fix(azure_ai): read the azure_ai card for gpt-5 series reasoning effort gates

Foundry deployments of gpt-6-astra reached through azure_ai used the bare OpenAI card
for the reasoning_effort none gates, so temperature and top_p were refused while the
azure_ai card says none is supported. AzureAIStudioConfig now dispatches gpt-5 series
params through AzureAIGPT5Config, which looks capabilities up under the azure_ai/
prefix the way the azure route does

Also carries the search_context_cost_per_query block azure/gpt-6-astra has, adds a
flex service tier cost test that fails at the merge base, and keeps the wildcard test
from stripping azure_ai/gpt-6-astra out of the provider set

litellm/llms/azure_ai/chat/transformation.py

@@ -17,6 +17,7 @@ from litellm.litellm_core_utils.prompt_templates.common_utils import (
 from litellm.llms.azure.common_utils import BaseAzureLLM
 from litellm.llms.azure_ai.common_utils import is_foundry_model_inference_base
 from litellm.llms.base_llm.chat.transformation import LiteLLMLoggingObj
+from litellm.llms.openai.chat.gpt_5_transformation import OpenAIGPT5Config
 from litellm.llms.openai.common_utils import drop_params_from_unprocessable_entity_error
 from litellm.llms.openai.openai import OpenAIConfig
 from litellm.llms.xai.chat.transformation import XAIChatConfig
@@ -42,12 +43,25 @@ NON_OPENAI_SPEC_MESSAGE_FIELDS: Final = (
 )
 
 
+class AzureAIGPT5Config(OpenAIGPT5Config):
+    @classmethod
+    def _model_map_lookup_name(cls, model: str) -> str:
+        return model if model.startswith("azure_ai/") else f"azure_ai/{model}"
+
+
+azureAIGPT5Config: Final = AzureAIGPT5Config()
+
+
 class AzureAIStudioConfig(OpenAIConfig):
     def get_supported_openai_params(self, model: str) -> list:
         model_supports_tool_choice = True  # azure ai supports this by default
         if not supports_tool_choice(model=f"azure_ai/{model}"):
             model_supports_tool_choice = False
-        supported_params = super().get_supported_openai_params(model)
+        supported_params = (
+            azureAIGPT5Config.get_supported_openai_params(model)
+            if azureAIGPT5Config.is_model_gpt_5_model(model)
+            else super().get_supported_openai_params(model)
+        )
         if not model_supports_tool_choice:
             filtered_supported_params: Final = []
             for param in supported_params:
@@ -61,6 +75,27 @@ class AzureAIStudioConfig(OpenAIConfig):
 
         return supported_params
 
+    def map_openai_params(
+        self,
+        non_default_params: dict,  # mutable-ok: OpenAIConfig.map_openai_params signature
+        optional_params: dict,  # mutable-ok: OpenAIConfig.map_openai_params signature
+        model: str,
+        drop_params: bool,
+    ) -> dict:  # mutable-ok: OpenAIConfig.map_openai_params signature
+        if not azureAIGPT5Config.is_model_gpt_5_model(model):
+            return super().map_openai_params(
+                non_default_params=non_default_params,
+                optional_params=optional_params,
+                model=model,
+                drop_params=drop_params,
+            )
+        return azureAIGPT5Config.map_openai_params(
+            non_default_params=non_default_params,
+            optional_params=optional_params,
+            model=model,
+            drop_params=drop_params,
+        )
+
     def _supports_stop_reason(self, model: str) -> bool:
         """
         Check if the model supports stop tokens.

litellm/model_prices_and_context_window_backup.json

@@ -3499,6 +3499,11 @@
         "mode": "chat",
         "output_cost_per_token": 5e-05,
         "output_cost_per_token_above_272k_tokens": 7.5e-05,
+        "search_context_cost_per_query": {
+            "search_context_size_high": 0.01,
+            "search_context_size_low": 0.01,
+            "search_context_size_medium": 0.01
+        },
         "source": "https://ai.azure.com/catalog/models/gpt-6-astra",
         "supported_endpoints": [
             "/v1/chat/completions",

model_prices_and_context_window.json

@@ -3499,6 +3499,11 @@
         "mode": "chat",
         "output_cost_per_token": 5e-05,
         "output_cost_per_token_above_272k_tokens": 7.5e-05,
+        "search_context_cost_per_query": {
+            "search_context_size_high": 0.01,
+            "search_context_size_low": 0.01,
+            "search_context_size_medium": 0.01
+        },
         "source": "https://ai.azure.com/catalog/models/gpt-6-astra",
         "supported_endpoints": [
             "/v1/chat/completions",

tests/test_litellm/litellm_core_utils/llm_cost_calc/test_llm_cost_calc_utils.py

@@ -2060,6 +2060,21 @@ def test_generic_cost_per_token_azure_gpt_6_astra_foundry_price_sheet(
     assert completion_cost == pytest.approx(zone_multiplier * output_multiplier * completion_tokens * 5e-5)
 
 
+def test_generic_cost_per_token_azure_ai_gpt_6_astra_flex_bills_the_standard_rate(_local_model_cost_map):
+    """Foundry sells gpt-6-astra on Standard Global only, so a flex service_tier bills the standard rate.
+    The bare OpenAI card the azure_ai route fell back to before this entry existed carries flex prices
+    at half rate (LIT-7081)."""
+    usage = Usage(prompt_tokens=1000, completion_tokens=100, total_tokens=1100)
+
+    standard = generic_cost_per_token(model="azure_ai/gpt-6-astra", usage=usage, custom_llm_provider="azure_ai")
+    flex = generic_cost_per_token(
+        model="azure_ai/gpt-6-astra", usage=usage, custom_llm_provider="azure_ai", service_tier="flex"
+    )
+
+    assert flex == standard
+    assert standard == pytest.approx((1000 * 1e-05, 100 * 5e-05))
+
+
 @pytest.mark.parametrize(
     "model,expected_none,expected_xhigh,expected_minimal",
     [

tests/test_litellm/llms/azure_ai/chat/test_azure_ai_transformation.py

@@ -3,6 +3,8 @@ from unittest.mock import MagicMock, patch
 
 import pytest
 
+import litellm
+from litellm.litellm_core_utils.get_model_cost_map import get_model_cost_map
 from litellm.llms.azure_ai.azure_model_router.transformation import (
     AzureModelRouterConfig,
 )
@@ -138,6 +140,26 @@ def test_azure_ai_validate_environment_with_azure_ad_token():
     assert headers["Content-Type"] == "application/json"
 
 
+@pytest.fixture
+def _local_model_cost_map(monkeypatch: pytest.MonkeyPatch) -> None:
+    monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
+    monkeypatch.setattr(litellm, "model_cost", get_model_cost_map(url=litellm.model_cost_map_url))
+
+
+def test_foundry_gpt_6_astra_keeps_sampling_params_when_reasoning_effort_is_none(_local_model_cost_map):
+    """A Foundry deployment reached through azure_ai reads the azure_ai/ card, where gpt-6-astra supports
+    reasoning_effort none, so temperature and top_p ride along; the bare OpenAI card says none is
+    unsupported and the route used to refuse temperature and drop top_p (LIT-7081)."""
+    optional_params = AzureAIStudioConfig().map_openai_params(
+        non_default_params={"reasoning_effort": "none", "temperature": 0.2, "top_p": 0.9},
+        optional_params={},
+        model="gpt-6-astra",
+        drop_params=False,
+    )
+
+    assert optional_params == {"reasoning_effort": "none", "temperature": 0.2, "top_p": 0.9}
+
+
 def test_azure_ai_grok_stop_parameter_handling():
     """
     Test that Grok models properly handle stop parameter filtering in Azure AI Studio.

tests/test_litellm/proxy/auth/test_model_checks.py

@@ -868,12 +868,14 @@ def test_azure_ai_wildcard_lists_the_foundry_gpt_6_astra_entry(monkeypatch):
     monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
     foundry_key = "azure_ai/gpt-6-astra"
     local_entry = litellm.get_model_cost_map(url="")[foundry_key]
+    registered_before = foundry_key in litellm.azure_ai_models
     try:
         litellm.add_known_models(model_cost_map={foundry_key: local_entry})
         assert foundry_key in get_known_models_from_wildcard("azure_ai/*")
     finally:
-        litellm.azure_ai_models.discard(foundry_key)
-        litellm.add_known_models(model_cost_map={})
+        if not registered_before:
+            litellm.azure_ai_models.discard(foundry_key)
+            litellm.add_known_models(model_cost_map={})
 
 
 def test_get_complete_model_list_drops_no_default_models_sentinel():