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https://github.com/meta-llama/llama-stack.git
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b9961c8735
OpenAIMixin expects to use an API key and creates its own AsyncOpenAI client. So our code now authenticate with the Google service, retrieves a token and pass it to the OpenAI client. Falls back to an empty string if credentials can't be obtained (letting LiteLLM handle ADC directly). Signed-off-by: Sébastien Han <seb@redhat.com>
77 lines
3.1 KiB
Python
77 lines
3.1 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 typing import Any
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import google.auth.transport.requests
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from google.auth import default
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from llama_stack.apis.inference import ChatCompletionRequest
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from llama_stack.providers.utils.inference.litellm_openai_mixin import (
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LiteLLMOpenAIMixin,
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)
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from llama_stack.providers.utils.inference.openai_mixin import OpenAIMixin
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from .config import VertexAIConfig
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from .models import MODEL_ENTRIES
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class VertexAIInferenceAdapter(OpenAIMixin, LiteLLMOpenAIMixin):
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def __init__(self, config: VertexAIConfig) -> None:
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LiteLLMOpenAIMixin.__init__(
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self,
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MODEL_ENTRIES,
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litellm_provider_name="vertex_ai",
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api_key_from_config=None, # Vertex AI uses ADC, not API keys
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provider_data_api_key_field="vertex_project", # Use project for validation
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)
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self.config = config
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def get_api_key(self) -> str:
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"""
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Get an access token for Vertex AI using Application Default Credentials.
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Vertex AI uses ADC instead of API keys. This method obtains an access token
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from the default credentials and returns it for use with the OpenAI-compatible client.
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"""
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try:
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# Get default credentials - will read from GOOGLE_APPLICATION_CREDENTIALS
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credentials, _ = default(scopes=["https://www.googleapis.com/auth/cloud-platform"])
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credentials.refresh(google.auth.transport.requests.Request())
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return credentials.token
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except Exception:
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# If we can't get credentials, return empty string to let LiteLLM handle it
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# This allows the LiteLLM mixin to work with ADC directly
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return ""
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def get_base_url(self) -> str:
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"""
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Get the Vertex AI OpenAI-compatible API base URL.
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Returns the Vertex AI OpenAI-compatible endpoint URL.
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Source: https://cloud.google.com/vertex-ai/generative-ai/docs/start/openai
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"""
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return f"https://{self.config.location}-aiplatform.googleapis.com/v1/projects/{self.config.project}/locations/{self.config.location}/endpoints/openapi"
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async def _get_params(self, request: ChatCompletionRequest) -> dict[str, Any]:
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# Get base parameters from parent
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params = await super()._get_params(request)
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# Add Vertex AI specific parameters
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provider_data = self.get_request_provider_data()
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if provider_data:
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if getattr(provider_data, "vertex_project", None):
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params["vertex_project"] = provider_data.vertex_project
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if getattr(provider_data, "vertex_location", None):
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params["vertex_location"] = provider_data.vertex_location
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else:
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params["vertex_project"] = self.config.project
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params["vertex_location"] = self.config.location
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# Remove api_key since Vertex AI uses ADC
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params.pop("api_key", None)
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return params
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