fix: Responses API: handle type=None in streaming tool calls (#2166)

# What does this PR do?

In the Responses API, we convert incoming response requests to chat
completion requests. When streaming the resulting chunks of those chat
completion requests, inference providers that use OpenAI clients will
often return a `type=None` value in the tool call parts of the response.
This causes issues when we try to dump and load that response into our
pydantic model, because type cannot be None in the Responses API model
we're loading these into.

So, strip the "type" field, if present, off those chat completion tool
call results before dumping and loading them as our typed pydantic
models, which will apply our default value for that type field.

## Test Plan

This was found via manual testing of the Responses API with codex, where
I was getting errors in some tool call situations. I added a unit test
to simulate this scenario and verify the fix, as well as manual codex
testing to verify the fix.

Signed-off-by: Ben Browning <bbrownin@redhat.com>

llama_stack/providers/inline/agents/meta_reference/openai_responses.py

@@ -7,7 +7,7 @@
 import json
 import uuid
 from collections.abc import AsyncIterator
-from typing import cast
+from typing import Any, cast
 
 from openai.types.chat import ChatCompletionToolParam
 from pydantic import BaseModel
@@ -264,7 +264,11 @@ class OpenAIResponsesImpl:
                             if response_tool_call:
                                 response_tool_call.function.arguments += tool_call.function.arguments
                             else:
-                                response_tool_call = OpenAIChatCompletionToolCall(**tool_call.model_dump())
+                                tool_call_dict: dict[str, Any] = tool_call.model_dump()
+                                # Ensure we don't have any empty type field in the tool call dict.
+                                # The OpenAI client used by providers often returns a type=None here.
+                                tool_call_dict.pop("type", None)
+                                response_tool_call = OpenAIChatCompletionToolCall(**tool_call_dict)
                             chat_response_tool_calls[tool_call.index] = response_tool_call
 
             # Convert the dict of tool calls by index to a list of tool calls to pass back in our response