fixing centml get params

llama_stack/providers/remote/inference/centml/centml.py

@@ -237,6 +237,7 @@ class CentMLInferenceAdapter(
     async def _get_params(
         self, request: Union[ChatCompletionRequest, CompletionRequest]
     ) -> dict:
+
         """
         Build the 'params' dict that the OpenAI (CentML) client expects.
         For chat requests, we always prefer "messages" so that it calls
@@ -251,25 +252,36 @@ class CentMLInferenceAdapter(
                 await convert_message_to_openai_dict(m)
                 for m in request.messages
             ]
-
         else:
             # Non-chat (CompletionRequest)
-            assert not media_present, (
-                "CentML does not support media for completions"
-            )
+            assert not media_present, "CentML does not support media for completions"
             input_dict["prompt"] = await completion_request_to_prompt(
-                request, self.formatter
-            )
+                request, self.formatter)
 
-        return {
-            "model": request.model,
+        params = {
+            "model":
+            request.model,
             **input_dict,
-            "stream": request.stream,
-            **self._build_options(
-                request.sampling_params, request.response_format
-            ),
+            "stream":
+            request.stream,
+            **self._build_options(request.sampling_params, request.response_format),
         }
 
+        # For non-chat completions (i.e. when using a "prompt"), CentML's
+        # completions endpoint does not support the response_format parameter.
+        if "prompt" in params and "response_format" in params:
+            del params["response_format"]
+
+        # For chat completions with structured output, CentML requires
+        # guided decoding settings to use num_scheduler_steps=1 and spec_enabled=False.
+        # Override these if a response_format was requested.
+        if "messages" in params and request.response_format:
+            params["num_scheduler_steps"] = 1
+            params["spec_enabled"] = False
+
+        return params
+
+
     def _build_options(
         self,
         sampling_params: Optional[SamplingParams],