diff --git a/src/backend/base/langflow/components/agents/ToolCallingAgent.py b/src/backend/base/langflow/components/agents/ToolCallingAgent.py
index ddc21c3a5..bf40f89f7 100644
--- a/src/backend/base/langflow/components/agents/ToolCallingAgent.py
+++ b/src/backend/base/langflow/components/agents/ToolCallingAgent.py
@@ -1,38 +1,40 @@
-from typing import List, cast
+from typing import List
 
-from langchain.agents import AgentExecutor, BaseSingleActionAgent
 from langchain.agents.tool_calling_agent.base import create_tool_calling_agent
-from langchain_core.messages import BaseMessage, HumanMessage
 from langchain_core.prompts import ChatPromptTemplate
-
-from langflow.custom import Component
-from langflow.io import BoolInput, HandleInput, Output, TextInput
-from langflow.schema import Data
+from langchain.agents import AgentExecutor
+from langchain_core.messages import BaseMessage
 from langflow.schema.message import Message
+from langflow.custom import Component
+from langflow.io import HandleInput, TextInput, BoolInput, Output
+from langflow.schema import Data
 
 
 class ToolCallingAgentComponent(Component):
     display_name: str = "Tool Calling Agent"
-    description: str = "Agent that uses tools. Only models that are compatible with function calling are supported."
-    icon = "Agent"
+    description: str = (
+        "Agent that uses tools. Only models that are compatible with function calling are supported."
+    )
+    icon = "LangChain"
 
     inputs = [
-        HandleInput(
-            name="llm",
-            display_name="LLM",
-            input_types=["LanguageModel"],
+        TextInput(
+            name="system_prompt",
+            display_name="System Prompt",
+            info="System prompt for the agent.",
+            value="You are a helpful assistant",
         ),
-        HandleInput(
-            name="tools",
-            display_name="Tools",
-            input_types=["Tool"],
-            is_list=True,
+        TextInput(
+            name="input_value",
+            display_name="Inputs",
+            info="Input text to pass to the agent.",
         ),
         TextInput(
             name="user_prompt",
             display_name="Prompt",
             info="This prompt must contain 'input' key.",
             value="{input}",
+            advanced=True,
         ),
         BoolInput(
             name="handle_parsing_errors",
@@ -47,10 +49,16 @@ class ToolCallingAgentComponent(Component):
             input_types=["Data"],
             info="Memory to use for the agent.",
         ),
-        TextInput(
-            name="input_value",
-            display_name="Inputs",
-            info="Input text to pass to the agent.",
+        HandleInput(
+            name="tools",
+            display_name="Tools",
+            input_types=["Tool"],
+            is_list=True,
+        ),
+        HandleInput(
+            name="llm",
+            display_name="LLM",
+            input_types=["LanguageModel"],
         ),
     ]
 
@@ -62,7 +70,7 @@ class ToolCallingAgentComponent(Component):
         if "input" not in self.user_prompt:
             raise ValueError("Prompt must contain 'input' key.")
         messages = [
-            ("system", "You are a helpful assistant"),
+            ("system", self.system_prompt),
             (
                 "placeholder",
                 "{chat_history}",
@@ -74,7 +82,7 @@ class ToolCallingAgentComponent(Component):
         agent = create_tool_calling_agent(self.llm, self.tools, prompt)
 
         runnable = AgentExecutor.from_agent_and_tools(
-            agent=cast(BaseSingleActionAgent, agent),
+            agent=agent,
             tools=self.tools,
             verbose=True,
             handle_parsing_errors=self.handle_parsing_errors,
@@ -92,16 +100,9 @@ class ToolCallingAgentComponent(Component):
 
         return Message(text=result_string)
 
-    def convert_chat_history(self, chat_history: List[Message | Data]) -> List[BaseMessage]:
+    def convert_chat_history(self, chat_history: List[Data]) -> List[Dict[str, str]]:
         messages = []
         for item in chat_history:
-            if isinstance(item, (Message, Data)):
-                messages.append(item.to_lc_message())
-            elif isinstance(item, str):
-                messages.append(HumanMessage(content=item))
-            elif isinstance(item, dict) and "sender" in item and "text" in item:
-                messages.append(HumanMessage(content=item["text"], sender=item["sender"]))
-            else:
-                raise ValueError(f"Invalid item ({type(item)}) in chat history: {item}")
-
+            role = "user" if item.sender == "User" else "assistant"
+            messages.append({"role": role, "content": item.text})
         return messages