diff --git a/libs/community/langchain_community/chat_models/baidu_qianfan_endpoint.py b/libs/community/langchain_community/chat_models/baidu_qianfan_endpoint.py
index 3a4bb9a69a1..8fbde19764d 100644
--- a/libs/community/langchain_community/chat_models/baidu_qianfan_endpoint.py
+++ b/libs/community/langchain_community/chat_models/baidu_qianfan_endpoint.py
@@ -1,3 +1,4 @@
+import json
 import logging
 import uuid
 from operator import itemgetter
@@ -65,7 +66,7 @@ def convert_message_to_dict(message: BaseMessage) -> dict:
     elif isinstance(message, (FunctionMessage, ToolMessage)):
         message_dict = {
             "role": "function",
-            "content": message.content,
+            "content": _create_tool_content(message.content),
             "name": message.name or message.additional_kwargs.get("name"),
         }
     else:
@@ -74,6 +75,20 @@ def convert_message_to_dict(message: BaseMessage) -> dict:
     return message_dict
 
 
+def _create_tool_content(content: Union[str, List[Union[str, Dict[Any, Any]]]]) -> str:
+    """Convert tool content to dict scheme."""
+    if isinstance(content, str):
+        try:
+            if isinstance(json.loads(content), dict):
+                return content
+            else:
+                return json.dumps({"tool_result": content})
+        except json.JSONDecodeError:
+            return json.dumps({"tool_result": content})
+    else:
+        return json.dumps({"tool_result": content})
+
+
 def _convert_dict_to_message(_dict: Mapping[str, Any]) -> AIMessage:
     content = _dict.get("result", "") or ""
     additional_kwargs: Mapping[str, Any] = {}
diff --git a/libs/community/tests/integration_tests/chat_models/test_baiduqianfan.py b/libs/community/tests/integration_tests/chat_models/test_baiduqianfan.py
index e69de29bb2d..b2d169f9c71 100644
--- a/libs/community/tests/integration_tests/chat_models/test_baiduqianfan.py
+++ b/libs/community/tests/integration_tests/chat_models/test_baiduqianfan.py
@@ -0,0 +1,39 @@
+from langchain_core.messages import AIMessage, HumanMessage, ToolMessage
+from langchain_core.messages.tool import ToolCall
+from langchain_core.tools import tool
+
+from langchain_community.chat_models import QianfanChatEndpoint
+
+
+@tool
+def get_current_weather(location: str, unit: str = "摄氏度") -> str:
+    """获取指定地点的天气"""
+    return f"{location}是晴朗，25{unit}左右。"
+
+
+def test_chat_qianfan_tool_result_to_model() -> None:
+    """Test QianfanChatEndpoint invoke with tool_calling result."""
+    messages = [
+        HumanMessage("上海天气怎么样？"),
+        AIMessage(
+            content=" ",
+            tool_calls=[
+                ToolCall(
+                    name="get_current_weather",
+                    args={"location": "上海", "unit": "摄氏度"},
+                    id="foo",
+                    type="tool_call",
+                ),
+            ],
+        ),
+        ToolMessage(
+            content="上海是晴天，25度左右。",
+            tool_call_id="foo",
+            name="get_current_weather",
+        ),
+    ]
+    chat = QianfanChatEndpoint(model="ERNIE-3.5-8K")  # type: ignore[call-arg]
+    llm_with_tool = chat.bind_tools([get_current_weather])
+    response = llm_with_tool.invoke(messages)
+    assert isinstance(response, AIMessage)
+    print(response.content)  # noqa: T201