openai[patch]: [URGENT REGRESSION FIX] Don't fail if tool message alr…

…eady doesn't contain name (langchain-ai#19435)

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---------

Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>

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

@@ -141,14 +141,8 @@ def _convert_message_to_dict(message: BaseMessage) -> dict:
     message_dict: Dict[str, Any] = {
         "content": message.content,
     }
-    if message.name is not None:
-        message_dict["name"] = message.name
-    elif (
-        "name" in message.additional_kwargs
-        and message.additional_kwargs["name"] is not None
-    ):
-        # fall back on additional kwargs for backwards compatibility
-        message_dict["name"] = message.additional_kwargs["name"]
+    if (name := message.name or message.additional_kwargs.get("name")) is not None:
+        message_dict["name"] = name
 
     # populate role and additional message data
     if isinstance(message, ChatMessage):
@@ -175,9 +169,8 @@ def _convert_message_to_dict(message: BaseMessage) -> dict:
         message_dict["role"] = "tool"
         message_dict["tool_call_id"] = message.tool_call_id
 
-        # tool message doesn't have name: https://platform.openai.com/docs/api-reference/chat/create#chat-create-messages
-        if message_dict["name"] is None:
-            del message_dict["name"]
+        supported_props = {"content", "role", "tool_call_id"}
+        message_dict = {k: v for k, v in message_dict.items() if k in supported_props}
     else:
         raise TypeError(f"Got unknown type {message}")
     return message_dict

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

@@ -10,10 +10,14 @@
     FunctionMessage,
     HumanMessage,
     SystemMessage,
+    ToolMessage,
 )
 
 from langchain_openai import ChatOpenAI
-from langchain_openai.chat_models.base import _convert_dict_to_message
+from langchain_openai.chat_models.base import (
+    _convert_dict_to_message,
+    _convert_message_to_dict,
+)
 
 
 def test_openai_model_param() -> None:
@@ -43,41 +47,55 @@ def test__convert_dict_to_message_human() -> None:
     result = _convert_dict_to_message(message)
     expected_output = HumanMessage(content="foo")
     assert result == expected_output
+    assert _convert_message_to_dict(expected_output) == message
 
 
 def test__convert_dict_to_message_human_with_name() -> None:
     message = {"role": "user", "content": "foo", "name": "test"}
     result = _convert_dict_to_message(message)
     expected_output = HumanMessage(content="foo", name="test")
     assert result == expected_output
+    assert _convert_message_to_dict(expected_output) == message
 
 
 def test__convert_dict_to_message_ai() -> None:
     message = {"role": "assistant", "content": "foo"}
     result = _convert_dict_to_message(message)
     expected_output = AIMessage(content="foo")
     assert result == expected_output
+    assert _convert_message_to_dict(expected_output) == message
 
 
 def test__convert_dict_to_message_ai_with_name() -> None:
     message = {"role": "assistant", "content": "foo", "name": "test"}
     result = _convert_dict_to_message(message)
     expected_output = AIMessage(content="foo", name="test")
     assert result == expected_output
+    assert _convert_message_to_dict(expected_output) == message
 
 
 def test__convert_dict_to_message_system() -> None:
     message = {"role": "system", "content": "foo"}
     result = _convert_dict_to_message(message)
     expected_output = SystemMessage(content="foo")
     assert result == expected_output
+    assert _convert_message_to_dict(expected_output) == message
 
 
 def test__convert_dict_to_message_system_with_name() -> None:
     message = {"role": "system", "content": "foo", "name": "test"}
     result = _convert_dict_to_message(message)
     expected_output = SystemMessage(content="foo", name="test")
     assert result == expected_output
+    assert _convert_message_to_dict(expected_output) == message
+
+
+def test__convert_dict_to_message_tool() -> None:
+    message = {"role": "tool", "content": "foo", "tool_call_id": "bar"}
+    result = _convert_dict_to_message(message)
+    expected_output = ToolMessage(content="foo", tool_call_id="bar")
+    assert result == expected_output
+    assert _convert_message_to_dict(expected_output) == message
 
 
 @pytest.fixture