openai[patch]: add attribute to always use previous_response_id (#31734)

libs/langchain/tests/unit_tests/chat_models/test_base.py

@@ -138,6 +138,7 @@ def test_configurable() -> None:
             "extra_body": None,
             "include_response_headers": False,
             "stream_usage": False,
+            "use_previous_response_id": False,
             "use_responses_api": None,
         },
         "kwargs": {

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

@@ -607,6 +607,40 @@ class BaseChatOpenAI(BaseChatModel):
     .. versionadded:: 0.3.24
     """
 
+    use_previous_response_id: bool = False
+    """If True, always pass ``previous_response_id`` using the ID of the most recent
+    response. Responses API only.
+
+    Input messages up to the most recent response will be dropped from request
+    payloads.
+
+    For example, the following two are equivalent:
+
+    .. code-block:: python
+
+        llm = ChatOpenAI(
+            model="o4-mini",
+            use_previous_response_id=True,
+        )
+        llm.invoke(
+            [
+                HumanMessage("Hello"),
+                AIMessage("Hi there!", response_metadata={"id": "resp_123"}),
+                HumanMessage("How are you?"),
+            ]
+        )
+
+    .. code-block:: python
+
+        llm = ChatOpenAI(
+            model="o4-mini",
+            use_responses_api=True,
+        )
+        llm.invoke([HumanMessage("How are you?")], previous_response_id="resp_123")
+
+    .. versionadded:: 0.3.26
+    """
+
     use_responses_api: Optional[bool] = None
     """Whether to use the Responses API instead of the Chat API.
 
@@ -1081,6 +1115,8 @@ class BaseChatOpenAI(BaseChatModel):
             return True
         elif self.truncation is not None:
             return True
+        elif self.use_previous_response_id:
+            return True
         else:
             return _use_responses_api(payload)
 
@@ -1097,6 +1133,13 @@ class BaseChatOpenAI(BaseChatModel):
 
         payload = {**self._default_params, **kwargs}
         if self._use_responses_api(payload):
+            if self.use_previous_response_id:
+                last_messages, previous_response_id = _get_last_messages(messages)
+                payload_to_use = last_messages if previous_response_id else messages
+                if previous_response_id:
+                    payload["previous_response_id"] = previous_response_id
+                payload = _construct_responses_api_payload(payload_to_use, payload)
+            else:
                 payload = _construct_responses_api_payload(messages, payload)
         else:
             payload["messages"] = [_convert_message_to_dict(m) for m in messages]
@@ -3202,6 +3245,30 @@ def _use_responses_api(payload: dict) -> bool:
     return bool(uses_builtin_tools or responses_only_args.intersection(payload))
 
 
+def _get_last_messages(
+    messages: Sequence[BaseMessage],
+) -> tuple[Sequence[BaseMessage], Optional[str]]:
+    """
+    Return
+        1. Every message after the most-recent AIMessage that has a non-empty
+           ``response_metadata["id"]`` (may be an empty list),
+        2. That id.
+
+    If the most-recent AIMessage does not have an id (or there is no
+    AIMessage at all) the entire conversation is returned together with ``None``.
+    """
+    for i in range(len(messages) - 1, -1, -1):
+        msg = messages[i]
+        if isinstance(msg, AIMessage):
+            response_id = msg.response_metadata.get("id")
+            if response_id:
+                return messages[i + 1 :], response_id
+            else:
+                return messages, None
+
+    return messages, None
+
+
 def _construct_responses_api_payload(
     messages: Sequence[BaseMessage], payload: dict
 ) -> dict:

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

@@ -12,6 +12,7 @@ from langchain_core.load import dumps, loads
 from langchain_core.messages import (
     AIMessage,
     AIMessageChunk,
+    BaseMessage,
     FunctionMessage,
     HumanMessage,
     InvalidToolCall,
@@ -59,6 +60,7 @@ from langchain_openai.chat_models.base import (
     _convert_to_openai_response_format,
     _create_usage_metadata,
     _format_message_content,
+    _get_last_messages,
     _oai_structured_outputs_parser,
 )
 
@@ -2151,3 +2153,102 @@ def test_compat() -> None:
     message_v03_output = _convert_to_v03_ai_message(message)
     assert message_v03_output == message_v03
     assert message_v03_output is not message_v03
+
+
+def test_get_last_messages() -> None:
+    messages: list[BaseMessage] = [HumanMessage("Hello")]
+    last_messages, previous_response_id = _get_last_messages(messages)
+    assert last_messages == [HumanMessage("Hello")]
+    assert previous_response_id is None
+
+    messages = [
+        HumanMessage("Hello"),
+        AIMessage("Hi there!", response_metadata={"id": "resp_123"}),
+        HumanMessage("How are you?"),
+    ]
+
+    last_messages, previous_response_id = _get_last_messages(messages)
+    assert last_messages == [HumanMessage("How are you?")]
+    assert previous_response_id == "resp_123"
+
+    messages = [
+        HumanMessage("Hello"),
+        AIMessage("Hi there!", response_metadata={"id": "resp_123"}),
+        HumanMessage("How are you?"),
+        AIMessage("Well thanks.", response_metadata={"id": "resp_456"}),
+        HumanMessage("Great."),
+    ]
+    last_messages, previous_response_id = _get_last_messages(messages)
+    assert last_messages == [HumanMessage("Great.")]
+    assert previous_response_id == "resp_456"
+
+    messages = [
+        HumanMessage("Hello"),
+        AIMessage("Hi there!", response_metadata={"id": "resp_123"}),
+        HumanMessage("What's the weather?"),
+        AIMessage(
+            "",
+            response_metadata={"id": "resp_456"},
+            tool_calls=[
+                {
+                    "type": "tool_call",
+                    "name": "get_weather",
+                    "id": "call_123",
+                    "args": {"location": "San Francisco"},
+                }
+            ],
+        ),
+        ToolMessage("It's sunny.", tool_call_id="call_123"),
+    ]
+    last_messages, previous_response_id = _get_last_messages(messages)
+    assert last_messages == [ToolMessage("It's sunny.", tool_call_id="call_123")]
+    assert previous_response_id == "resp_456"
+
+    messages = [
+        HumanMessage("Hello"),
+        AIMessage("Hi there!", response_metadata={"id": "resp_123"}),
+        HumanMessage("How are you?"),
+        AIMessage("Well thanks.", response_metadata={"id": "resp_456"}),
+        HumanMessage("Good."),
+        HumanMessage("Great."),
+    ]
+    last_messages, previous_response_id = _get_last_messages(messages)
+    assert last_messages == [HumanMessage("Good."), HumanMessage("Great.")]
+    assert previous_response_id == "resp_456"
+
+    messages = [
+        HumanMessage("Hello"),
+        AIMessage("Hi there!", response_metadata={"id": "resp_123"}),
+    ]
+    last_messages, response_id = _get_last_messages(messages)
+    assert last_messages == []
+    assert response_id == "resp_123"
+
+
+def test_get_request_payload_use_previous_response_id() -> None:
+    # Default - don't use previous_response ID
+    llm = ChatOpenAI(model="o4-mini", use_responses_api=True)
+    messages = [
+        HumanMessage("Hello"),
+        AIMessage("Hi there!", response_metadata={"id": "resp_123"}),
+        HumanMessage("How are you?"),
+    ]
+    payload = llm._get_request_payload(messages)
+    assert "previous_response_id" not in payload
+    assert len(payload["input"]) == 3
+
+    # Use previous response ID
+    llm = ChatOpenAI(
+        model="o4-mini",
+        # Specifying use_previous_response_id automatically engages Responses API
+        use_previous_response_id=True,
+    )
+    payload = llm._get_request_payload(messages)
+    assert payload["previous_response_id"] == "resp_123"
+    assert len(payload["input"]) == 1
+
+    # Check single message
+    messages = [HumanMessage("Hello")]
+    payload = llm._get_request_payload(messages)
+    assert "previous_response_id" not in payload
+    assert len(payload["input"]) == 1