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https://github.com/meta-llama/llama-stack.git
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6143b9b0c3
- RemoteInferenceProviderConfig now has auth_credential: SecretStr - the default alias is api_key (most common name) - some providers override to use api_token (RunPod, vLLM, Databricks) - some providers exclude it (Ollama, TGI, Vertex AI)
48 lines
1.4 KiB
Python
48 lines
1.4 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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from pydantic import BaseModel, Field, SecretStr
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from llama_stack.providers.utils.inference.model_registry import RemoteInferenceProviderConfig
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from llama_stack.schema_utils import json_schema_type
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class VertexAIProviderDataValidator(BaseModel):
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vertex_project: str | None = Field(
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default=None,
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description="Google Cloud project ID for Vertex AI",
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)
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vertex_location: str | None = Field(
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default=None,
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description="Google Cloud location for Vertex AI (e.g., us-central1)",
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)
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@json_schema_type
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class VertexAIConfig(RemoteInferenceProviderConfig):
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auth_credential: SecretStr | None = Field(default=None, exclude=True)
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project: str = Field(
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description="Google Cloud project ID for Vertex AI",
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)
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location: str = Field(
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default="us-central1",
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description="Google Cloud location for Vertex AI",
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)
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@classmethod
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def sample_run_config(
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cls,
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project: str = "${env.VERTEX_AI_PROJECT:=}",
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location: str = "${env.VERTEX_AI_LOCATION:=us-central1}",
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**kwargs,
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) -> dict[str, Any]:
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return {
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"project": project,
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"location": location,
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}
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