community[patch]: Add ToolMessage for ChatZhipuAI (#25547)

- **Description:** Add ToolMessage for `ChatZhipuAI` to solve the issue
#25490

libs/community/langchain_community/chat_models/zhipuai.py

@@ -42,6 +42,7 @@ from langchain_core.messages import (
     HumanMessageChunk,
     SystemMessage,
     SystemMessageChunk,
+    ToolMessage,
 )
 from langchain_core.output_parsers.base import OutputParserLike
 from langchain_core.output_parsers.openai_tools import (
@@ -150,6 +151,15 @@ def _convert_dict_to_message(dct: Dict[str, Any]) -> BaseMessage:
         if tool_calls is not None:
             additional_kwargs["tool_calls"] = tool_calls
         return AIMessage(content=content, additional_kwargs=additional_kwargs)
+    if role == "tool":
+        additional_kwargs = {}
+        if "name" in dct:
+            additional_kwargs["name"] = dct["name"]
+        return ToolMessage(
+            content=content,
+            tool_call_id=dct.get("tool_call_id"),  # type: ignore[arg-type]
+            additional_kwargs=additional_kwargs,
+        )
     return ChatMessage(role=role, content=content)  # type: ignore[arg-type]
 
 
@@ -171,6 +181,13 @@ def _convert_message_to_dict(message: BaseMessage) -> Dict[str, Any]:
         message_dict = {"role": "user", "content": message.content}
     elif isinstance(message, AIMessage):
         message_dict = {"role": "assistant", "content": message.content}
+    elif isinstance(message, ToolMessage):
+        message_dict = {
+            "role": "tool",
+            "content": message.content,
+            "tool_call_id": message.tool_call_id,
+            "name": message.name or message.additional_kwargs.get("name"),
+        }
     else:
         raise TypeError(f"Got unknown type '{message.__class__.__name__}'.")
     return message_dict

libs/community/tests/unit_tests/chat_models/test_zhipuai.py

@@ -1,8 +1,12 @@
 """Test ZhipuAI Chat API wrapper"""
 
 import pytest
+from langchain_core.messages import ToolMessage
 
-from langchain_community.chat_models.zhipuai import ChatZhipuAI
+from langchain_community.chat_models.zhipuai import (
+    ChatZhipuAI,
+    _convert_message_to_dict,
+)
 
 
 @pytest.mark.requires("httpx", "httpx_sse", "jwt")
@@ -11,3 +15,15 @@ def test_zhipuai_model_param() -> None:
     assert llm.model_name == "foo"
     llm = ChatZhipuAI(api_key="test", model_name="foo")  # type: ignore[call-arg]
     assert llm.model_name == "foo"
+
+
+def test__convert_message_to_dict_with_tool() -> None:
+    message = ToolMessage(name="foo", content="bar", tool_call_id="abc123")
+    result = _convert_message_to_dict(message)
+    expected_output = {
+        "name": "foo",
+        "content": "bar",
+        "tool_call_id": "abc123",
+        "role": "tool",
+    }
+    assert result == expected_output