fmt

libs/partners/openai/langchain_openai/chat_models/base.py

@@ -914,9 +914,9 @@ class BaseChatOpenAI(BaseChatModel):
             raw_response = self.client.with_raw_response.create(**payload)
             response = raw_response.parse()
             generation_info = {"headers": dict(raw_response.headers)}
-        elif _use_response_api(payload):
+        elif _use_responses_api(payload):
             response = self.root_client.responses.create(**payload)
-            return _construct_lc_result_from_response_api(response)
+            return _construct_lc_result_from_responses_api(response)
         else:
             response = self.client.create(**payload)
         return self._create_chat_result(response, generation_info)
@@ -933,8 +933,8 @@ class BaseChatOpenAI(BaseChatModel):
             kwargs["stop"] = stop
 
         payload = {**self._default_params, **kwargs}
-        if _use_response_api(payload):
-            payload = _construct_response_api_payload(messages, payload)
+        if _use_responses_api(payload):
+            payload = _construct_responses_api_payload(messages, payload)
         else:
             payload["messages"] = [_convert_message_to_dict(m) for m in messages]
         return payload
@@ -1088,9 +1088,9 @@ class BaseChatOpenAI(BaseChatModel):
             raw_response = await self.async_client.with_raw_response.create(**payload)
             response = raw_response.parse()
             generation_info = {"headers": dict(raw_response.headers)}
-        elif _use_response_api(payload):
+        elif _use_responses_api(payload):
             response = await self.root_async_client.responses.create(**payload)
-            return _construct_lc_result_from_response_api(response)
+            return _construct_lc_result_from_responses_api(response)
         else:
             response = await self.async_client.create(**payload)
         return await run_in_executor(
@@ -2189,7 +2189,7 @@ class ChatOpenAI(BaseChatOpenAI):  # type: ignore[override]
         self, *args: Any, stream_usage: Optional[bool] = None, **kwargs: Any
     ) -> Iterator[ChatGenerationChunk]:
         """Set default stream_options."""
-        if _use_response_api(kwargs):
+        if _use_responses_api(kwargs):
             return super()._stream_responses(*args, **kwargs)
         else:
             stream_usage = self._should_stream_usage(stream_usage, **kwargs)
@@ -2207,7 +2207,7 @@ class ChatOpenAI(BaseChatOpenAI):  # type: ignore[override]
         self, *args: Any, stream_usage: Optional[bool] = None, **kwargs: Any
     ) -> AsyncIterator[ChatGenerationChunk]:
         """Set default stream_options."""
-        if _use_response_api(kwargs):
+        if _use_responses_api(kwargs):
             async for chunk in super()._astream_responses(*args, **kwargs):
                 yield chunk
         else:
@@ -2760,16 +2760,18 @@ def _is_builtin_tool(tool: dict) -> bool:
     return "type" in tool and tool["type"] != "function"
 
 
-def _use_response_api(payload: dict) -> bool:
-    return "tools" in payload and any(
+def _use_responses_api(payload: dict) -> bool:
+    uses_builtin_tools = "tools" in payload and any(
         _is_builtin_tool(tool) for tool in payload["tools"]
     )
+    responses_only_args = {"previous_response_id", "text", "truncation", "include"}
+    return bool(uses_builtin_tools or responses_only_args.intersection(payload))
 
 
-def _construct_response_api_payload(
+def _construct_responses_api_payload(
     messages: Sequence[BaseMessage], payload: dict
 ) -> dict:
-    payload["input"] = _construct_response_api_input(messages)
+    payload["input"] = _construct_responses_api_input(messages)
     if tools := payload.pop("tools", None):
         new_tools: list = []
         for tool in tools:
@@ -2803,7 +2805,7 @@ def _construct_response_api_payload(
     return payload
 
 
-def _construct_response_api_input(messages: Sequence[BaseMessage]) -> list:
+def _construct_responses_api_input(messages: Sequence[BaseMessage]) -> list:
     input_ = []
     for lc_msg in messages:
         msg = _convert_message_to_dict(lc_msg)
@@ -2899,7 +2901,7 @@ def _construct_response_api_input(messages: Sequence[BaseMessage]) -> list:
     return input_
 
 
-def _construct_lc_result_from_response_api(response: Response) -> ChatResult:
+def _construct_lc_result_from_responses_api(response: Response) -> ChatResult:
     """Construct ChatResponse from OpenAI Response API response."""
     if response.error:
         raise ValueError(response.error)

libs/partners/openai/tests/integration_tests/chat_models/test_base.py

@@ -2,7 +2,6 @@
 
 import base64
 import json
-import os
 from pathlib import Path
 from textwrap import dedent
 from typing import Any, AsyncIterator, List, Literal, Optional, cast
@@ -1229,102 +1228,3 @@ def test_structured_output_and_tools() -> None:
     assert len(full.tool_calls) == 1
     tool_call = full.tool_calls[0]
     assert tool_call["name"] == "GenerateUsername"
-
-
-def _check_response(response: Optional[BaseMessage]) -> None:
-    assert isinstance(response, AIMessage)
-    assert isinstance(response.content, list)
-    for block in response.content:
-        assert isinstance(block, dict)
-        if block["type"] == "text":
-            assert isinstance(block["text"], str)
-            for annotation in block["annotations"]:
-                if annotation["type"] == "file_citation":
-                    assert all(
-                        key in annotation
-                        for key in ["file_id", "filename", "index", "type"]
-                    )
-                elif annotation["type"] == "web_search":
-                    assert all(
-                        key in annotation
-                        for key in ["end_index", "start_index", "title", "type", "url"]
-                    )
-
-    text_content = response.text()
-    assert isinstance(text_content, str)
-    assert text_content
-    assert response.usage_metadata
-    assert response.usage_metadata["input_tokens"] > 0
-    assert response.usage_metadata["output_tokens"] > 0
-    assert response.usage_metadata["total_tokens"] > 0
-    assert response.response_metadata["model_name"]
-    for tool_output in response.additional_kwargs["tool_outputs"]:
-        assert tool_output["id"]
-        assert tool_output["status"]
-        assert tool_output["type"]
-
-
-def test_web_search() -> None:
-    llm = ChatOpenAI(model="gpt-4o-mini")
-    response = llm.invoke(
-        "What was a positive news story from today?",
-        tools=[{"type": "web_search_preview"}],
-    )
-    _check_response(response)
-    assert response.response_metadata["status"]
-
-    # Test streaming
-    full: Optional[BaseMessageChunk] = None
-    for chunk in llm.stream(
-        "What was a positive news story from today?",
-        tools=[{"type": "web_search_preview"}],
-    ):
-        assert isinstance(chunk, AIMessageChunk)
-        full = chunk if full is None else full + chunk
-    _check_response(full)
-
-    llm.invoke(
-        "what about a negative one",
-        tools=[{"type": "web_search_preview"}],
-        response_id=response.response_metadata["id"],
-    )
-    _check_response(response)
-
-
-async def test_web_search_async() -> None:
-    llm = ChatOpenAI(model="gpt-4o-mini")
-    response = await llm.ainvoke(
-        "What was a positive news story from today?",
-        tools=[{"type": "web_search_preview"}],
-    )
-    _check_response(response)
-    assert response.response_metadata["status"]
-
-    # Test streaming
-    full: Optional[BaseMessageChunk] = None
-    async for chunk in llm.astream(
-        "What was a positive news story from today?",
-        tools=[{"type": "web_search_preview"}],
-    ):
-        assert isinstance(chunk, AIMessageChunk)
-        full = chunk if full is None else full + chunk
-    assert isinstance(full, AIMessageChunk)
-    _check_response(full)
-
-
-def test_file_search() -> None:
-    pytest.skip()  # TODO: set up infra
-    llm = ChatOpenAI(model="gpt-4o-mini")
-    tool = {
-        "type": "file_search",
-        "vector_store_ids": [os.environ["OPENAI_VECTOR_STORE_ID"]],
-    }
-    response = llm.invoke("What is deep research by OpenAI?", tools=[tool])
-    _check_response(response)
-
-    full: Optional[BaseMessageChunk] = None
-    for chunk in llm.stream("What is deep research by OpenAI?", tools=[tool]):
-        assert isinstance(chunk, AIMessageChunk)
-        full = chunk if full is None else full + chunk
-    assert isinstance(full, AIMessageChunk)
-    _check_response(full)

libs/partners/openai/tests/integration_tests/chat_models/test_responses_api.py

@@ -0,0 +1,132 @@
+"""Test Responses API usage."""
+
+import os
+from typing import Optional
+
+import pytest
+from langchain_core.messages import (
+    AIMessage,
+    AIMessageChunk,
+    BaseMessage,
+    BaseMessageChunk,
+)
+
+from langchain_openai import ChatOpenAI
+
+
+def _check_response(response: Optional[BaseMessage]) -> None:
+    assert isinstance(response, AIMessage)
+    assert isinstance(response.content, list)
+    for block in response.content:
+        assert isinstance(block, dict)
+        if block["type"] == "text":
+            assert isinstance(block["text"], str)
+            for annotation in block["annotations"]:
+                if annotation["type"] == "file_citation":
+                    assert all(
+                        key in annotation
+                        for key in ["file_id", "filename", "index", "type"]
+                    )
+                elif annotation["type"] == "web_search":
+                    assert all(
+                        key in annotation
+                        for key in ["end_index", "start_index", "title", "type", "url"]
+                    )
+
+    text_content = response.text()
+    assert isinstance(text_content, str)
+    assert text_content
+    assert response.usage_metadata
+    assert response.usage_metadata["input_tokens"] > 0
+    assert response.usage_metadata["output_tokens"] > 0
+    assert response.usage_metadata["total_tokens"] > 0
+    assert response.response_metadata["model_name"]
+    for tool_output in response.additional_kwargs["tool_outputs"]:
+        assert tool_output["id"]
+        assert tool_output["status"]
+        assert tool_output["type"]
+
+
+def test_web_search() -> None:
+    llm = ChatOpenAI(model="gpt-4o-mini")
+    first_response = llm.invoke(
+        "What was a positive news story from today?",
+        tools=[{"type": "web_search_preview"}],
+    )
+    _check_response(first_response)
+
+    # Test streaming
+    full: Optional[BaseMessageChunk] = None
+    for chunk in llm.stream(
+        "What was a positive news story from today?",
+        tools=[{"type": "web_search_preview"}],
+    ):
+        assert isinstance(chunk, AIMessageChunk)
+        full = chunk if full is None else full + chunk
+    _check_response(full)
+
+    # Use OpenAI's stateful API
+    response = llm.invoke(
+        "what about a negative one",
+        tools=[{"type": "web_search_preview"}],
+        previous_response_id=first_response.response_metadata["id"],
+    )
+    _check_response(response)
+
+    # Manually pass in chat history
+    response = llm.invoke(
+        [
+            first_response,
+            {
+                "role": "user",
+                "content": [{"type": "text", "text": "what about a negative one"}],
+            },
+        ],
+        tools=[{"type": "web_search_preview"}],
+    )
+    _check_response(response)
+
+    # Bind tool
+    response = llm.bind_tools([{"type": "web_search_preview"}]).invoke(
+        "What was a positive news story from today?"
+    )
+    _check_response(response)
+
+
+async def test_web_search_async() -> None:
+    llm = ChatOpenAI(model="gpt-4o-mini")
+    response = await llm.ainvoke(
+        "What was a positive news story from today?",
+        tools=[{"type": "web_search_preview"}],
+    )
+    _check_response(response)
+    assert response.response_metadata["status"]
+
+    # Test streaming
+    full: Optional[BaseMessageChunk] = None
+    async for chunk in llm.astream(
+        "What was a positive news story from today?",
+        tools=[{"type": "web_search_preview"}],
+    ):
+        assert isinstance(chunk, AIMessageChunk)
+        full = chunk if full is None else full + chunk
+    assert isinstance(full, AIMessageChunk)
+    _check_response(full)
+
+
+def test_file_search() -> None:
+    pytest.skip()  # TODO: set up infra
+    llm = ChatOpenAI(model="gpt-4o-mini")
+    tool = {
+        "type": "file_search",
+        "vector_store_ids": [os.environ["OPENAI_VECTOR_STORE_ID"]],
+    }
+    response = llm.invoke("What is deep research by OpenAI?", tools=[tool])
+    _check_response(response)
+
+    full: Optional[BaseMessageChunk] = None
+    for chunk in llm.stream("What is deep research by OpenAI?", tools=[tool]):
+        assert isinstance(chunk, AIMessageChunk)
+        full = chunk if full is None else full + chunk
+    assert isinstance(full, AIMessageChunk)
+    _check_response(full)

libs/partners/openai/tests/unit_tests/chat_models/test_base.py

@@ -41,8 +41,8 @@ from typing_extensions import TypedDict
 from langchain_openai import ChatOpenAI
 from langchain_openai.chat_models.base import (
     _FUNCTION_CALL_IDS_MAP_KEY,
-    _construct_lc_result_from_response_api,
-    _construct_response_api_input,
+    _construct_lc_result_from_responses_api,
+    _construct_responses_api_input,
     _convert_dict_to_message,
     _convert_message_to_dict,
     _convert_to_openai_response_format,
@@ -955,7 +955,7 @@ def test_structured_outputs_parser() -> None:
     assert result == parsed_response
 
 
-def test__construct_lc_result_from_response_api_error_handling() -> None:
+def test__construct_lc_result_from_responses_api_error_handling() -> None:
     """Test that errors in the response are properly raised."""
     response = Response(
         id="resp_123",
@@ -970,12 +970,12 @@ def test__construct_lc_result_from_response_api_error_handling() -> None:
     )
 
     with pytest.raises(ValueError) as excinfo:
-        _construct_lc_result_from_response_api(response)
+        _construct_lc_result_from_responses_api(response)
 
     assert "Test error" in str(excinfo.value)
 
 
-def test__construct_lc_result_from_response_api_basic_text_response() -> None:
+def test__construct_lc_result_from_responses_api_basic_text_response() -> None:
     """Test a basic text response with no tools or special features."""
     response = Response(
         id="resp_123",
@@ -1006,7 +1006,7 @@ def test__construct_lc_result_from_response_api_basic_text_response() -> None:
         ),
     )
 
-    result = _construct_lc_result_from_response_api(response)
+    result = _construct_lc_result_from_responses_api(response)
 
     assert isinstance(result, ChatResult)
     assert len(result.generations) == 1
@@ -1024,7 +1024,7 @@ def test__construct_lc_result_from_response_api_basic_text_response() -> None:
     assert result.generations[0].message.response_metadata["model_name"] == "gpt-4o"
 
 
-def test__construct_lc_result_from_response_api_multiple_text_blocks() -> None:
+def test__construct_lc_result_from_responses_api_multiple_text_blocks() -> None:
     """Test a response with multiple text blocks."""
     response = Response(
         id="resp_123",
@@ -1052,14 +1052,14 @@ def test__construct_lc_result_from_response_api_multiple_text_blocks() -> None:
         ],
     )
 
-    result = _construct_lc_result_from_response_api(response)
+    result = _construct_lc_result_from_responses_api(response)
 
     assert len(result.generations[0].message.content) == 2
     assert result.generations[0].message.content[0]["text"] == "First part"  # type: ignore
     assert result.generations[0].message.content[1]["text"] == "Second part"  # type: ignore
 
 
-def test__construct_lc_result_from_response_api_refusal_response() -> None:
+def test__construct_lc_result_from_responses_api_refusal_response() -> None:
     """Test a response with a refusal."""
     response = Response(
         id="resp_123",
@@ -1084,7 +1084,7 @@ def test__construct_lc_result_from_response_api_refusal_response() -> None:
         ],
     )
 
-    result = _construct_lc_result_from_response_api(response)
+    result = _construct_lc_result_from_responses_api(response)
 
     assert result.generations[0].message.content == []
     assert (
@@ -1093,7 +1093,7 @@ def test__construct_lc_result_from_response_api_refusal_response() -> None:
     )
 
 
-def test__construct_lc_result_from_response_api_function_call_valid_json() -> None:
+def test__construct_lc_result_from_responses_api_function_call_valid_json() -> None:
     """Test a response with a valid function call."""
     response = Response(
         id="resp_123",
@@ -1114,7 +1114,7 @@ def test__construct_lc_result_from_response_api_function_call_valid_json() -> No
         ],
     )
 
-    result = _construct_lc_result_from_response_api(response)
+    result = _construct_lc_result_from_responses_api(response)
 
     msg: AIMessage = cast(AIMessage, result.generations[0].message)
     assert len(msg.tool_calls) == 1
@@ -1131,7 +1131,7 @@ def test__construct_lc_result_from_response_api_function_call_valid_json() -> No
     )
 
 
-def test__construct_lc_result_from_response_api_function_call_invalid_json() -> None:
+def test__construct_lc_result_from_responses_api_function_call_invalid_json() -> None:
     """Test a response with an invalid JSON function call."""
     response = Response(
         id="resp_123",
@@ -1153,7 +1153,7 @@ def test__construct_lc_result_from_response_api_function_call_invalid_json() ->
         ],
     )
 
-    result = _construct_lc_result_from_response_api(response)
+    result = _construct_lc_result_from_responses_api(response)
 
     msg: AIMessage = cast(AIMessage, result.generations[0].message)
     assert len(msg.invalid_tool_calls) == 1
@@ -1168,7 +1168,7 @@ def test__construct_lc_result_from_response_api_function_call_invalid_json() ->
     assert _FUNCTION_CALL_IDS_MAP_KEY in result.generations[0].message.additional_kwargs
 
 
-def test__construct_lc_result_from_response_api_complex_response() -> None:
+def test__construct_lc_result_from_responses_api_complex_response() -> None:
     """Test a complex response with multiple output types."""
     response = Response(
         id="resp_123",
@@ -1206,7 +1206,7 @@ def test__construct_lc_result_from_response_api_complex_response() -> None:
         user="user_123",
     )
 
-    result = _construct_lc_result_from_response_api(response)
+    result = _construct_lc_result_from_responses_api(response)
 
     # Check message content
     assert result.generations[0].message.content == [
@@ -1235,7 +1235,7 @@ def test__construct_lc_result_from_response_api_complex_response() -> None:
     assert result.generations[0].message.response_metadata["user"] == "user_123"
 
 
-def test__construct_lc_result_from_response_api_no_usage_metadata() -> None:
+def test__construct_lc_result_from_responses_api_no_usage_metadata() -> None:
     """Test a response without usage metadata."""
     response = Response(
         id="resp_123",
@@ -1261,12 +1261,12 @@ def test__construct_lc_result_from_response_api_no_usage_metadata() -> None:
         # No usage field
     )
 
-    result = _construct_lc_result_from_response_api(response)
+    result = _construct_lc_result_from_responses_api(response)
 
     assert cast(AIMessage, result.generations[0].message).usage_metadata is None
 
 
-def test__construct_lc_result_from_response_api_web_search_response() -> None:
+def test__construct_lc_result_from_responses_api_web_search_response() -> None:
     """Test a response with web search output."""
     from openai.types.responses.response_function_web_search import (
         ResponseFunctionWebSearch,
@@ -1287,7 +1287,7 @@ def test__construct_lc_result_from_response_api_web_search_response() -> None:
         ],
     )
 
-    result = _construct_lc_result_from_response_api(response)
+    result = _construct_lc_result_from_responses_api(response)
 
     assert "tool_outputs" in result.generations[0].message.additional_kwargs
     assert len(result.generations[0].message.additional_kwargs["tool_outputs"]) == 1
@@ -1305,7 +1305,7 @@ def test__construct_lc_result_from_response_api_web_search_response() -> None:
     )
 
 
-def test__construct_lc_result_from_response_api_file_search_response() -> None:
+def test__construct_lc_result_from_responses_api_file_search_response() -> None:
     """Test a response with file search output."""
     response = Response(
         id="resp_123",
@@ -1334,7 +1334,7 @@ def test__construct_lc_result_from_response_api_file_search_response() -> None:
         ],
     )
 
-    result = _construct_lc_result_from_response_api(response)
+    result = _construct_lc_result_from_responses_api(response)
 
     assert "tool_outputs" in result.generations[0].message.additional_kwargs
     assert len(result.generations[0].message.additional_kwargs["tool_outputs"]) == 1
@@ -1375,7 +1375,7 @@ def test__construct_lc_result_from_response_api_file_search_response() -> None:
     )
 
 
-def test__construct_lc_result_from_response_api_mixed_search_responses() -> None:
+def test__construct_lc_result_from_responses_api_mixed_search_responses() -> None:
     """Test a response with both web search and file search outputs."""
 
     response = Response(
@@ -1418,7 +1418,7 @@ def test__construct_lc_result_from_response_api_mixed_search_responses() -> None
         ],
     )
 
-    result = _construct_lc_result_from_response_api(response)
+    result = _construct_lc_result_from_responses_api(response)
 
     # Check message content
     assert result.generations[0].message.content == [
@@ -1449,14 +1449,14 @@ def test__construct_lc_result_from_response_api_mixed_search_responses() -> None
     assert file_search["results"][0]["filename"] == "example.py"
 
 
-def test__construct_response_api_input_human_message_with_text_blocks_conversion() -> (
+def test__construct_responses_api_input_human_message_with_text_blocks_conversion() -> (
     None
 ):
     """Test that human messages with text blocks are properly converted."""
     messages: list = [
         HumanMessage(content=[{"type": "text", "text": "What's in this image?"}])
     ]
-    result = _construct_response_api_input(messages)
+    result = _construct_responses_api_input(messages)
 
     assert len(result) == 1
     assert result[0]["role"] == "user"
@@ -1466,7 +1466,7 @@ def test__construct_response_api_input_human_message_with_text_blocks_conversion
     assert result[0]["content"][0]["text"] == "What's in this image?"
 
 
-def test__construct_response_api_input_human_message_with_image_url_conversion() -> (
+def test__construct_responses_api_input_human_message_with_image_url_conversion() -> (
     None
 ):
     """Test that human messages with image_url blocks are properly converted."""
@@ -1484,7 +1484,7 @@ def test__construct_response_api_input_human_message_with_image_url_conversion()
             ]
         )
     ]
-    result = _construct_response_api_input(messages)
+    result = _construct_responses_api_input(messages)
 
     assert len(result) == 1
     assert result[0]["role"] == "user"
@@ -1501,7 +1501,7 @@ def test__construct_response_api_input_human_message_with_image_url_conversion()
     assert result[0]["content"][1]["detail"] == "high"
 
 
-def test__construct_response_api_input_ai_message_with_tool_calls() -> None:
+def test__construct_responses_api_input_ai_message_with_tool_calls() -> None:
     """Test that AI messages with tool calls are properly converted."""
     tool_calls = [
         {
@@ -1521,7 +1521,7 @@ def test__construct_response_api_input_ai_message_with_tool_calls() -> None:
         additional_kwargs={_FUNCTION_CALL_IDS_MAP_KEY: function_call_ids},
     )
 
-    result = _construct_response_api_input([ai_message])
+    result = _construct_responses_api_input([ai_message])
 
     assert len(result) == 1
     assert result[0]["type"] == "function_call"
@@ -1531,7 +1531,9 @@ def test__construct_response_api_input_ai_message_with_tool_calls() -> None:
     assert result[0]["id"] == "func_456"
 
 
-def test__construct_response_api_input_ai_message_with_tool_calls_and_content() -> None:
+def test__construct_responses_api_input_ai_message_with_tool_calls_and_content() -> (
+    None
+):
     """Test that AI messages with both tool calls and content are properly converted."""
     tool_calls = [
         {
@@ -1551,7 +1553,7 @@ def test__construct_response_api_input_ai_message_with_tool_calls_and_content()
         additional_kwargs={_FUNCTION_CALL_IDS_MAP_KEY: function_call_ids},
     )
 
-    result = _construct_response_api_input([ai_message])
+    result = _construct_responses_api_input([ai_message])
 
     assert len(result) == 2
 
@@ -1567,7 +1569,7 @@ def test__construct_response_api_input_ai_message_with_tool_calls_and_content()
     assert result[1]["id"] == "func_456"
 
 
-def test__construct_response_api_input_missing_function_call_ids() -> None:
+def test__construct_responses_api_input_missing_function_call_ids() -> None:
     """Test AI messages with tool calls but missing function call IDs raise an error."""
     tool_calls = [
         {
@@ -1581,10 +1583,10 @@ def test__construct_response_api_input_missing_function_call_ids() -> None:
     ai_message = AIMessage(content="", tool_calls=tool_calls)
 
     with pytest.raises(ValueError):
-        _construct_response_api_input([ai_message])
+        _construct_responses_api_input([ai_message])
 
 
-def test__construct_response_api_input_tool_message_conversion() -> None:
+def test__construct_responses_api_input_tool_message_conversion() -> None:
     """Test that tool messages are properly converted to function_call_output."""
     messages = [
         ToolMessage(
@@ -1593,7 +1595,7 @@ def test__construct_response_api_input_tool_message_conversion() -> None:
         )
     ]
 
-    result = _construct_response_api_input(messages)
+    result = _construct_responses_api_input(messages)
 
     assert len(result) == 1
     assert result[0]["type"] == "function_call_output"
@@ -1601,7 +1603,7 @@ def test__construct_response_api_input_tool_message_conversion() -> None:
     assert result[0]["call_id"] == "call_123"
 
 
-def test__construct_response_api_input_multiple_message_types() -> None:
+def test__construct_responses_api_input_multiple_message_types() -> None:
     """Test conversion of a conversation with multiple message types."""
     messages = [
         SystemMessage(content="You are a helpful assistant."),
@@ -1637,7 +1639,7 @@ def test__construct_response_api_input_multiple_message_types() -> None:
     ]
     messages_copy = [m.copy(deep=True) for m in messages]
 
-    result = _construct_response_api_input(messages)
+    result = _construct_responses_api_input(messages)
 
     assert len(result) == len(messages)