diff --git a/docs/docs/integrations/chat/ai21.ipynb b/docs/docs/integrations/chat/ai21.ipynb
index efdb43cab42..38429aa9153 100644
--- a/docs/docs/integrations/chat/ai21.ipynb
+++ b/docs/docs/integrations/chat/ai21.ipynb
@@ -50,18 +50,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "62e0dbc3",
    "metadata": {
     "tags": []
    },
-   "outputs": [],
    "source": [
     "import os\n",
     "from getpass import getpass\n",
     "\n",
     "os.environ[\"AI21_API_KEY\"] = getpass()"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -73,14 +73,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "7c2e19d3-7c58-4470-9e1a-718b27a32056",
    "metadata": {},
-   "outputs": [],
    "source": [
     "# os.environ[\"LANGCHAIN_TRACING_V2\"] = \"true\"\n",
     "# os.environ[\"LANGCHAIN_API_KEY\"] = getpass.getpass(\"Enter your LangSmith API key: \")"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -115,15 +115,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
    "id": "c40756fb-cbf8-4d44-a293-3989d707237e",
    "metadata": {},
-   "outputs": [],
    "source": [
     "from langchain_ai21 import ChatAI21\n",
     "\n",
     "llm = ChatAI21(model=\"jamba-instruct\", temperature=0)"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -135,21 +135,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
    "id": "46b982dc-5d8a-46da-a711-81c03ccd6adc",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "AIMessage(content=\"J'adore programmer.\", id='run-2e8d16d6-a06e-45cb-8d0c-1c8208645033-0')"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
    "source": [
     "messages = [\n",
     "    (\n",
@@ -160,7 +147,9 @@
     "]\n",
     "ai_msg = llm.invoke(messages)\n",
     "ai_msg"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -174,7 +163,6 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
    "id": "39353473fce5dd2e",
    "metadata": {
     "collapsed": false,
@@ -182,18 +170,6 @@
      "outputs_hidden": false
     }
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "AIMessage(content='Ich liebe das Programmieren.', id='run-e1bd82dc-1a7e-4b2e-bde9-ac995929ac0f-0')"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
    "source": [
     "from langchain_core.prompts import ChatPromptTemplate\n",
     "\n",
@@ -215,7 +191,95 @@
     "        \"input\": \"I love programming.\",\n",
     "    }\n",
     ")"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
+  },
+  {
+   "metadata": {},
+   "cell_type": "markdown",
+   "source": "# Tool Calls / Function Calling",
+   "id": "39c0ccd229927eab"
+  },
+  {
+   "metadata": {},
+   "cell_type": "markdown",
+   "source": "This example shows how to use tool calling with AI21 models:",
+   "id": "2bf6b40be07fe2d4"
+  },
+  {
+   "metadata": {},
+   "cell_type": "code",
+   "source": [
+    "import os\n",
+    "from getpass import getpass\n",
+    "\n",
+    "from langchain_ai21.chat_models import ChatAI21\n",
+    "from langchain_core.messages import HumanMessage, SystemMessage, ToolMessage\n",
+    "from langchain_core.tools import tool\n",
+    "from langchain_core.utils.function_calling import convert_to_openai_tool\n",
+    "\n",
+    "os.environ[\"AI21_API_KEY\"] = getpass()\n",
+    "\n",
+    "\n",
+    "@tool\n",
+    "def get_weather(location: str, date: str) -> str:\n",
+    "    \"\"\"“Provide the weather for the specified location on the given date.”\"\"\"\n",
+    "    if location == \"New York\" and date == \"2024-12-05\":\n",
+    "        return \"25 celsius\"\n",
+    "    elif location == \"New York\" and date == \"2024-12-06\":\n",
+    "        return \"27 celsius\"\n",
+    "    elif location == \"London\" and date == \"2024-12-05\":\n",
+    "        return \"22 celsius\"\n",
+    "    return \"32 celsius\"\n",
+    "\n",
+    "\n",
+    "llm = ChatAI21(model=\"jamba-1.5-mini\")\n",
+    "\n",
+    "llm_with_tools = llm.bind_tools([convert_to_openai_tool(get_weather)])\n",
+    "\n",
+    "chat_messages = [\n",
+    "    SystemMessage(\n",
+    "        content=\"You are a helpful assistant. You can use the provided tools \"\n",
+    "        \"to assist with various tasks and provide accurate information\"\n",
+    "    )\n",
+    "]\n",
+    "\n",
+    "human_messages = [\n",
+    "    HumanMessage(\n",
+    "        content=\"What is the forecast for the weather in New York on December 5, 2024?\"\n",
+    "    ),\n",
+    "    HumanMessage(content=\"And what about the 2024-12-06?\"),\n",
+    "    HumanMessage(content=\"OK, thank you.\"),\n",
+    "    HumanMessage(content=\"What is the expected weather in London on December 5, 2024?\"),\n",
+    "]\n",
+    "\n",
+    "\n",
+    "for human_message in human_messages:\n",
+    "    print(f\"User: {human_message.content}\")\n",
+    "    chat_messages.append(human_message)\n",
+    "    response = llm_with_tools.invoke(chat_messages)\n",
+    "    chat_messages.append(response)\n",
+    "    if response.tool_calls:\n",
+    "        tool_call = response.tool_calls[0]\n",
+    "        if tool_call[\"name\"] == \"get_weather\":\n",
+    "            weather = get_weather.invoke(\n",
+    "                {\n",
+    "                    \"location\": tool_call[\"args\"][\"location\"],\n",
+    "                    \"date\": tool_call[\"args\"][\"date\"],\n",
+    "                }\n",
+    "            )\n",
+    "            chat_messages.append(\n",
+    "                ToolMessage(content=weather, tool_call_id=tool_call[\"id\"])\n",
+    "            )\n",
+    "            llm_answer = llm_with_tools.invoke(chat_messages)\n",
+    "            print(f\"Assistant: {llm_answer.content}\")\n",
+    "    else:\n",
+    "        print(f\"Assistant: {response.content}\")"
+   ],
+   "id": "a181a28df77120fb",
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",