diff --git a/litellm/integrations/rubrik.py b/litellm/integrations/rubrik.py index 4a6258acf2c..a988c0b3604 100644 --- a/litellm/integrations/rubrik.py +++ b/litellm/integrations/rubrik.py @@ -319,12 +319,8 @@ class RubrikLogger(CustomGuardrail, CustomBatchLogger): "content": system_prompt_msg_list, } if isinstance(standard_logging_payload["messages"], list): - standard_logging_payload["messages"].insert( - 0, system_scaffold - ) - elif isinstance( - standard_logging_payload["messages"], (dict, str) - ): + standard_logging_payload["messages"].insert(0, system_scaffold) + elif isinstance(standard_logging_payload["messages"], (dict, str)): standard_logging_payload["messages"] = [ system_scaffold, standard_logging_payload["messages"], @@ -354,14 +350,10 @@ class RubrikLogger(CustomGuardrail, CustomBatchLogger): exc_info=True, ) - async def async_log_success_event( - self, kwargs, response_obj, start_time, end_time - ): + async def async_log_success_event(self, kwargs, response_obj, start_time, end_time): await self._enqueue_log_event(kwargs, "success") - async def async_log_failure_event( - self, kwargs, response_obj, start_time, end_time - ): + async def async_log_failure_event(self, kwargs, response_obj, start_time, end_time): await self._enqueue_log_event(kwargs, "failure") # -- Batch logging --------------------------------------------------------- diff --git a/litellm/llms/bedrock/chat/invoke_transformations/anthropic_claude3_transformation.py b/litellm/llms/bedrock/chat/invoke_transformations/anthropic_claude3_transformation.py index d6c5aacc35d..9e8467fe394 100644 --- a/litellm/llms/bedrock/chat/invoke_transformations/anthropic_claude3_transformation.py +++ b/litellm/llms/bedrock/chat/invoke_transformations/anthropic_claude3_transformation.py @@ -170,7 +170,9 @@ class AmazonAnthropicClaudeConfig(AmazonInvokeConfig, AnthropicConfig): anthropic_request.pop("model", None) anthropic_request.pop("stream", None) anthropic_request.pop("output_format", None) - if not _supports_factory(model=model, custom_llm_provider=None, key="supports_output_config"): + if not _supports_factory( + model=model, custom_llm_provider=None, key="supports_output_config" + ): anthropic_request.pop("output_config", None) if "anthropic_version" not in anthropic_request: anthropic_request["anthropic_version"] = self.anthropic_version diff --git a/litellm/llms/bedrock/messages/invoke_transformations/anthropic_claude3_transformation.py b/litellm/llms/bedrock/messages/invoke_transformations/anthropic_claude3_transformation.py index b52d34a52b9..e53b5881867 100644 --- a/litellm/llms/bedrock/messages/invoke_transformations/anthropic_claude3_transformation.py +++ b/litellm/llms/bedrock/messages/invoke_transformations/anthropic_claude3_transformation.py @@ -515,7 +515,9 @@ class AmazonAnthropicClaudeMessagesConfig( # 5b. Bedrock Invoke supports output_config (effort) for Claude 4.6+ models, # but older models do not — strip it to avoid request rejection. # Ref: https://github.com/BerriAI/litellm/issues/22797 - if not _supports_factory(model=model, custom_llm_provider=None, key="supports_output_config"): + if not _supports_factory( + model=model, custom_llm_provider=None, key="supports_output_config" + ): anthropic_messages_request.pop("output_config", None) # 5a. Remove `custom` field from tools (Bedrock doesn't support it) diff --git a/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/gpt_oss/test_vertex_ai_gpt_oss_transformation.py b/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/gpt_oss/test_vertex_ai_gpt_oss_transformation.py index b16fc2bc44d..f617a8db850 100644 --- a/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/gpt_oss/test_vertex_ai_gpt_oss_transformation.py +++ b/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/gpt_oss/test_vertex_ai_gpt_oss_transformation.py @@ -118,7 +118,7 @@ async def test_vertex_ai_gpt_oss_simple_request(): "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", + "litellm.llms.vertex_ai.vertex_ai_partner_models.main.VertexAIPartnerModels._ensure_access_token", return_value=("fake-token", "pathrise-convert-1606954137718"), ), patch.dict( @@ -217,7 +217,7 @@ async def test_vertex_ai_gpt_oss_reasoning_effort(): "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", + "litellm.llms.vertex_ai.vertex_ai_partner_models.main.VertexAIPartnerModels._ensure_access_token", return_value=("fake-token", "pathrise-convert-1606954137718"), ), patch.dict( diff --git a/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/qwen/test_vertex_ai_qwen_global_endpoint.py b/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/qwen/test_vertex_ai_qwen_global_endpoint.py index bf6e0a5f2cd..5a86325b7fd 100644 --- a/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/qwen/test_vertex_ai_qwen_global_endpoint.py +++ b/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/qwen/test_vertex_ai_qwen_global_endpoint.py @@ -7,7 +7,6 @@ These tests verify that: 3. The completion() and responses() API work with Qwen models """ -import json import os import sys from unittest.mock import MagicMock, patch, AsyncMock @@ -179,7 +178,7 @@ async def test_vertex_ai_qwen_global_endpoint_url(): "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", + "litellm.llms.vertex_ai.vertex_ai_partner_models.main.VertexAIPartnerModels._ensure_access_token", return_value=("fake-token", "test-project"), ), patch.dict(