llama-stack-mirror/llama_stack/providers/remote/inference/vertexai/vertexai.py
Matthew Farrellee b67aef2fc4
feat: add static embedding metadata to dynamic model listings for providers using OpenAIMixin (#3547)
# What does this PR do?

- remove auto-download of ollama embedding models
- add embedding model metadata to dynamic listing w/ unit test
- add support and tests for allowed_models
- removed inference provider models.py files where dynamic listing is
enabled
- store embedding metadata in embedding_model_metadata field on
inference providers
- make model_entries optional on ModelRegistryHelper and
LiteLLMOpenAIMixin
- make OpenAIMixin a ModelRegistryHelper
- skip base64 embedding test for remote::ollama, always returns floats
- only use OpenAI client for ollama model listing
- remove unused build_model_entry function
- remove unused get_huggingface_repo function


## Test Plan

ci w/ new tests
2025-09-25 17:17:00 -04:00

75 lines
3 KiB
Python

# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
from typing import Any
import google.auth.transport.requests
from google.auth import default
from llama_stack.apis.inference import ChatCompletionRequest
from llama_stack.providers.utils.inference.litellm_openai_mixin import (
LiteLLMOpenAIMixin,
)
from llama_stack.providers.utils.inference.openai_mixin import OpenAIMixin
from .config import VertexAIConfig
class VertexAIInferenceAdapter(OpenAIMixin, LiteLLMOpenAIMixin):
def __init__(self, config: VertexAIConfig) -> None:
LiteLLMOpenAIMixin.__init__(
self,
litellm_provider_name="vertex_ai",
api_key_from_config=None, # Vertex AI uses ADC, not API keys
provider_data_api_key_field="vertex_project", # Use project for validation
)
self.config = config
def get_api_key(self) -> str:
"""
Get an access token for Vertex AI using Application Default Credentials.
Vertex AI uses ADC instead of API keys. This method obtains an access token
from the default credentials and returns it for use with the OpenAI-compatible client.
"""
try:
# Get default credentials - will read from GOOGLE_APPLICATION_CREDENTIALS
credentials, _ = default(scopes=["https://www.googleapis.com/auth/cloud-platform"])
credentials.refresh(google.auth.transport.requests.Request())
return str(credentials.token)
except Exception:
# If we can't get credentials, return empty string to let LiteLLM handle it
# This allows the LiteLLM mixin to work with ADC directly
return ""
def get_base_url(self) -> str:
"""
Get the Vertex AI OpenAI-compatible API base URL.
Returns the Vertex AI OpenAI-compatible endpoint URL.
Source: https://cloud.google.com/vertex-ai/generative-ai/docs/start/openai
"""
return f"https://{self.config.location}-aiplatform.googleapis.com/v1/projects/{self.config.project}/locations/{self.config.location}/endpoints/openapi"
async def _get_params(self, request: ChatCompletionRequest) -> dict[str, Any]:
# Get base parameters from parent
params = await super()._get_params(request)
# Add Vertex AI specific parameters
provider_data = self.get_request_provider_data()
if provider_data:
if getattr(provider_data, "vertex_project", None):
params["vertex_project"] = provider_data.vertex_project
if getattr(provider_data, "vertex_location", None):
params["vertex_location"] = provider_data.vertex_location
else:
params["vertex_project"] = self.config.project
params["vertex_location"] = self.config.location
# Remove api_key since Vertex AI uses ADC
params.pop("api_key", None)
return params