fix: ensure assistant message is followed by tool call message as expected by openai (#3224)

# What does this PR do?

As described in #3134 a langchain example works against openai's
responses impl, but not against llama stack's. This turned out to be due
to the order of the inputs. The langchain example has the two function
call outputs first, followed by each call result in turn. This seems to
be valid as it is accepted by openai's impl. However in llama stack,
these inputs are converted to chat completion inputs and the resulting
order for that api is not accpeted by openai.

This PR fixes the issue by ensuring that the converted chat completions
inputs are in the expected order.

Closes #3134 

## Test Plan
Added unit and integration tests. Verified this fixes original issue as
reported.

---------

Signed-off-by: Gordon Sim <gsim@redhat.com>

tests/integration/non_ci/responses/test_tool_responses.py

@@ -260,6 +260,94 @@ def test_response_non_streaming_custom_tool(compat_client, text_model_id, case):
     assert response.output[0].name == "get_weather"
 
 
+@pytest.mark.parametrize("case", custom_tool_test_cases)
+def test_response_function_call_ordering_1(compat_client, text_model_id, case):
+    response = compat_client.responses.create(
+        model=text_model_id,
+        input=case.input,
+        tools=case.tools,
+        stream=False,
+    )
+    assert len(response.output) == 1
+    assert response.output[0].type == "function_call"
+    assert response.output[0].status == "completed"
+    assert response.output[0].name == "get_weather"
+    inputs = []
+    inputs.append(
+        {
+            "role": "user",
+            "content": case.input,
+        }
+    )
+    inputs.append(
+        {
+            "type": "function_call_output",
+            "output": "It is raining.",
+            "call_id": response.output[0].call_id,
+        }
+    )
+    response = compat_client.responses.create(
+        model=text_model_id, input=inputs, tools=case.tools, stream=False, previous_response_id=response.id
+    )
+    assert len(response.output) == 1
+
+
+def test_response_function_call_ordering_2(compat_client, text_model_id):
+    tools = [
+        {
+            "type": "function",
+            "name": "get_weather",
+            "description": "Get current temperature for a given location.",
+            "parameters": {
+                "additionalProperties": False,
+                "properties": {
+                    "location": {
+                        "description": "City and country e.g. Bogotá, Colombia",
+                        "type": "string",
+                    }
+                },
+                "required": ["location"],
+                "type": "object",
+            },
+        }
+    ]
+    inputs = [
+        {
+            "role": "user",
+            "content": "Is the weather better in San Francisco or Los Angeles?",
+        }
+    ]
+    response = compat_client.responses.create(
+        model=text_model_id,
+        input=inputs,
+        tools=tools,
+        stream=False,
+    )
+    for output in response.output:
+        if output.type == "function_call" and output.status == "completed" and output.name == "get_weather":
+            inputs.append(output)
+    for output in response.output:
+        if output.type == "function_call" and output.status == "completed" and output.name == "get_weather":
+            weather = "It is raining."
+            if "Los Angeles" in output.arguments:
+                weather = "It is cloudy."
+            inputs.append(
+                {
+                    "type": "function_call_output",
+                    "output": weather,
+                    "call_id": output.call_id,
+                }
+            )
+    response = compat_client.responses.create(
+        model=text_model_id,
+        input=inputs,
+        tools=tools,
+        stream=False,
+    )
+    assert len(response.output) == 1
+    assert "Los Angeles" in response.output_text
+
+
 @pytest.mark.parametrize("case", multi_turn_tool_execution_test_cases)
 def test_response_non_streaming_multi_turn_tool_execution(compat_client, text_model_id, case):
     """Test multi-turn tool execution where multiple MCP tool calls are performed in sequence."""