openai[patch]: pass message name

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

@@ -92,9 +92,10 @@ def _convert_dict_to_message(_dict: Mapping[str, Any]) -> BaseMessage:
         The LangChain message.
     """
     role = _dict.get("role")
+    name = _dict.get("name")
     id_ = _dict.get("id")
     if role == "user":
-        return HumanMessage(content=_dict.get("content", ""), id=id_)
+        return HumanMessage(content=_dict.get("content", ""), id=id_, name=name)
     elif role == "assistant":
         # Fix for azure
         # Also OpenAI returns None for tool invocations
@@ -104,21 +105,24 @@ def _convert_dict_to_message(_dict: Mapping[str, Any]) -> BaseMessage:
             additional_kwargs["function_call"] = dict(function_call)
         if tool_calls := _dict.get("tool_calls"):
             additional_kwargs["tool_calls"] = tool_calls
-        return AIMessage(content=content, additional_kwargs=additional_kwargs, id=id_)
+        return AIMessage(
+            content=content, additional_kwargs=additional_kwargs, name=name, id=id_
+        )
     elif role == "system":
-        return SystemMessage(content=_dict.get("content", ""), id=id_)
+        return SystemMessage(content=_dict.get("content", ""), name=name, id=id_)
     elif role == "function":
         return FunctionMessage(
-            content=_dict.get("content", ""), name=_dict.get("name"), id=id_
+            content=_dict.get("content", ""), name=cast(str, _dict.get("name")), id=id_
         )
     elif role == "tool":
         additional_kwargs = {}
         if "name" in _dict:
             additional_kwargs["name"] = _dict["name"]
         return ToolMessage(
             content=_dict.get("content", ""),
-            tool_call_id=_dict.get("tool_call_id"),
+            tool_call_id=cast(str, _dict.get("tool_call_id")),
             additional_kwargs=additional_kwargs,
+            name=name,
             id=id_,
         )
     else:
@@ -134,13 +138,16 @@ def _convert_message_to_dict(message: BaseMessage) -> dict:
     Returns:
         The dictionary.
     """
-    message_dict: Dict[str, Any]
+    message_dict: Dict[str, Any] = {
+        "content": message.content,
+        "name": message.name,
+    }
     if isinstance(message, ChatMessage):
-        message_dict = {"role": message.role, "content": message.content}
+        message_dict["role"] = message.role
     elif isinstance(message, HumanMessage):
-        message_dict = {"role": "user", "content": message.content}
+        message_dict["role"] = "user"
     elif isinstance(message, AIMessage):
-        message_dict = {"role": "assistant", "content": message.content}
+        message_dict["role"] = "assistant"
         if "function_call" in message.additional_kwargs:
             message_dict["function_call"] = message.additional_kwargs["function_call"]
             # If function call only, content is None not empty string
@@ -152,19 +159,16 @@ def _convert_message_to_dict(message: BaseMessage) -> dict:
             if message_dict["content"] == "":
                 message_dict["content"] = None
     elif isinstance(message, SystemMessage):
-        message_dict = {"role": "system", "content": message.content}
+        message_dict["role"] = "system"
     elif isinstance(message, FunctionMessage):
-        message_dict = {
-            "role": "function",
-            "content": message.content,
-            "name": message.name,
-        }
+        message_dict["role"] = "function"
     elif isinstance(message, ToolMessage):
-        message_dict = {
-            "role": "tool",
-            "content": message.content,
-            "tool_call_id": message.tool_call_id,
-        }
+        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"]
     else:
         raise TypeError(f"Got unknown type {message}")
     if "name" in message.additional_kwargs:

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

@@ -1,4 +1,5 @@
 """Test OpenAI Chat API wrapper."""
+
 import json
 from typing import Any
 from unittest.mock import AsyncMock, MagicMock, patch
@@ -44,20 +45,41 @@ def test__convert_dict_to_message_human() -> None:
     assert result == expected_output
 
 
+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
+
+
 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
 
 
+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
+
+
 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
 
 
+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
+
+
 @pytest.fixture
 def mock_completion() -> dict:
     return {
@@ -71,6 +93,7 @@ def mock_completion() -> dict:
                 "message": {
                     "role": "assistant",
                     "content": "Bar Baz",
+                    "name": "Erick",
                 },
                 "finish_reason": "stop",
             }
@@ -134,3 +157,31 @@ async def mock_create(*args: Any, **kwargs: Any) -> Any:
 def test__get_encoding_model(model: str) -> None:
     ChatOpenAI(model=model)._get_encoding_model()
     return
+
+
+def test_openai_invoke_name(mock_completion: dict) -> None:
+    llm = ChatOpenAI()
+
+    mock_client = MagicMock()
+    mock_client.create.return_value = mock_completion
+
+    with patch.object(
+        llm,
+        "client",
+        mock_client,
+    ):
+        messages = [
+            HumanMessage(content="Foo", name="Katie"),
+        ]
+        res = llm.invoke(messages)
+        call_args, call_kwargs = mock_client.create.call_args
+        assert len(call_args) == 0  # no positional args
+        call_messages = call_kwargs["messages"]
+        assert len(call_messages) == 1
+        assert call_messages[0]["role"] == "user"
+        assert call_messages[0]["content"] == "Foo"
+        assert call_messages[0]["name"] == "Katie"
+
+        # check return type has name
+        assert res.content == "Bar Baz"
+        assert res.name == "Erick"