvidia" ) response = client.inference.chat_completion( model_id=model_name, messages=[{"role":"system","content":"You are a helpful assistant."},{"role":"user","content":"Write a limerick about the wonders of GPU computing."}], ) ``` ## Test Plan ```bash pytest tests/unit/providers/nvidia/test_supervised_fine_tuning.py ========================================================== test session starts =========================================================== platform linux -- Python 3.10.0, pytest-8.3.5, pluggy-1.5.0 rootdir: /home/ubuntu/llama-stack configfile: pyproject.toml plugins: anyio-4.9.0 collected 6 items tests/unit/providers/nvidia/test_supervised_fine_tuning.py ...... [100%] ============================================================ warnings summary ============================================================ ../miniconda/envs/nvidia-1/lib/python3.10/site-packages/pydantic/fields.py:1076 /home/ubuntu/miniconda/envs/nvidia-1/lib/python3.10/site-packages/pydantic/fields.py:1076: PydanticDeprecatedSince20: Using extra keyword arguments on `Field` is deprecated and will be removed. Use `json_schema_extra` instead. (Extra keys: 'contentEncoding'). Deprecated in Pydantic V2.0 to be removed in V3.0. See Pydantic V2 Migration Guide at https://errors.pydantic.dev/2.11/migration/ warn( -- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html ====================================================== 6 passed, 1 warning in 1.51s ====================================================== ``` [//]: # (## Documentation) Updated Readme.md cc: @dglogo, @sumitb, @mattf
61 lines
2.3 KiB
Python
61 lines
2.3 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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import os
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from typing import Any, Dict, Optional
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from pydantic import BaseModel, Field, SecretStr
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from llama_stack.schema_utils import json_schema_type
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@json_schema_type
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class NVIDIAConfig(BaseModel):
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"""
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Configuration for the NVIDIA NIM inference endpoint.
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Attributes:
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url (str): A base url for accessing the NVIDIA NIM, e.g. http://localhost:8000
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api_key (str): The access key for the hosted NIM endpoints
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There are two ways to access NVIDIA NIMs -
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0. Hosted: Preview APIs hosted at https://integrate.api.nvidia.com
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1. Self-hosted: You can run NVIDIA NIMs on your own infrastructure
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By default the configuration is set to use the hosted APIs. This requires
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an API key which can be obtained from https://ngc.nvidia.com/.
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By default the configuration will attempt to read the NVIDIA_API_KEY environment
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variable to set the api_key. Please do not put your API key in code.
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If you are using a self-hosted NVIDIA NIM, you can set the url to the
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URL of your running NVIDIA NIM and do not need to set the api_key.
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"""
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url: str = Field(
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default_factory=lambda: os.getenv("NVIDIA_BASE_URL", "https://integrate.api.nvidia.com"),
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description="A base url for accessing the NVIDIA NIM",
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)
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api_key: Optional[SecretStr] = Field(
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default_factory=lambda: os.getenv("NVIDIA_API_KEY"),
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description="The NVIDIA API key, only needed of using the hosted service",
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)
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timeout: int = Field(
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default=60,
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description="Timeout for the HTTP requests",
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)
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append_api_version: bool = Field(
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default_factory=lambda: os.getenv("NVIDIA_APPEND_API_VERSION", "True").lower() != "false",
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description="When set to false, the API version will not be appended to the base_url. By default, it is true.",
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)
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@classmethod
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def sample_run_config(cls, **kwargs) -> Dict[str, Any]:
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return {
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"url": "${env.NVIDIA_BASE_URL:https://integrate.api.nvidia.com}",
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"api_key": "${env.NVIDIA_API_KEY:}",
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"append_api_version": "${env.NVIDIA_APPEND_API_VERSION:True}",
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}
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