diff --git a/docs/docs/integrations/memory/streamlit_chat_message_history.ipynb b/docs/docs/integrations/memory/streamlit_chat_message_history.ipynb
index 21de8c78ac4..987d6aeccce 100644
--- a/docs/docs/integrations/memory/streamlit_chat_message_history.ipynb
+++ b/docs/docs/integrations/memory/streamlit_chat_message_history.ipynb
@@ -10,7 +10,6 @@
     ">[Streamlit](https://docs.streamlit.io/) is an open-source Python library that makes it easy to create and share beautiful, \n",
     "custom web apps for machine learning and data science.\n",
     "\n",
-    "\n",
     "This notebook goes over how to store and use chat message history in a `Streamlit` app. `StreamlitChatMessageHistory` will store messages in\n",
     "[Streamlit session state](https://docs.streamlit.io/library/api-reference/session-state)\n",
     "at the specified `key=`. The default key is `\"langchain_messages\"`.\n",
@@ -20,6 +19,12 @@
     "- For more on Streamlit check out their\n",
     "[getting started documentation](https://docs.streamlit.io/library/get-started).\n",
     "\n",
+    "The integration lives in the `langchain-community` package, so we need to install that. We also need to install `streamlit`.\n",
+    "\n",
+    "```\n",
+    "pip install -U langchain-community streamlit\n",
+    "```\n",
+    "\n",
     "You can see the [full app example running here](https://langchain-st-memory.streamlit.app/), and more examples in\n",
     "[github.com/langchain-ai/streamlit-agent](https://github.com/langchain-ai/streamlit-agent)."
    ]
@@ -31,7 +36,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain.memory import StreamlitChatMessageHistory\n",
+    "from langchain_community.chat_message_histories import StreamlitChatMessageHistory\n",
     "\n",
     "history = StreamlitChatMessageHistory(key=\"chat_messages\")\n",
     "\n",
@@ -54,7 +59,9 @@
    "id": "b60dc735",
    "metadata": {},
    "source": [
-    "You can integrate `StreamlitChatMessageHistory` into `ConversationBufferMemory` and chains or agents as usual. The history will be persisted across re-runs of the Streamlit app within a given user session. A given `StreamlitChatMessageHistory` will NOT be persisted or shared across user sessions."
+    "We can easily combine this message history class with [LCEL Runnables](https://python.langchain.com/docs/expression_language/how_to/message_history).\n",
+    "\n",
+    "The history will be persisted across re-runs of the Streamlit app within a given user session. A given `StreamlitChatMessageHistory` will NOT be persisted or shared across user sessions."
    ]
   },
   {
@@ -64,13 +71,11 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain.memory import ConversationBufferMemory\n",
     "from langchain_community.chat_message_histories import StreamlitChatMessageHistory\n",
     "\n",
     "# Optionally, specify your own session_state key for storing messages\n",
     "msgs = StreamlitChatMessageHistory(key=\"special_app_key\")\n",
     "\n",
-    "memory = ConversationBufferMemory(memory_key=\"history\", chat_memory=msgs)\n",
     "if len(msgs.messages) == 0:\n",
     "    msgs.add_ai_message(\"How can I help you?\")"
    ]
@@ -82,19 +87,34 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain.chains import LLMChain\n",
-    "from langchain.prompts import PromptTemplate\n",
-    "from langchain_openai import OpenAI\n",
+    "from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder\n",
+    "from langchain_core.runnables.history import RunnableWithMessageHistory\n",
+    "from langchain_openai import ChatOpenAI\n",
     "\n",
-    "template = \"\"\"You are an AI chatbot having a conversation with a human.\n",
+    "prompt = ChatPromptTemplate.from_messages(\n",
+    "    [\n",
+    "        (\"system\", \"You are an AI chatbot having a conversation with a human.\"),\n",
+    "        MessagesPlaceholder(variable_name=\"history\"),\n",
+    "        (\"human\", \"{question}\"),\n",
+    "    ]\n",
+    ")\n",
     "\n",
-    "{history}\n",
-    "Human: {human_input}\n",
-    "AI: \"\"\"\n",
-    "prompt = PromptTemplate(input_variables=[\"history\", \"human_input\"], template=template)\n",
-    "\n",
-    "# Add the memory to an LLMChain as usual\n",
-    "llm_chain = LLMChain(llm=OpenAI(), prompt=prompt, memory=memory)"
+    "chain = prompt | ChatOpenAI()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "dac3d94f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "chain_with_history = RunnableWithMessageHistory(\n",
+    "    chain,\n",
+    "    lambda session_id: msgs,  # Always return the instance created earlier\n",
+    "    input_messages_key=\"question\",\n",
+    "    history_messages_key=\"history\",\n",
+    ")"
    ]
   },
   {
@@ -121,8 +141,9 @@
     "    st.chat_message(\"human\").write(prompt)\n",
     "\n",
     "    # As usual, new messages are added to StreamlitChatMessageHistory when the Chain is called.\n",
-    "    response = llm_chain.run(prompt)\n",
-    "    st.chat_message(\"ai\").write(response)"
+    "    config = {\"configurable\": {\"session_id\": \"any\"}}\n",
+    "    response = chain_with_history.invoke({\"question\": prompt}, config)\n",
+    "    st.chat_message(\"ai\").write(response.content)"
    ]
   },
   {