community: fix CI (#21766)

libs/community/langchain_community/chat_models/tongyi.py

@@ -119,7 +119,7 @@ def convert_dict_to_message(
             AIMessageChunk(
                 content=content,
                 additional_kwargs=additional_kwargs,
-                tool_call_chunks=tool_calls,
+                tool_call_chunks=tool_calls,  # type: ignore[arg-type]
                 id=_dict.get("id"),
             )
             if is_chunk
@@ -143,13 +143,13 @@ def convert_dict_to_message(
         return (
             ToolMessageChunk(
                 content=_dict.get("content", ""),
-                tool_call_id=_dict.get("tool_call_id"),
+                tool_call_id=_dict.get("tool_call_id"),  # type: ignore[arg-type]
                 additional_kwargs=additional_kwargs,
             )
             if is_chunk
             else ToolMessage(
                 content=_dict.get("content", ""),
-                tool_call_id=_dict.get("tool_call_id"),
+                tool_call_id=_dict.get("tool_call_id"),  # type: ignore[arg-type]
                 additional_kwargs=additional_kwargs,
             )
         )

libs/community/tests/integration_tests/chat_models/test_tongyi.py

@@ -151,9 +151,11 @@ class GenerateUsername(BaseModel):
 
 
 def test_tool_use() -> None:
-    llm = ChatTongyi(model="qwen-turbo", temperature=0)
+    llm = ChatTongyi(model="qwen-turbo", temperature=0)  # type: ignore
     llm_with_tool = llm.bind_tools(tools=[GenerateUsername])
-    msgs: List = [HumanMessage("Sally has green hair, what would her username be?")]
+    msgs: List = [
+        HumanMessage(content="Sally has green hair, what would her username be?")
+    ]
     ai_msg = llm_with_tool.invoke(msgs)
     # assert ai_msg is None
     # ai_msg.content = " "
@@ -165,8 +167,8 @@ def test_tool_use() -> None:
     assert "args" in tool_call
 
     tool_msg = ToolMessage(
-        "sally_green_hair",
-        tool_call_id=ai_msg.tool_calls[0]["id"],
+        content="sally_green_hair",
+        tool_call_id=ai_msg.tool_calls[0]["id"],  # type: ignore
         name=ai_msg.tool_calls[0]["name"],
     )
     msgs.extend([ai_msg, tool_msg])
@@ -184,7 +186,7 @@ def test_tool_use() -> None:
     assert isinstance(gathered, AIMessageChunk)
 
     streaming_tool_msg = ToolMessage(
-        "sally_green_hair",
+        content="sally_green_hair",
         name=tool_call["name"],
         tool_call_id=tool_call["id"] if tool_call["id"] else " ",
     )
@@ -194,10 +196,10 @@ def test_tool_use() -> None:
 
 def test_manual_tool_call_msg() -> None:
     """Test passing in manually construct tool call message."""
-    llm = ChatTongyi(model="qwen-turbo", temperature=0)
+    llm = ChatTongyi(model="qwen-turbo", temperature=0)  # type: ignore
     llm_with_tool = llm.bind_tools(tools=[GenerateUsername])
     msgs: List = [
-        HumanMessage("Sally has green hair, what would her username be?"),
+        HumanMessage(content="Sally has green hair, what would her username be?"),
         AIMessage(
             content=" ",
             tool_calls=[
@@ -208,7 +210,7 @@ def test_manual_tool_call_msg() -> None:
                 )
             ],
         ),
-        ToolMessage("sally_green_hair", tool_call_id="foo"),
+        ToolMessage(content="sally_green_hair", tool_call_id="foo"),
     ]
     output: AIMessage = cast(AIMessage, llm_with_tool.invoke(msgs))
     assert output.content