feat: Add "instructions" support to responses API (#2205)

# What does this PR do?
Add support for "instructions" to the responses API. Instructions
provide a way to swap out system (or developer) messages in new
responses.


## Test Plan
unit tests added

Signed-off-by: Derek Higgins <derekh@redhat.com>

tests/unit/providers/agents/meta_reference/test_openai_responses.py

@@ -384,3 +384,141 @@ async def test_prepend_previous_response_web_search(get_previous_response_with_i
     # Check for new input
     assert isinstance(input[3], OpenAIResponseMessage)
     assert input[3].content == "fake_input"
+
+
+@pytest.mark.asyncio
+async def test_create_openai_response_with_instructions(openai_responses_impl, mock_inference_api):
+    # Setup
+    input_text = "What is the capital of Ireland?"
+    model = "meta-llama/Llama-3.1-8B-Instruct"
+    instructions = "You are a geography expert. Provide concise answers."
+
+    # Load the chat completion fixture
+    mock_chat_completion = load_chat_completion_fixture("simple_chat_completion.yaml")
+    mock_inference_api.openai_chat_completion.return_value = mock_chat_completion
+
+    # Execute
+    await openai_responses_impl.create_openai_response(
+        input=input_text,
+        model=model,
+        instructions=instructions,
+    )
+
+    # Verify
+    mock_inference_api.openai_chat_completion.assert_called_once()
+    call_args = mock_inference_api.openai_chat_completion.call_args
+    sent_messages = call_args.kwargs["messages"]
+
+    # Check that instructions were prepended as a system message
+    assert len(sent_messages) == 2
+    assert sent_messages[0].role == "system"
+    assert sent_messages[0].content == instructions
+    assert sent_messages[1].role == "user"
+    assert sent_messages[1].content == input_text
+
+
+@pytest.mark.asyncio
+async def test_create_openai_response_with_instructions_and_multiple_messages(
+    openai_responses_impl, mock_inference_api
+):
+    # Setup
+    input_messages = [
+        OpenAIResponseMessage(role="user", content="Name some towns in Ireland", name=None),
+        OpenAIResponseMessage(
+            role="assistant",
+            content="Galway, Longford, Sligo",
+            name=None,
+        ),
+        OpenAIResponseMessage(role="user", content="Which is the largest?", name=None),
+    ]
+    model = "meta-llama/Llama-3.1-8B-Instruct"
+    instructions = "You are a geography expert. Provide concise answers."
+
+    mock_chat_completion = load_chat_completion_fixture("simple_chat_completion.yaml")
+    mock_inference_api.openai_chat_completion.return_value = mock_chat_completion
+
+    # Execute
+    await openai_responses_impl.create_openai_response(
+        input=input_messages,
+        model=model,
+        instructions=instructions,
+    )
+
+    # Verify
+    mock_inference_api.openai_chat_completion.assert_called_once()
+    call_args = mock_inference_api.openai_chat_completion.call_args
+    sent_messages = call_args.kwargs["messages"]
+
+    # Check that instructions were prepended as a system message
+    assert len(sent_messages) == 4  # 1 system + 3 input messages
+    assert sent_messages[0].role == "system"
+    assert sent_messages[0].content == instructions
+
+    # Check the rest of the messages were converted correctly
+    assert sent_messages[1].role == "user"
+    assert sent_messages[1].content == "Name some towns in Ireland"
+    assert sent_messages[2].role == "assistant"
+    assert sent_messages[2].content == "Galway, Longford, Sligo"
+    assert sent_messages[3].role == "user"
+    assert sent_messages[3].content == "Which is the largest?"
+
+
+@pytest.mark.asyncio
+@patch.object(OpenAIResponsesImpl, "_get_previous_response_with_input")
+async def test_create_openai_response_with_instructions_and_previous_response(
+    get_previous_response_with_input, openai_responses_impl, mock_inference_api
+):
+    """Test prepending both instructions and previous response."""
+
+    input_item_message = OpenAIResponseMessage(
+        id="123",
+        content="Name some towns in Ireland",
+        role="user",
+    )
+    input_items = OpenAIResponseInputItemList(data=[input_item_message])
+    response_output_message = OpenAIResponseMessage(
+        id="123",
+        content="Galway, Longford, Sligo",
+        status="completed",
+        role="assistant",
+    )
+    response = OpenAIResponseObject(
+        created_at=1,
+        id="resp_123",
+        model="fake_model",
+        output=[response_output_message],
+        status="completed",
+    )
+    previous_response = OpenAIResponsePreviousResponseWithInputItems(
+        input_items=input_items,
+        response=response,
+    )
+    get_previous_response_with_input.return_value = previous_response
+
+    model = "meta-llama/Llama-3.1-8B-Instruct"
+    instructions = "You are a geography expert. Provide concise answers."
+    mock_chat_completion = load_chat_completion_fixture("simple_chat_completion.yaml")
+    mock_inference_api.openai_chat_completion.return_value = mock_chat_completion
+
+    # Execute
+    await openai_responses_impl.create_openai_response(
+        input="Which is the largest?", model=model, instructions=instructions, previous_response_id="123"
+    )
+
+    # Verify
+    mock_inference_api.openai_chat_completion.assert_called_once()
+    call_args = mock_inference_api.openai_chat_completion.call_args
+    sent_messages = call_args.kwargs["messages"]
+
+    # Check that instructions were prepended as a system message
+    assert len(sent_messages) == 4
+    assert sent_messages[0].role == "system"
+    assert sent_messages[0].content == instructions
+
+    # Check the rest of the messages were converted correctly
+    assert sent_messages[1].role == "user"
+    assert sent_messages[1].content == "Name some towns in Ireland"
+    assert sent_messages[2].role == "assistant"
+    assert sent_messages[2].content == "Galway, Longford, Sligo"
+    assert sent_messages[3].role == "user"
+    assert sent_messages[3].content == "Which is the largest?"