From e3da87f739113432f4ca90f25c328e2320408dd7 Mon Sep 17 00:00:00 2001 From: Iana Date: Fri, 15 May 2026 18:55:38 +0100 Subject: [PATCH] fix(vertex_ai): route google/gemma-*-maas through partner-models OpenAI path MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Fixes #26083 vertex_ai/google/gemma-4-26b-a4b-it-maas previously fell through to the NON_GEMINI route. Per owtaylor's plan on #26083: add the google/gemma- prefix to PartnerModelPrefixes so is_vertex_partner_model picks it up and should_use_openai_handler routes it to the OpenAI-compatible /endpoints/openapi/chat/completions URL. No gemma-detection exclusion needed (the "gemma/" check uses a slash, which google/gemma-... doesn't match). No OpenAIGPTConfig subclass needed — works with the base handler. --- .../vertex_ai_partner_models/main.py | 3 + model_prices_and_context_window.json | 16 ++ .../vertex_ai/test_vertex_ai_common_utils.py | 258 ++++++++++++------ .../gemma/__init__.py | 0 .../test_vertex_ai_gemma_global_endpoint.py | 191 +++++++++++++ 5 files changed, 378 insertions(+), 90 deletions(-) create mode 100644 tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/gemma/__init__.py create mode 100644 tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/gemma/test_vertex_ai_gemma_global_endpoint.py diff --git a/litellm/llms/vertex_ai/vertex_ai_partner_models/main.py b/litellm/llms/vertex_ai/vertex_ai_partner_models/main.py index 123d925f7c1..26b6ea33760 100644 --- a/litellm/llms/vertex_ai/vertex_ai_partner_models/main.py +++ b/litellm/llms/vertex_ai/vertex_ai_partner_models/main.py @@ -41,6 +41,7 @@ class PartnerModelPrefixes(str, Enum): MINIMAX_PREFIX = "minimaxai/" MOONSHOT_PREFIX = "moonshotai/" ZAI_PREFIX = "zai-org/" + GEMMA_MAAS_PREFIX = "google/gemma-" class VertexAIPartnerModels(VertexBase): @@ -68,6 +69,7 @@ class VertexAIPartnerModels(VertexBase): or model.startswith(PartnerModelPrefixes.MINIMAX_PREFIX) or model.startswith(PartnerModelPrefixes.MOONSHOT_PREFIX) or model.startswith(PartnerModelPrefixes.ZAI_PREFIX) + or model.startswith(PartnerModelPrefixes.GEMMA_MAAS_PREFIX) ): return True return False @@ -82,6 +84,7 @@ class VertexAIPartnerModels(VertexBase): PartnerModelPrefixes.MINIMAX_PREFIX, PartnerModelPrefixes.MOONSHOT_PREFIX, PartnerModelPrefixes.ZAI_PREFIX, + PartnerModelPrefixes.GEMMA_MAAS_PREFIX, ] if any(provider in model for provider in OPENAI_LIKE_VERTEX_PROVIDERS): return True diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index c624736d6bf..978e1422921 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -31996,6 +31996,22 @@ "us-central1" ] }, + "vertex_ai/google/gemma-4-26b-a4b-it-maas": { + "input_cost_per_token": 1.5e-07, + "litellm_provider": "vertex_ai-language-models", + "max_input_tokens": 256000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 6e-07, + "source": "https://docs.cloud.google.com/vertex-ai/generative-ai/docs/maas/google/gemma-4-26b-a4b-it", + "supported_regions": [ + "global" + ], + "supports_function_calling": true, + "supports_response_schema": true, + "supports_tool_choice": true + }, "vertex_ai/openai/gpt-oss-120b-maas": { "input_cost_per_token": 1.5e-07, "litellm_provider": "vertex_ai-openai_models", diff --git a/tests/test_litellm/llms/vertex_ai/test_vertex_ai_common_utils.py b/tests/test_litellm/llms/vertex_ai/test_vertex_ai_common_utils.py index d483a81a349..a762917d0c0 100644 --- a/tests/test_litellm/llms/vertex_ai/test_vertex_ai_common_utils.py +++ b/tests/test_litellm/llms/vertex_ai/test_vertex_ai_common_utils.py @@ -440,7 +440,9 @@ def test_vertex_ai_complex_response_schema(): optional_params = {} v.apply_response_schema_transformation( - value=non_default_params["response_format"], optional_params=optional_params, model="gemini-1.5-pro-preview-0409" + value=non_default_params["response_format"], + optional_params=optional_params, + model="gemini-1.5-pro-preview-0409", ) # Assertions for the transformed schema @@ -558,7 +560,6 @@ def test_get_vertex_url_global_region(stream, expected_endpoint_suffix): assert url == expected_url - @pytest.mark.parametrize( "model_cost_entry, vertex_region, expected_region", [ @@ -571,9 +572,17 @@ def test_get_vertex_url_global_region(stream, expected_endpoint_suffix): # Model with supported_regions=["us-west2"], no user region -> use "us-west2" ({"supported_regions": ["us-west2"]}, None, "us-west2"), # Model with supported_regions=["us-west2", "us-central1"], user passes supported region -> respect it - ({"supported_regions": ["us-west2", "us-central1"]}, "us-central1", "us-central1"), + ( + {"supported_regions": ["us-west2", "us-central1"]}, + "us-central1", + "us-central1", + ), # Model with supported_regions=["us-west2", "us-central1"], user passes unsupported region -> override - ({"supported_regions": ["us-west2", "us-central1"]}, "europe-west1", "us-west2"), + ( + {"supported_regions": ["us-west2", "us-central1"]}, + "europe-west1", + "us-west2", + ), # No model_cost entry, no user region -> default us-central1 ({}, None, "us-central1"), # No model_cost entry, user specifies region -> use specified region @@ -656,11 +665,12 @@ def test_vertex_filter_format_uri(): assert "uri" not in json.dumps(new_parameters) + def test_convert_schema_types_type_array_conversion(): """ Test _convert_schema_types function handles type arrays and case conversion. - - This test verifies the fix for the issue where type arrays like ["string", "number"] + + This test verifies the fix for the issue where type arrays like ["string", "number"] would raise an exception in Vertex AI schema validation. Relevant issue: https://github.com/BerriAI/litellm/issues/14091 @@ -673,12 +683,12 @@ def test_convert_schema_types_type_array_conversion(): "properties": { "studio": { "type": ["string", "number"], - "description": "The studio ID or name" + "description": "The studio ID or name", } }, "required": ["studio"], "additionalProperties": False, - "$schema": "http://json-schema.org/draft-07/schema#" + "$schema": "http://json-schema.org/draft-07/schema#", } # Expected output: Vertex AI compatible schema with anyOf and uppercase types @@ -686,16 +696,13 @@ def test_convert_schema_types_type_array_conversion(): "type": "object", "properties": { "studio": { - "anyOf": [ - {"type": "string"}, - {"type": "number"} - ], - "description": "The studio ID or name" + "anyOf": [{"type": "string"}, {"type": "number"}], + "description": "The studio ID or name", } }, "required": ["studio"], "additionalProperties": False, - "$schema": "http://json-schema.org/draft-07/schema#" + "$schema": "http://json-schema.org/draft-07/schema#", } # Apply the transformation @@ -718,15 +725,17 @@ def test_convert_schema_types_type_array_conversion(): assert anyof_types[1]["type"] == "number" # 4. Other properties preserved - assert input_schema["properties"]["studio"]["description"] == "The studio ID or name" + assert ( + input_schema["properties"]["studio"]["description"] == "The studio ID or name" + ) assert input_schema["required"] == ["studio"] def test_fix_enum_empty_strings(): """ Test _fix_enum_empty_strings function replaces empty strings with None in enum arrays. - - This test verifies the fix for the issue where Gemini rejects tool definitions + + This test verifies the fix for the issue where Gemini rejects tool definitions with empty strings in enum values, causing API failures. Relevant issue: Gemini does not accept empty strings in enum values @@ -740,23 +749,23 @@ def test_fix_enum_empty_strings(): "user_agent_type": { "enum": ["", "desktop", "mobile", "tablet"], "type": "string", - "description": "Device type for user agent" + "description": "Device type for user agent", } }, - "required": ["user_agent_type"] + "required": ["user_agent_type"], } # Expected output: Empty strings replaced with None expected_output = { - "type": "object", + "type": "object", "properties": { "user_agent_type": { "enum": [None, "desktop", "mobile", "tablet"], "type": "string", - "description": "Device type for user agent" + "description": "Device type for user agent", } }, - "required": ["user_agent_type"] + "required": ["user_agent_type"], } # Apply the transformation @@ -859,7 +868,7 @@ def test_construct_target_url_with_version_prefix(): def test_fix_enum_types(): """ Test _fix_enum_types function removes enum fields when type is not string. - + This test verifies the fix for the issue where Gemini rejects cached content with function parameter enums on non-string types, causing API failures. @@ -874,38 +883,41 @@ def test_fix_enum_types(): "truncateMode": { "enum": ["auto", "none", "start", "end"], "type": "string", # This should keep the enum - "description": "How to truncate content" + "description": "How to truncate content", }, "maxLength": { "enum": [100, 200, 500], # This should be removed "type": "integer", - "description": "Maximum length" + "description": "Maximum length", }, "enabled": { "enum": [True, False], # This should be removed "type": "boolean", - "description": "Whether feature is enabled" + "description": "Whether feature is enabled", }, "nested": { "type": "object", "properties": { "innerEnum": { "enum": ["a", "b", "c"], # This should be kept - "type": "string" + "type": "string", }, "innerNonStringEnum": { "enum": [1, 2, 3], # This should be removed - "type": "integer" - } - } + "type": "integer", + }, + }, }, "anyOfField": { "anyOf": [ - {"type": "string", "enum": ["option1", "option2"]}, # This should be kept - {"type": "integer", "enum": [1, 2, 3]} # This should be removed + { + "type": "string", + "enum": ["option1", "option2"], + }, # This should be kept + {"type": "integer", "enum": [1, 2, 3]}, # This should be removed ] - } - } + }, + }, } # Expected output: Non-string enums removed, string enums kept @@ -919,31 +931,32 @@ def test_fix_enum_types(): }, "maxLength": { # enum removed "type": "integer", - "description": "Maximum length" + "description": "Maximum length", }, "enabled": { # enum removed "type": "boolean", - "description": "Whether feature is enabled" + "description": "Whether feature is enabled", }, "nested": { "type": "object", "properties": { "innerEnum": { "enum": ["a", "b", "c"], # Kept - string type - "type": "string" + "type": "string", }, - "innerNonStringEnum": { # enum removed - "type": "integer" - } - } + "innerNonStringEnum": {"type": "integer"}, # enum removed + }, }, "anyOfField": { "anyOf": [ - {"type": "string", "enum": ["option1", "option2"]}, # Kept - has string type - {"type": "integer"} # enum removed + { + "type": "string", + "enum": ["option1", "option2"], + }, # Kept - has string type + {"type": "integer"}, # enum removed ] - } - } + }, + }, } # Apply the transformation @@ -955,15 +968,27 @@ def test_fix_enum_types(): # Verify specific transformations: # 1. String enums are preserved assert "enum" in input_schema["properties"]["truncateMode"] - assert input_schema["properties"]["truncateMode"]["enum"] == ["auto", "none", "start", "end"] - + assert input_schema["properties"]["truncateMode"]["enum"] == [ + "auto", + "none", + "start", + "end", + ] + assert "enum" in input_schema["properties"]["nested"]["properties"]["innerEnum"] - assert input_schema["properties"]["nested"]["properties"]["innerEnum"]["enum"] == ["a", "b", "c"] + assert input_schema["properties"]["nested"]["properties"]["innerEnum"]["enum"] == [ + "a", + "b", + "c", + ] # 2. Non-string enums are removed assert "enum" not in input_schema["properties"]["maxLength"] assert "enum" not in input_schema["properties"]["enabled"] - assert "enum" not in input_schema["properties"]["nested"]["properties"]["innerNonStringEnum"] + assert ( + "enum" + not in input_schema["properties"]["nested"]["properties"]["innerNonStringEnum"] + ) # 3. anyOf with string type keeps enum, non-string removes it assert "enum" in input_schema["properties"]["anyOfField"]["anyOf"][0] @@ -1003,8 +1028,6 @@ def test_get_token_url(): print("url=", url) - - should_use_v1beta1_features = vertex_llm.is_using_v1beta1_features( optional_params={"temperature": 0.1} ) @@ -1210,9 +1233,7 @@ def test_vertex_ai_minimax_uses_openai_handler(): VertexAIPartnerModels, ) - assert VertexAIPartnerModels.should_use_openai_handler( - "minimaxai/minimax-m2-maas" - ) + assert VertexAIPartnerModels.should_use_openai_handler("minimaxai/minimax-m2-maas") def test_vertex_ai_moonshot_uses_openai_handler(): @@ -1236,9 +1257,7 @@ def test_vertex_ai_zai_uses_openai_handler(): VertexAIPartnerModels, ) - assert VertexAIPartnerModels.should_use_openai_handler( - "zai-org/glm-4.7-maas" - ) + assert VertexAIPartnerModels.should_use_openai_handler("zai-org/glm-4.7-maas") def test_vertex_ai_zai_is_partner_model(): @@ -1252,17 +1271,74 @@ def test_vertex_ai_zai_is_partner_model(): assert VertexAIPartnerModels.is_vertex_partner_model("zai-org/glm-4.7-maas") +def test_vertex_ai_gemma_maas_is_partner_model(): + """ + Ensure Gemma MaaS models are detected as Vertex AI partner models so they + route through the OpenAI-compatible /endpoints/openapi path (not the + legacy non-gemini path or the vertex_ai/gemma/ predict-endpoint handler). + """ + from litellm.llms.vertex_ai.vertex_ai_partner_models.main import ( + VertexAIPartnerModels, + ) + + assert VertexAIPartnerModels.is_vertex_partner_model( + "google/gemma-4-26b-a4b-it-maas" + ) + + +def test_vertex_ai_gemma_maas_uses_openai_handler(): + """ + Ensure Gemma MaaS partner models re-use the OpenAI-format handler. + """ + from litellm.llms.vertex_ai.vertex_ai_partner_models.main import ( + VertexAIPartnerModels, + ) + + assert VertexAIPartnerModels.should_use_openai_handler( + "google/gemma-4-26b-a4b-it-maas" + ) + + +def test_vertex_ai_gemma_maas_routes_to_partner_models(): + """ + Regression guard for owtaylor's worry that Gemma MaaS could be misrouted as + a gemma model. get_vertex_ai_model_route must return PARTNER_MODELS, never + GEMMA, MODEL_GARDEN, or NON_GEMINI. + """ + from litellm.llms.vertex_ai.common_utils import ( + VertexAIModelRoute, + get_vertex_ai_model_route, + ) + + route = get_vertex_ai_model_route("google/gemma-4-26b-a4b-it-maas") + assert route == VertexAIModelRoute.PARTNER_MODELS + + +def test_vertex_ai_google_gemini_not_detected_as_gemma_maas(): + """ + Negative: adding the "google/gemma-" prefix must not widen detection to + other google/* models like google/gemini-* (which should keep flowing + through the gemini route, not partner_models). + """ + from litellm.llms.vertex_ai.vertex_ai_partner_models.main import ( + VertexAIPartnerModels, + ) + + assert not VertexAIPartnerModels.is_vertex_partner_model("google/gemini-1.5-pro") + assert not VertexAIPartnerModels.should_use_openai_handler("google/gemini-1.5-pro") + + def test_build_vertex_schema_empty_properties(): """ Test _build_vertex_schema handles empty properties objects correctly. - - This test verifies the fix for the issue where Gemini rejects schemas + + This test verifies the fix for the issue where Gemini rejects schemas with empty properties objects like {"properties": {}, "type": "object"}. - + Error from Gemini: "GenerateContentRequest.generation_config.response_schema - .properties[\"action\"].items.any_of[0].properties[\"go_back\"].properties: + .properties[\"action\"].items.any_of[0].properties[\"go_back\"].properties: should be non-empty for OBJECT type" - + The fix removes empty properties objects and their associated type/required fields. """ from litellm.llms.vertex_ai.common_utils import _build_vertex_schema @@ -1281,20 +1357,20 @@ def test_build_vertex_schema_empty_properties(): "type": "object", "additionalProperties": False, "description": "Go back", - "required": [] + "required": [], } }, "required": ["go_back"], "type": "object", - "additionalProperties": False + "additionalProperties": False, } ] }, - "type": "array" + "type": "array", } }, "type": "object", - "additionalProperties": False + "additionalProperties": False, } # Apply the transformation @@ -1302,24 +1378,36 @@ def test_build_vertex_schema_empty_properties(): # Verify the transformation removed empty properties # Navigate to the go_back schema - go_back_schema = result["properties"]["action"]["items"]["anyOf"][0]["properties"]["go_back"] - + go_back_schema = result["properties"]["action"]["items"]["anyOf"][0]["properties"][ + "go_back" + ] + # Verify empty properties was removed assert "properties" not in go_back_schema, "Empty properties should be removed" - + # Verify type is kept as object (Gemini requires type: object even without properties) - assert go_back_schema.get("type") == "object", "Type should be kept as object when properties is empty" - + assert ( + go_back_schema.get("type") == "object" + ), "Type should be kept as object when properties is empty" + # Verify required was also removed - assert "required" not in go_back_schema, "Required should be removed when properties is empty" - + assert ( + "required" not in go_back_schema + ), "Required should be removed when properties is empty" + # Verify description is preserved - assert go_back_schema.get("description") == "Go back", "Description should be preserved" - + assert ( + go_back_schema.get("description") == "Go back" + ), "Description should be preserved" + # Verify parent schema still has proper structure parent_schema = result["properties"]["action"]["items"]["anyOf"][0] - assert parent_schema["type"] == "object", "Parent schema should still have object type" - assert "go_back" in parent_schema["properties"], "go_back should still be in parent properties" + assert ( + parent_schema["type"] == "object" + ), "Parent schema should still have object type" + assert ( + "go_back" in parent_schema["properties"] + ), "go_back should still be in parent properties" def test_add_object_type_schema_with_no_properties_and_no_type(): @@ -1330,9 +1418,7 @@ def test_add_object_type_schema_with_no_properties_and_no_type(): from litellm.llms.vertex_ai.common_utils import add_object_type # Input: Schema with no properties and no type (the problematic case) - input_schema = { - "$schema": "https://json-schema.org/draft/2020-12/schema" - } + input_schema = {"$schema": "https://json-schema.org/draft/2020-12/schema"} # Apply the transformation add_object_type(input_schema) @@ -1351,10 +1437,7 @@ def test_add_object_type_does_not_override_existing_type(): from litellm.llms.vertex_ai.common_utils import add_object_type # Input: Schema with existing type - input_schema = { - "type": "string", - "description": "A string field" - } + input_schema = {"type": "string", "description": "A string field"} # Apply the transformation add_object_type(input_schema) @@ -1370,12 +1453,7 @@ def test_add_object_type_does_not_add_type_when_anyof_present(): from litellm.llms.vertex_ai.common_utils import add_object_type # Input: Schema with anyOf but no type - input_schema = { - "anyOf": [ - {"type": "string"}, - {"type": "null"} - ] - } + input_schema = {"anyOf": [{"type": "string"}, {"type": "null"}]} # Apply the transformation add_object_type(input_schema) diff --git a/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/gemma/__init__.py b/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/gemma/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/gemma/test_vertex_ai_gemma_global_endpoint.py b/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/gemma/test_vertex_ai_gemma_global_endpoint.py new file mode 100644 index 00000000000..849689daee0 --- /dev/null +++ b/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/gemma/test_vertex_ai_gemma_global_endpoint.py @@ -0,0 +1,191 @@ +""" +Tests for Vertex AI Gemma MaaS models that route through the partner-models +OpenAI-compatible path (https://aiplatform.googleapis.com/.../endpoints/openapi). + +These tests verify that: +1. The correct global URL is constructed (https://aiplatform.googleapis.com) +2. get_vertex_region resolves to "global" when model_cost says so +3. acompletion() goes through the OpenAI-compatible handler and hits + /endpoints/openapi/chat/completions +""" + +import os +import sys +from unittest.mock import AsyncMock, MagicMock, patch + +import pytest + +sys.path.insert( + 0, os.path.abspath("../../../../../..") +) # Adds the parent directory to the system path + +import litellm +from litellm.llms.vertex_ai.vertex_llm_base import VertexBase +from litellm.types.llms.vertex_ai import VertexPartnerProvider + + +@pytest.fixture(autouse=True) +def clean_vertex_env(): + """Clear Google/Vertex AI environment variables before each test to prevent test isolation issues.""" + saved_env = {} + env_vars_to_clear = [ + "GOOGLE_APPLICATION_CREDENTIALS", + "GOOGLE_CLOUD_PROJECT", + "VERTEXAI_PROJECT", + "VERTEX_PROJECT", + "VERTEX_LOCATION", + "VERTEX_AI_PROJECT", + ] + for var in env_vars_to_clear: + if var in os.environ: + saved_env[var] = os.environ[var] + del os.environ[var] + + yield + + for var, value in saved_env.items(): + os.environ[var] = value + + +class TestVertexBaseGetVertexRegionGemma: + """Test the get_vertex_region method for Gemma MaaS via model_cost lookup.""" + + def test_global_model_no_user_region_returns_global(self): + vertex_base = VertexBase() + + with patch.dict( + litellm.model_cost, + { + "vertex_ai/google/gemma-4-26b-a4b-it-maas": { + "supported_regions": ["global"] + } + }, + clear=False, + ): + result = vertex_base.get_vertex_region( + vertex_region=None, + model="google/gemma-4-26b-a4b-it-maas", + ) + assert result == "global" + + def test_global_model_with_unsupported_user_region_overrides(self): + vertex_base = VertexBase() + + with patch.dict( + litellm.model_cost, + { + "vertex_ai/google/gemma-4-26b-a4b-it-maas": { + "supported_regions": ["global"] + } + }, + clear=False, + ): + result = vertex_base.get_vertex_region( + vertex_region="us-central1", + model="google/gemma-4-26b-a4b-it-maas", + ) + assert result == "global" + + +class TestCreateVertexURLGemma: + """Test that create_vertex_url produces the expected OpenAI-compatible URL.""" + + def test_global_location_url_format(self): + url = VertexBase.create_vertex_url( + vertex_location="global", + vertex_project="test-project", + partner=VertexPartnerProvider.llama, + stream=False, + model="google/gemma-4-26b-a4b-it-maas", + ) + + assert url.startswith("https://aiplatform.googleapis.com") + assert "global-aiplatform.googleapis.com" not in url + assert "/locations/global/" in url + assert url.endswith("/endpoints/openapi/chat/completions") + + def test_regional_location_url_format(self): + url = VertexBase.create_vertex_url( + vertex_location="us-central1", + vertex_project="test-project", + partner=VertexPartnerProvider.llama, + stream=False, + model="google/gemma-4-26b-a4b-it-maas", + ) + + assert url.startswith("https://us-central1-aiplatform.googleapis.com") + assert "/locations/us-central1/" in url + assert url.endswith("/endpoints/openapi/chat/completions") + + +@pytest.mark.asyncio +async def test_vertex_ai_gemma_global_endpoint_url(): + """ + End-to-end: acompletion on vertex_ai/google/gemma-4-26b-a4b-it-maas should + POST to the global endpoints/openapi/chat/completions URL. + """ + mock_response = MagicMock() + mock_response.status_code = 200 + mock_response.headers = {} + mock_response.json.return_value = { + "id": "chatcmpl-gemma-test", + "object": "chat.completion", + "created": 1234567890, + "model": "google/gemma-4-26b-a4b-it-maas", + "choices": [ + { + "index": 0, + "message": { + "role": "assistant", + "content": "Hello! How can I help you today?", + }, + "finish_reason": "stop", + } + ], + "usage": {"prompt_tokens": 10, "completion_tokens": 8, "total_tokens": 18}, + } + + mock_vertexai = MagicMock() + mock_vertexai.preview = MagicMock() + + with ( + patch( + "litellm.llms.custom_httpx.http_handler.AsyncHTTPHandler" + ) as mock_http_handler, + patch( + "litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini.VertexLLM._ensure_access_token", + return_value=("fake-token", "test-project"), + ), + patch.dict( + "sys.modules", + {"vertexai": mock_vertexai, "vertexai.preview": mock_vertexai.preview}, + ), + patch.dict( + litellm.model_cost, + { + "vertex_ai/google/gemma-4-26b-a4b-it-maas": { + "supported_regions": ["global"] + } + }, + clear=False, + ), + ): + mock_http_handler.return_value.post = AsyncMock(return_value=mock_response) + + response = await litellm.acompletion( + model="vertex_ai/google/gemma-4-26b-a4b-it-maas", + messages=[{"role": "user", "content": "Hello"}], + vertex_ai_project="test-project", + ) + + mock_http_handler.return_value.post.assert_called_once() + + call_args = mock_http_handler.return_value.post.call_args + called_url = call_args.kwargs["url"] + + assert called_url.startswith("https://aiplatform.googleapis.com") + assert "global-aiplatform.googleapis.com" not in called_url + assert "/locations/global/" in called_url + assert "/endpoints/openapi/chat/completions" in called_url + + assert response.model == "google/gemma-4-26b-a4b-it-maas"