diff --git a/docs/docs/integrations/callbacks/streamlit.md b/docs/docs/integrations/callbacks/streamlit.md
index 47b39cfd0b6..ad42d462d00 100644
--- a/docs/docs/integrations/callbacks/streamlit.md
+++ b/docs/docs/integrations/callbacks/streamlit.md
@@ -28,7 +28,7 @@ You can run `streamlit hello` to load a sample app and validate your install suc
 To create a `StreamlitCallbackHandler`, you just need to provide a parent container to render the output.
 
 ```python
-from langchain.callbacks import StreamlitCallbackHandler
+from langchain_community.callbacks import StreamlitCallbackHandler
 import streamlit as st
 
 st_callback = StreamlitCallbackHandler(st.container())
@@ -44,23 +44,26 @@ agent in your Streamlit app and simply pass the `StreamlitCallbackHandler` to `a
 thoughts and actions live in your app.
 
 ```python
-from langchain_openai import OpenAI
-from langchain.agents import AgentType, initialize_agent, load_tools
-from langchain_community.callbacks import StreamlitCallbackHandler
 import streamlit as st
+from langchain import hub
+from langchain.agents import AgentExecutor, create_react_agent, load_tools
+from langchain_community.callbacks import StreamlitCallbackHandler
+from langchain_openai import OpenAI
 
 llm = OpenAI(temperature=0, streaming=True)
 tools = load_tools(["ddg-search"])
-agent = initialize_agent(
-    tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True
-)
+prompt = hub.pull("hwchase17/react")
+agent = create_react_agent(llm, tools, prompt)
+agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
 
 if prompt := st.chat_input():
     st.chat_message("user").write(prompt)
     with st.chat_message("assistant"):
         st_callback = StreamlitCallbackHandler(st.container())
-        response = agent.run(prompt, callbacks=[st_callback])
-        st.write(response)
+        response = agent_executor.invoke(
+            {"input": prompt}, {"callbacks": [st_callback]}
+        )
+        st.write(response["output"])
 ```
 
 **Note:** You will need to set `OPENAI_API_KEY` for the above app code to run successfully.