diff --git a/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py b/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py index d113b2b4f6b..b4712fd376b 100644 --- a/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py +++ b/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py @@ -124,6 +124,12 @@ def _unsupported_reasoning_effort(reasoning_effort: str) -> UnsupportedParamsErr ) +def _served_model_name(model_version: object) -> str | None: + if not isinstance(model_version, str) or not model_version: + return None + return model_version.split("@", 1)[0] + + class VertexAIBaseConfig: def get_mapped_special_auth_params(self) -> dict: """ @@ -1951,6 +1957,7 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig): def _check_prompt_level_content_filter( processed_chunk: GenerateContentResponseBody, response_id: str | None, + model: str | None = None, ) -> Optional["ModelResponseStream"]: """ Check if prompt is blocked due to content filtering at the prompt level. @@ -1990,7 +1997,7 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig): enhancements=None, ) - model_response: Final = ModelResponseStream(choices=[choice], id=response_id) + model_response: Final = ModelResponseStream(choices=[choice], id=response_id, model=model) return model_response return None @@ -2434,7 +2441,8 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig): completion_response = GenerateContentResponseBody(**completion_response) ## GET MODEL ## - model_response.model = model + served: Final = _served_model_name(completion_response.get("modelVersion")) + model_response.model = served if served is not None else model ## CHECK IF RESPONSE FLAGGED if "promptFeedback" in completion_response and "blockReason" in completion_response["promptFeedback"]: @@ -3264,12 +3272,18 @@ class ModelResponseIterator: processed_chunk: Final = GenerateContentResponseBody(**chunk) response_id: Final = processed_chunk.get("responseId") - model_response = ModelResponseStream(choices=[], id=response_id) + served: Final = _served_model_name(processed_chunk.get("modelVersion")) + model_response = ModelResponseStream( + choices=[], + id=response_id, + model=served, + ) # Check if prompt is blocked due to content filtering blocked_response: Final = VertexGeminiConfig._check_prompt_level_content_filter( processed_chunk=processed_chunk, response_id=response_id, + model=served, ) if blocked_response is not None: model_response = blocked_response diff --git a/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_and_google_ai_studio_gemini.py b/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_and_google_ai_studio_gemini.py index 101f6e6fa5d..001105fc53d 100644 --- a/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_and_google_ai_studio_gemini.py +++ b/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_and_google_ai_studio_gemini.py @@ -5836,3 +5836,126 @@ def test_supported_reasoning_efforts_still_map(model): drop_params=False, ) assert "thinkingConfig" in result + + +def _generate_content_body() -> dict: + return { + "candidates": [ + { + "content": {"role": "model", "parts": [{"text": "hi"}]}, + "finishReason": "STOP", + "index": 0, + } + ], + "usageMetadata": { + "promptTokenCount": 5, + "candidatesTokenCount": 7, + "totalTokenCount": 12, + }, + } + + +def test_generate_content_transform_uses_reported_model_version(): + """The served modelVersion must win over the requested name so downstream + pricing sees what actually ran.""" + import httpx + + body = {**_generate_content_body(), "modelVersion": "gemini-x-served"} + response: Final = VertexGeminiConfig()._transform_google_generate_content_to_openai_model_response( + completion_response=body, + model_response=ModelResponse(), + model="gemini-x", + logging_obj=MagicMock(), + raw_response=httpx.Response(200, headers={}), + ) + + assert response.model == "gemini-x-served" + + +def test_generate_content_transform_falls_back_to_requested_model(): + import httpx + + response: Final = VertexGeminiConfig()._transform_google_generate_content_to_openai_model_response( + completion_response=_generate_content_body(), + model_response=ModelResponse(), + model="gemini-x", + logging_obj=MagicMock(), + raw_response=httpx.Response(200, headers={}), + ) + + assert response.model == "gemini-x" + + +def test_streaming_chunk_carries_model_version(): + from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import ( + ModelResponseIterator, + ) + + chunk = {**_generate_content_body(), "modelVersion": "gemini-x-served"} + iterator: Final = ModelResponseIterator(streaming_response=[], sync_stream=True, logging_obj=MagicMock()) + streaming_chunk: Final = iterator.chunk_parser(chunk) + + assert streaming_chunk.model == "gemini-x-served" + + +def test_served_model_version_reaches_assembled_stream_through_custom_stream_wrapper(): + from litellm.litellm_core_utils.streaming_handler import CustomStreamWrapper + from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import ( + ModelResponseIterator, + ) + + served_model: Final = "gemini-3.8-flash-001" + iterator: Final = ModelResponseIterator( + streaming_response=iter( + [json.dumps({**_generate_content_body(), "modelVersion": served_model}) for _ in range(3)] + ), + sync_stream=True, + logging_obj=MagicMock(), + ) + wrapper: Final = CustomStreamWrapper( + completion_stream=iter(iterator), + model="gemini/gemini-3.8-flash", + custom_llm_provider="gemini", + logging_obj=MagicMock(), + ) + + chunks: Final = list(wrapper) + + assert len(chunks) >= 3 + for chunk in chunks[:-1]: + assert chunk._hidden_params["provider_response_model"] == served_model + assembled: Final = litellm.stream_chunk_builder(chunks=list(chunks), messages=[{"role": "user", "content": "hi"}]) + assert assembled._hidden_params["provider_response_model"] == served_model + + +def test_generate_content_transform_strips_version_suffix_from_model_version(): + import httpx + + body: Final = {**_generate_content_body(), "modelVersion": "gemini-3.8-flash-001@default"} + response: Final = VertexGeminiConfig()._transform_google_generate_content_to_openai_model_response( + completion_response=body, + model_response=ModelResponse(), + model="gemini-3.8-flash", + logging_obj=MagicMock(), + raw_response=httpx.Response(200, headers={}), + ) + + assert response.model == "gemini-3.8-flash-001" + + +def test_prompt_blocked_chunk_keeps_served_model_version(): + from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import ( + ModelResponseIterator, + ) + + chunk: Final = { + "promptFeedback": {"blockReason": "SAFETY", "blockReasonMessage": "prompt was blocked"}, + "modelVersion": "gemini-3.8-flash-001", + "responseId": "resp-1", + } + iterator: Final = ModelResponseIterator(streaming_response=[], sync_stream=True, logging_obj=MagicMock()) + + streaming_chunk: Final = iterator.chunk_parser(chunk) + + assert streaming_chunk.model == "gemini-3.8-flash-001" + assert streaming_chunk.choices[0].finish_reason == "content_filter"