feat: Add Google Vertex AI inference provider support

- Add new Vertex AI remote inference provider with litellm integration
- Support for Gemini models through Google Cloud Vertex AI platform
- Uses Google Cloud Application Default Credentials (ADC) for authentication
- Added VertexAI models: gemini-2.5-flash, gemini-2.5-pro, gemini-2.0-flash.
- Updated provider registry to include vertexai provider
- Updated starter template to support Vertex AI configuration
- Added comprehensive documentation and sample configuration

Signed-off-by: Eran Cohen <eranco@redhat.com>

llama_stack/providers/remote/inference/vertexai/models.py

@@ -0,0 +1,36 @@
+# 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 llama_stack.apis.models import ModelType
+from llama_stack.providers.utils.inference.model_registry import (
+    ProviderModelEntry,
+)
+
+# Vertex AI model IDs with vertex_ai/ prefix as required by litellm
+LLM_MODEL_IDS = [
+    "vertex_ai/gemini-2.0-flash",
+    "vertex_ai/gemini-2.5-flash",
+    "vertex_ai/gemini-2.5-pro",
+]
+
+SAFETY_MODELS_ENTRIES = list[ProviderModelEntry]()
+
+MODEL_ENTRIES = (
+    [ProviderModelEntry(provider_model_id=m) for m in LLM_MODEL_IDS]
+    + [
+        ProviderModelEntry(
+            provider_model_id="vertex_ai/text-embedding-004",
+            model_type=ModelType.embedding,
+            metadata={"embedding_dimension": 768, "context_length": 2048},
+        ),
+        ProviderModelEntry(
+            provider_model_id="vertex_ai/text-embedding-005",
+            model_type=ModelType.embedding,
+            metadata={"embedding_dimension": 768, "context_length": 2048},
+        ),
+    ]
+    + SAFETY_MODELS_ENTRIES
+)