diff --git a/libs/vertexai/langchain_google_vertexai/chat_models.py b/libs/vertexai/langchain_google_vertexai/chat_models.py
index 6383b5ea..b855e976 100644
--- a/libs/vertexai/langchain_google_vertexai/chat_models.py
+++ b/libs/vertexai/langchain_google_vertexai/chat_models.py
@@ -29,6 +29,7 @@
     FunctionMessage,
     HumanMessage,
     SystemMessage,
+    ToolMessage,
 )
 from langchain_core.output_parsers.base import OutputParserLike
 from langchain_core.output_parsers.openai_functions import (
@@ -199,6 +200,16 @@ def _convert_to_parts(message: BaseMessage) -> List[Part]:
                     },
                 )
             ]
+        elif isinstance(message, ToolMessage):
+            role = "function"
+            parts = [
+                Part.from_function_response(
+                    name=message.name,
+                    response={
+                        "content": message.content,
+                    },
+                )
+            ]
         else:
             raise ValueError(
                 f"Unexpected message with type {type(message)} at the position {i}."
@@ -301,7 +312,7 @@ class ChatVertexAI(_VertexAICommon, BaseChatModel):
     "Underlying model name."
     examples: Optional[List[BaseMessage]] = None
     convert_system_message_to_human: bool = False
-    """[Deprecated] Since new Gemini models support setting a System Message, 
+    """[Deprecated] Since new Gemini models support setting a System Message,
     setting this parameter to True is discouraged.
     """
 
diff --git a/libs/vertexai/tests/unit_tests/test_chat_models.py b/libs/vertexai/tests/unit_tests/test_chat_models.py
index 344d7472..9265ad4f 100644
--- a/libs/vertexai/tests/unit_tests/test_chat_models.py
+++ b/libs/vertexai/tests/unit_tests/test_chat_models.py
@@ -9,6 +9,7 @@
 from google.cloud.aiplatform_v1beta1.types import (
     Content,
     FunctionCall,
+    FunctionResponse,
     Part,
 )
 from google.cloud.aiplatform_v1beta1.types import (
@@ -16,8 +17,10 @@
 )
 from langchain_core.messages import (
     AIMessage,
+    FunctionMessage,
     HumanMessage,
     SystemMessage,
+    ToolMessage,
 )
 from vertexai.generative_models import (  # type: ignore
     Candidate,
@@ -184,6 +187,82 @@ def test_parse_history_gemini_converted_message() -> None:
     assert history[1].parts[0].text == text_answer1
 
 
+def test_parse_history_gemini_function() -> None:
+    system_input = "You're supposed to answer math questions."
+    text_question1 = "Which is bigger 2+2 or 2*2?"
+    function_name = "calculator"
+    function_call_1 = {
+        "name": function_name,
+        "arguments": json.dumps({"arg1": "2", "arg2": "2", "op": "+"}),
+    }
+    function_answer1 = json.dumps({"result": 4})
+    function_call_2 = {
+        "name": function_name,
+        "arguments": json.dumps({"arg1": "2", "arg2": "2", "op": "*"}),
+    }
+    function_answer2 = json.dumps({"result": 4})
+    text_answer1 = "They are same"
+
+    system_message = SystemMessage(content=system_input)
+    message1 = HumanMessage(content=text_question1)
+    message2 = AIMessage(
+        content="",
+        additional_kwargs={
+            "function_call": function_call_1,
+        },
+    )
+    message3 = ToolMessage(
+        name="calculator", content=function_answer1, tool_call_id="1"
+    )
+    message4 = AIMessage(
+        content="",
+        additional_kwargs={
+            "function_call": function_call_2,
+        },
+    )
+    message5 = FunctionMessage(name="calculator", content=function_answer2)
+    message6 = AIMessage(content=text_answer1)
+    messages = [
+        system_message,
+        message1,
+        message2,
+        message3,
+        message4,
+        message5,
+        message6,
+    ]
+    system_instructions, history = _parse_chat_history_gemini(messages)
+    assert len(history) == 6
+    assert system_instructions and system_instructions.parts[0].text == system_input
+    assert history[0].role == "user"
+    assert history[0].parts[0].text == text_question1
+
+    assert history[1].role == "model"
+    assert history[1].parts[0].function_call == FunctionCall(
+        name=function_call_1["name"], args=json.loads(function_call_1["arguments"])
+    )
+
+    assert history[2].role == "function"
+    assert history[2].parts[0].function_response == FunctionResponse(
+        name=function_call_1["name"],
+        response={"content": function_answer1},
+    )
+
+    assert history[3].role == "model"
+    assert history[3].parts[0].function_call == FunctionCall(
+        name=function_call_2["name"], args=json.loads(function_call_2["arguments"])
+    )
+
+    assert history[4].role == "function"
+    assert history[2].parts[0].function_response == FunctionResponse(
+        name=function_call_2["name"],
+        response={"content": function_answer2},
+    )
+
+    assert history[5].role == "model"
+    assert history[5].parts[0].text == text_answer1
+
+
 def test_default_params_palm() -> None:
     user_prompt = "Hello"