diff --git a/docs/docs/examples/llm/mistralai.ipynb b/docs/docs/examples/llm/mistralai.ipynb
index 00a3dc5abedb0b850205314b3542e3729b4ed1df..765743508fa45f5f634436a98e2efed6fb568ada 100644
--- a/docs/docs/examples/llm/mistralai.ipynb
+++ b/docs/docs/examples/llm/mistralai.ipynb
@@ -1,7 +1,6 @@
 {
  "cells": [
   {
-   "attachments": {},
    "cell_type": "markdown",
    "id": "6453d3d5",
    "metadata": {},
@@ -10,7 +9,6 @@
    ]
   },
   {
-   "attachments": {},
    "cell_type": "markdown",
    "id": "72ed6f61-28a7-4f90-8a45-e3f452f95dbd",
    "metadata": {},
@@ -82,7 +80,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Paul Graham is a well-known entrepreneur, hacker, and essayist. He co-founded the startup incubator Y Combinator in 2005, which has since become one of the most prominent seed accelerators in the world. Graham's essays on entrepreneurship, startups, and technology have been widely read and influential. He has also been an active programmer and has made significant contributions to various open-source projects. Graham's writing has been collected in several books, including \"Hackers & Painters,\" \"Maker's Schedule, Manager's Schedule,\" and \"The Accidental Entrepreneur.\" He is known for his insightful and thought-provoking perspectives on technology, business, and culture.\n"
+      "Paul Graham is a well-known entrepreneur, hacker, and essayist. He co-founded the startup incubator Y Combinator in 2005, which has since become one of the most successful and influential startup accelerators in the world. Graham is also known for his essays on entrepreneurship, programming, and startups, which have been published on his website, Hacker News, and in various publications. He has been described as a \"pioneer of the startup scene in Silicon Valley\" and a \"leading figure in the Y Combinator startup community.\" Graham's essays have influenced generations of entrepreneurs and programmers, and he is considered a thought leader in the tech industry.\n"
      ]
     }
    ],
@@ -146,7 +144,6 @@
    ]
   },
   {
-   "attachments": {},
    "cell_type": "markdown",
    "id": "71c3f32d",
    "metadata": {},
@@ -206,7 +203,6 @@
    ]
   },
   {
-   "attachments": {},
    "cell_type": "markdown",
    "id": "e6adbf45",
    "metadata": {},
@@ -253,7 +249,6 @@
    ]
   },
   {
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    "cell_type": "markdown",
    "id": "67293b92",
    "metadata": {},
@@ -458,6 +453,80 @@
     "    print(r.delta, end=\"\")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "ca6fefbb-419a-4f08-922c-ecd2362ff338",
+   "metadata": {},
+   "source": [
+    "## Function Calling\n",
+    "\n",
+    "`mistral-large` supports native function calling. There's a seamless integration with LlamaIndex tools, through the `predict_and_call` function on the `llm`. \n",
+    "\n",
+    "This allows the user to attach any tools and let the LLM decide which tools to call (if any).\n",
+    "\n",
+    "If you wish to perform tool calling as part of an agentic loop, check out our [agent guides](https://docs.llamaindex.ai/en/latest/module_guides/deploying/agents/) instead.\n",
+    "\n",
+    "**NOTE**: If you use another Mistral model, we will use a ReAct prompt to attempt to call the function. Your mileage may vary."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ab80d63a-7bd4-446c-9a22-0d1604dbc59e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from llama_index.llms.mistralai import MistralAI\n",
+    "from llama_index.core.tools import FunctionTool\n",
+    "\n",
+    "\n",
+    "def multiply(a: int, b: int) -> int:\n",
+    "    \"\"\"Multiple two integers and returns the result integer\"\"\"\n",
+    "    return a * b\n",
+    "\n",
+    "\n",
+    "def mystery(a: int, b: int) -> int:\n",
+    "    \"\"\"Mystery function on two integers.\"\"\"\n",
+    "    return a * b + a + b\n",
+    "\n",
+    "\n",
+    "mystery_tool = FunctionTool.from_defaults(fn=mystery)\n",
+    "multiply_tool = FunctionTool.from_defaults(fn=multiply)\n",
+    "\n",
+    "llm = MistralAI(model=\"mistral-large-latest\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bba8a5fa-bed9-44d3-bb3c-149dbc694bf6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "response = llm.predict_and_call(\n",
+    "    [mystery_tool, multiply_tool],\n",
+    "    user_msg=\"What happens if I run the mystery function on 5 and 7\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "28b3a9ed-1d0e-4bdc-abb2-acf4afab7a5f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "47\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(str(response))"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "5152a2b4-78e6-47a5-933d-f5186ec0f775",
@@ -500,9 +569,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "llama_index_v3",
    "language": "python",
-   "name": "python3"
+   "name": "llama_index_v3"
   },
   "language_info": {
    "codemirror_mode": {