use_responses_api

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

@@ -536,6 +536,14 @@ class BaseChatOpenAI(BaseChatModel):
     invocation. 
     """
 
+    use_responses_api: Optional[bool] = None
+    """Whether to use the Responses API instead of the Chat API.
+
+    If not specified then will be inferred based on invocation params.
+
+    .. versionadded:: 0.3.9
+    """
+
     model_config = ConfigDict(populate_by_name=True)
 
     @model_validator(mode="before")
@@ -871,13 +879,19 @@ 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_responses_api(payload):
+        elif self._use_responses_api(payload):
             response = self.root_client.responses.create(**payload)
             return _construct_lc_result_from_responses_api(response)
         else:
             response = self.client.create(**payload)
         return self._create_chat_result(response, generation_info)
 
+    def _use_responses_api(self, payload: dict) -> bool:
+        if isinstance(self.use_responses_api, bool):
+            return self.use_responses_api
+        else:
+            return _use_responses_api(payload)
+
     def _get_request_payload(
         self,
         input_: LanguageModelInput,
@@ -890,7 +904,7 @@ class BaseChatOpenAI(BaseChatModel):
             kwargs["stop"] = stop
 
         payload = {**self._default_params, **kwargs}
-        if _use_responses_api(payload):
+        if self._use_responses_api(payload):
             payload = _construct_responses_api_payload(messages, payload)
         else:
             payload["messages"] = [_convert_message_to_dict(m) for m in messages]
@@ -933,6 +947,8 @@ class BaseChatOpenAI(BaseChatModel):
             "model_name": response_dict.get("model", self.model_name),
             "system_fingerprint": response_dict.get("system_fingerprint", ""),
         }
+        if "id" in response_dict:
+            llm_output["id"] = response_dict["id"]
 
         if isinstance(response, openai.BaseModel) and getattr(
             response, "choices", None
@@ -1045,7 +1061,7 @@ 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_responses_api(payload):
+        elif self._use_responses_api(payload):
             response = await self.root_async_client.responses.create(**payload)
             return _construct_lc_result_from_responses_api(response)
         else:
@@ -2146,7 +2162,7 @@ class ChatOpenAI(BaseChatOpenAI):  # type: ignore[override]
         self, *args: Any, stream_usage: Optional[bool] = None, **kwargs: Any
     ) -> Iterator[ChatGenerationChunk]:
         """Set default stream_options."""
-        if _use_responses_api(kwargs):
+        if self._use_responses_api(kwargs):
             return super()._stream_responses(*args, **kwargs)
         else:
             stream_usage = self._should_stream_usage(stream_usage, **kwargs)
@@ -2164,7 +2180,7 @@ class ChatOpenAI(BaseChatOpenAI):  # type: ignore[override]
         self, *args: Any, stream_usage: Optional[bool] = None, **kwargs: Any
     ) -> AsyncIterator[ChatGenerationChunk]:
         """Set default stream_options."""
-        if _use_responses_api(kwargs):
+        if self._use_responses_api(kwargs):
             async for chunk in super()._astream_responses(*args, **kwargs):
                 yield chunk
         else:

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

@@ -1,7 +1,7 @@
 """Test Responses API usage."""
 
 import os
-from typing import Optional
+from typing import Any, Optional, cast
 
 import pytest
 from langchain_core.messages import (
@@ -114,6 +114,42 @@ async def test_web_search_async() -> None:
     _check_response(full)
 
 
+def test_function_calling() -> None:
+    def multiply(x: int, y: int) -> int:
+        """return x * y"""
+        return x * y
+
+    llm = ChatOpenAI(model="gpt-4o-mini")
+    bound_llm = llm.bind_tools([multiply, {"type": "web_search_preview"}])
+    ai_msg = cast(AIMessage, bound_llm.invoke("whats 5 * 4"))
+    assert len(ai_msg.tool_calls) == 1
+    assert ai_msg.tool_calls[0]["name"] == "multiply"
+    assert set(ai_msg.tool_calls[0]["args"]) == {"x", "y"}
+
+    full: Any = None
+    for chunk in bound_llm.stream("whats 5 * 4"):
+        assert isinstance(chunk, AIMessageChunk)
+        full = chunk if full is None else full + chunk
+    assert len(full.tool_calls) == 1
+    assert full.tool_calls[0]["name"] == "multiply"
+    assert set(full.tool_calls[0]["args"]) == {"x", "y"}
+
+    response = bound_llm.invoke("whats some good news from today")
+    _check_response(response)
+
+
+def test_stateful_api() -> None:
+    llm = ChatOpenAI(model="gpt-4o-mini", use_responses_api=True)
+    response = llm.invoke("how are you, my name is Bobo")
+    assert "id" in response.response_metadata
+
+    second_response = llm.invoke(
+        "what's my name", previous_response_id=response.response_metadata["id"]
+    )
+    assert isinstance(second_response.content, list)
+    assert "bobo" in second_response.content[0]["text"].lower()  # type: ignore
+
+
 def test_file_search() -> None:
     pytest.skip()  # TODO: set up infra
     llm = ChatOpenAI(model="gpt-4o-mini")