Fix YAML agent ignoring model.options execution settings

Fixes #13349

When loading agents from YAML files, model.options (like response_format,
temperature, etc.) were being added as regular KernelArguments dict items
instead of being placed in execution_settings. This caused AI service
calls to ignore these settings.

Changes:
- Modified _normalize_spec_fields() in agent.py to convert model.options
  to PromptExecutionSettings before creating KernelArguments
- Model options now correctly placed in execution_settings property
- Input defaults continue to be added as regular dict items (correct)

Testing:
- Verified with custom test showing model.options now in execution_settings
- All 30 existing unit tests in tests/unit/agents/test_agent.py pass
- No breaking changes introduced

Author: yashwantbezawada

python/semantic_kernel/agents/agent.py

@@ -13,6 +13,7 @@
 from pydantic import Field, model_validator
 
 from semantic_kernel.agents.channels.agent_channel import AgentChannel
+from semantic_kernel.connectors.ai.prompt_execution_settings import PromptExecutionSettings
 from semantic_kernel.contents.chat_message_content import CMC_ITEM_TYPES, ChatMessageContent
 from semantic_kernel.contents.streaming_chat_message_content import StreamingChatMessageContent
 from semantic_kernel.contents.utils.author_role import AuthorRole
@@ -998,9 +999,19 @@ def _normalize_spec_fields(
             if v.get("default") is not None
         }
 
-        # Start with model options
-        arguments = KernelArguments(**model_options)
-        # Update with input defaults (only if not already provided by model options)
+        # Convert model options to execution settings
+        # Model options (like response_format, temperature, etc.) should be execution settings,
+        # not regular arguments
+        if model_options:
+            # Create PromptExecutionSettings from model options
+            # The PromptExecutionSettings constructor handles **kwargs by putting them in extension_data
+            # and then unpacking them to actual fields if they exist
+            exec_settings = PromptExecutionSettings(**model_options)
+            arguments = KernelArguments(settings=exec_settings)
+        else:
+            arguments = KernelArguments()
+
+        # Add input defaults as regular dict items (not execution settings)
         for k, v in input_defaults.items():
             if k not in arguments:
                 arguments[k] = v