Fix: Azure OpenAI Responses API incorrectly blocking temperature parameter for GPT-5

litellm/llms/azure/responses/o_series_transformation.py

@@ -12,7 +12,6 @@
 
 from litellm._logging import verbose_logger
 from litellm.types.llms.openai import ResponsesAPIOptionalRequestParams
-from litellm.utils import supports_reasoning
 
 from .transformation import AzureOpenAIResponsesAPIConfig
 
@@ -79,15 +78,20 @@ def is_o_series_model(self, model: str) -> bool:
         """
         Check if the model is an O-series model.
 
+        O-series models include o1, o3, o4, etc. families (e.g., o1-preview, o3-mini).
+        Note: This is different from models that support reasoning - GPT-5 supports
+        reasoning but is NOT an O-series model.
+
         Args:
             model: The model name to check
 
         Returns:
             True if it's an O-series model, False otherwise
         """
-        # Check if model name contains o_series or if it's a known O-series model
-        if "o_series" in model.lower():
+        # Check if path contains o_series/ routing prefix (e.g., azure/responses/o_series/model)
+        if "o_series/" in model:
             return True
-
-        # Check if the model supports reasoning (which is O-series specific)
-        return supports_reasoning(model) 
+
+        # Check if the base model name starts with o1/o3/o4 prefixes
+        model_basename = model.split("/")[-1]  # could be "azure/o3" or "o3"
+        return any(model_basename.startswith(pfx) for pfx in ("o1", "o3", "o4")) 

litellm/utils.py

@@ -7396,11 +7396,18 @@ def get_provider_responses_api_config(
         if litellm.LlmProviders.OPENAI == provider:
             return litellm.OpenAIResponsesAPIConfig()
         elif litellm.LlmProviders.AZURE == provider:
-            # Check if it's an O-series model
-            if model and ("o_series" in model.lower() or supports_reasoning(model)):
-                return litellm.AzureOpenAIOSeriesResponsesAPIConfig()
-            else:
-                return litellm.AzureOpenAIResponsesAPIConfig()
+            # Check if it's an O-series model (o1, o3, o4, etc.)
+            # Note: We check for specific O-series model names, not just "supports_reasoning"
+            # since GPT-5 supports reasoning but is NOT an O-series model
+            if model:
+                # Check if path contains o_series/ routing prefix
+                if "o_series/" in model:
+                    return litellm.AzureOpenAIOSeriesResponsesAPIConfig()
+                # Check if the base model name starts with o1/o3/o4 prefixes
+                _model = model.split("/")[-1]  # could be "azure/o3" or "o3"
+                if any(_model.startswith(pfx) for pfx in ("o1", "o3", "o4")):
+                    return litellm.AzureOpenAIOSeriesResponsesAPIConfig()
+            return litellm.AzureOpenAIResponsesAPIConfig()
         elif litellm.LlmProviders.LITELLM_PROXY == provider:
             return litellm.LiteLLMProxyResponsesAPIConfig()
         return None

tests/test_litellm/llms/azure/response/test_azure_transformation.py

@@ -194,9 +194,31 @@ def test_o_series_model_detection():
     assert config.is_o_series_model("o_series/gpt-o1") == True
     assert config.is_o_series_model("azure/o_series/gpt-o3") == True
 
+    # Test O1 models
+    assert config.is_o_series_model("o1") == True
+    assert config.is_o_series_model("o1-preview") == True
+    assert config.is_o_series_model("o1-mini") == True
+    assert config.is_o_series_model("azure/o1-preview") == True
+
+    # Test O3 models
+    assert config.is_o_series_model("o3") == True
+    assert config.is_o_series_model("o3-mini") == True
+    assert config.is_o_series_model("azure/o3-mini") == True
+
     # Test regular models
     assert config.is_o_series_model("gpt-4o") == False
     assert config.is_o_series_model("gpt-3.5-turbo") == False
+
+    # Test GPT-5 (supports reasoning but is NOT an O-series model)
+    assert config.is_o_series_model("gpt-5") == False
+    assert config.is_o_series_model("gpt-5-turbo") == False
+    assert config.is_o_series_model("azure/gpt-5") == False
+
+    # Edge cases: Models with "o1", "o3", "o4" in the middle or end should NOT match
+    # (using startswith ensures only models that START with these prefixes match)
+    assert config.is_o_series_model("gpt-4o1") == False  # has "o1" but doesn't start with it
+    assert config.is_o_series_model("gpto1") == False  # has "o1" but doesn't start with it
+    assert config.is_o_series_model("model-o3-test") == False  # has "o3" but doesn't start with it
 
 
 @pytest.mark.serial
@@ -211,13 +233,35 @@ def test_provider_config_manager_o_series_selection():
     )
     assert isinstance(o_series_config, AzureOpenAIOSeriesResponsesAPIConfig)
 
+    # Test O1 model selection
+    o1_config = ProviderConfigManager.get_provider_responses_api_config(
+        provider=litellm.LlmProviders.AZURE, model="o1-preview"
+    )
+    assert isinstance(o1_config, AzureOpenAIOSeriesResponsesAPIConfig)
+
+    # Test O3 model selection
+    o3_config = ProviderConfigManager.get_provider_responses_api_config(
+        provider=litellm.LlmProviders.AZURE, model="o3-mini"
+    )
+    assert isinstance(o3_config, AzureOpenAIOSeriesResponsesAPIConfig)
+
     # Test regular model selection
     regular_config = ProviderConfigManager.get_provider_responses_api_config(
         provider=litellm.LlmProviders.AZURE, model="gpt-4o"
     )
     assert isinstance(regular_config, AzureOpenAIResponsesAPIConfig)
     assert not isinstance(regular_config, AzureOpenAIOSeriesResponsesAPIConfig)
 
+    # Test GPT-5 model selection (supports reasoning but is NOT O-series)
+    gpt5_config = ProviderConfigManager.get_provider_responses_api_config(
+        provider=litellm.LlmProviders.AZURE, model="gpt-5"
+    )
+    assert isinstance(gpt5_config, AzureOpenAIResponsesAPIConfig)
+    assert not isinstance(gpt5_config, AzureOpenAIOSeriesResponsesAPIConfig)
+    # Verify temperature is supported for GPT-5
+    gpt5_params = gpt5_config.get_supported_openai_params("gpt-5")
+    assert "temperature" in gpt5_params, "GPT-5 should support temperature parameter"
+
     # Test with no model specified (should default to regular)
     default_config = ProviderConfigManager.get_provider_responses_api_config(
         provider=litellm.LlmProviders.AZURE, model=None