openai[patch]: expose model request payload (#23287)

![Screenshot 2024-06-21 at 3 12 12
PM](https://github.com/langchain-ai/langchain/assets/22008038/6243a01f-1ef6-4085-9160-2844d9f2b683)

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

@@ -481,11 +481,10 @@ class BaseChatOpenAI(BaseChatModel):
         run_manager: Optional[CallbackManagerForLLMRun] = None,
         **kwargs: Any,
     ) -> Iterator[ChatGenerationChunk]:
-        message_dicts, params = self._create_message_dicts(messages, stop)
+        kwargs["stream"] = True
-        params = {**params, **kwargs, "stream": True}
+        payload = self._get_request_payload(messages, stop=stop, **kwargs)
-
         default_chunk_class: Type[BaseMessageChunk] = AIMessageChunk
-        with self.client.create(messages=message_dicts, **params) as response:
+        with self.client.create(**payload) as response:
             for chunk in response:
                 if not isinstance(chunk, dict):
                     chunk = chunk.model_dump()
@@ -544,19 +543,25 @@ class BaseChatOpenAI(BaseChatModel):
                 messages, stop=stop, run_manager=run_manager, **kwargs
             )
             return generate_from_stream(stream_iter)
-        message_dicts, params = self._create_message_dicts(messages, stop)
+        payload = self._get_request_payload(messages, stop=stop, **kwargs)
-        params = {**params, **kwargs}
+        response = self.client.create(**payload)
-        response = self.client.create(messages=message_dicts, **params)
         return self._create_chat_result(response)
 
-    def _create_message_dicts(
+    def _get_request_payload(
-        self, messages: List[BaseMessage], stop: Optional[List[str]]
+        self,
-    ) -> Tuple[List[Dict[str, Any]], Dict[str, Any]]:
+        input_: LanguageModelInput,
-        params = self._default_params
+        *,
+        stop: Optional[List[str]] = None,
+        **kwargs: Any,
+    ) -> dict:
+        messages = self._convert_input(input_).to_messages()
         if stop is not None:
-            params["stop"] = stop
+            kwargs["stop"] = stop
-        message_dicts = [_convert_message_to_dict(m) for m in messages]
+        return {
-        return message_dicts, params
+            "messages": [_convert_message_to_dict(m) for m in messages],
+            **self._default_params,
+            **kwargs,
+        }
 
     def _create_chat_result(
         self, response: Union[dict, openai.BaseModel]
@@ -600,11 +605,10 @@ class BaseChatOpenAI(BaseChatModel):
         run_manager: Optional[AsyncCallbackManagerForLLMRun] = None,
         **kwargs: Any,
     ) -> AsyncIterator[ChatGenerationChunk]:
-        message_dicts, params = self._create_message_dicts(messages, stop)
+        kwargs["stream"] = True
-        params = {**params, **kwargs, "stream": True}
+        payload = self._get_request_payload(messages, stop=stop, **kwargs)
-
         default_chunk_class: Type[BaseMessageChunk] = AIMessageChunk
-        response = await self.async_client.create(messages=message_dicts, **params)
+        response = await self.async_client.create(**payload)
         async with response:
             async for chunk in response:
                 if not isinstance(chunk, dict):
@@ -666,10 +670,8 @@ class BaseChatOpenAI(BaseChatModel):
                 messages, stop=stop, run_manager=run_manager, **kwargs
             )
             return await agenerate_from_stream(stream_iter)
-
+        payload = self._get_request_payload(messages, stop=stop, **kwargs)
-        message_dicts, params = self._create_message_dicts(messages, stop)
+        response = await self.async_client.create(**payload)
-        params = {**params, **kwargs}
-        response = await self.async_client.create(messages=message_dicts, **params)
         return self._create_chat_result(response)
 
     @property