fix(azure): stop duplicating logprobs params for gpt-5.2 and gpt-5.4

AzureOpenAIGPT5Config.get_supported_openai_params appended logprobs and
top_logprobs for gpt-5.2/5.4 unconditionally, but the base OpenAI gpt-5
config already includes them for models that support reasoning_effort='none'.
The result was each param listed twice in the supported-params output.

Append only when missing, matching the tool_choice guard above it, so the
list stays deduplicated while still covering the case where the base config
omitted them.

litellm/llms/azure/chat/gpt_5_transformation.py

@@ -84,8 +84,7 @@ class AzureOpenAIGPT5Config(AzureOpenAIConfig, OpenAIGPT5Config):
         ) and not self.is_model_gpt_5_2_model(model):
             params = [p for p in params if p not in ["logprobs", "top_logprobs"]]
         elif self.is_model_gpt_5_2_model(model):
-            azure_supported_params = ["logprobs", "top_logprobs"]
-            params.extend(azure_supported_params)
+            params.extend(p for p in ("logprobs", "top_logprobs") if p not in params)
 
         return params
 

tests/test_litellm/llms/azure/chat/test_azure_gpt5_transformation.py

@@ -299,3 +299,21 @@ def test_azure_gpt5_1_does_not_support_logprobs(config: AzureOpenAIGPT5Config):
     supported_params = config.get_supported_openai_params(model="gpt-5.1")
     assert "logprobs" not in supported_params
     assert "top_logprobs" not in supported_params
+
+
+@pytest.mark.parametrize(
+    "model",
+    ["gpt-5.2", "azure/gpt-5.2", "gpt5_series/gpt-5.2", "azure/gpt-5.4"],
+)
+def test_azure_gpt5_2_logprobs_not_duplicated(
+    config: AzureOpenAIGPT5Config, model: str
+):
+    """Regression: gpt-5.2/5.4 must list logprobs and top_logprobs exactly once.
+
+    These models support reasoning_effort="none", so the base config already
+    includes the logprobs params; the Azure override must not append a second
+    copy.
+    """
+    supported_params = config.get_supported_openai_params(model=model)
+    assert supported_params.count("logprobs") == 1
+    assert supported_params.count("top_logprobs") == 1