diff --git a/docs/docs/integrations/tools/prolog_tool.ipynb b/docs/docs/integrations/tools/prolog_tool.ipynb
index 8e0dc9d1e7a..37d38b78ddc 100644
--- a/docs/docs/integrations/tools/prolog_tool.ipynb
+++ b/docs/docs/integrations/tools/prolog_tool.ipynb
@@ -86,33 +86,14 @@
    "execution_count": 3,
    "id": "68709aa2",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "True"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "#!pip install python-dotenv\n",
     "\n",
     "from dotenv import find_dotenv, load_dotenv\n",
     "\n",
-    "load_dotenv(find_dotenv(), override=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "c171c1ef",
-   "metadata": {},
-   "outputs": [],
-   "source": [
+    "load_dotenv(find_dotenv(), override=True)\n",
+    "\n",
     "#!pip install langchain-openai\n",
     "\n",
     "from langchain_core.messages import HumanMessage\n",
@@ -124,19 +105,37 @@
    "id": "9d23b2c5",
    "metadata": {},
    "source": [
-    "To use the tool, bind it to the LLM model and query the model:"
+    "To use the tool, bind it to the LLM model:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 4,
    "id": "3ce4479d",
    "metadata": {},
    "outputs": [],
    "source": [
     "llm = ChatOpenAI(model=\"gpt-4o-mini\")\n",
-    "llm_with_tools = llm.bind_tools([prolog_tool])\n",
-    "messages = [HumanMessage(\"Who are John's children?\")]\n",
+    "llm_with_tools = llm.bind_tools([prolog_tool])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "74767c7c",
+   "metadata": {},
+   "source": [
+    "and then query the model:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "affb960e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "query = \"Who are John's children?\"\n",
+    "messages = [HumanMessage(query)]\n",
     "response = llm_with_tools.invoke(messages)"
    ]
   },
@@ -159,7 +158,7 @@
       "text/plain": [
        "{'name': 'family_query',\n",
        " 'args': {'men': 'john', 'women': None, 'child': None},\n",
-       " 'id': 'call_3VazWUstCGlY8zczi05TaduU',\n",
+       " 'id': 'call_gH8rWamYXITrkfvRP2s5pkbF',\n",
        " 'type': 'tool_call'}"
       ]
      },
@@ -208,7 +207,7 @@
     {
      "data": {
       "text/plain": [
-       "ToolMessage(content='[{\"Women\": \"bianca\", \"Child\": \"mary\"}, {\"Women\": \"bianca\", \"Child\": \"michael\"}]', name='family_query', tool_call_id='call_3VazWUstCGlY8zczi05TaduU')"
+       "ToolMessage(content='[{\"Women\": \"bianca\", \"Child\": \"mary\"}, {\"Women\": \"bianca\", \"Child\": \"michael\"}]', name='family_query', tool_call_id='call_gH8rWamYXITrkfvRP2s5pkbF')"
       ]
      },
      "execution_count": 8,
@@ -239,7 +238,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "John has two children: Mary and Michael. Their mother is Bianca.\n"
+      "John has two children: Mary and Michael, with Bianca as their mother.\n"
      ]
     }
    ],
@@ -269,28 +268,15 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "id": "b7bbfd79",
+   "id": "8957d420",
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain.agents import AgentExecutor, create_tool_calling_agent\n",
-    "from langchain_core.prompts import ChatPromptTemplate\n",
+    "#!pip install langgraph\n",
     "\n",
-    "llm = ChatOpenAI(model=\"gpt-4o-mini\")\n",
+    "from langgraph.prebuilt import create_react_agent\n",
     "\n",
-    "prompt = ChatPromptTemplate.from_messages(\n",
-    "    [\n",
-    "        (\"system\", \"You are a helpful assistant\"),\n",
-    "        (\"human\", \"{input}\"),\n",
-    "        (\"placeholder\", \"{agent_scratchpad}\"),\n",
-    "    ]\n",
-    ")\n",
-    "\n",
-    "tools = [prolog_tool]\n",
-    "\n",
-    "agent = create_tool_calling_agent(llm, tools, prompt)\n",
-    "\n",
-    "agent_executor = AgentExecutor(agent=agent, tools=tools)"
+    "agent_executor = create_react_agent(llm, [prolog_tool])"
    ]
   },
   {
@@ -310,7 +296,7 @@
    },
    "outputs": [],
    "source": [
-    "answer = agent_executor.invoke({\"input\": \"Who are John's children?\"})"
+    "messages = agent_executor.invoke({\"messages\": [(\"human\", query)]})"
    ]
   },
   {
@@ -318,7 +304,7 @@
    "id": "92e71ffa",
    "metadata": {},
    "source": [
-    "Then the agent recieves the tool response as part of the `\"agent_scratchpad`\" placeholder and generates the answer:"
+    "Then the agent receives​ the tool response and generates the answer:"
    ]
   },
   {
@@ -331,12 +317,14 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "==================================\u001b[1m Ai Message \u001b[0m==================================\n",
+      "\n",
       "John has two children: Mary and Michael, with Bianca as their mother.\n"
      ]
     }
    ],
    "source": [
-    "print(answer[\"output\"])"
+    "messages[\"messages\"][-1].pretty_print()"
    ]
   },
   {
@@ -346,17 +334,23 @@
    "source": [
     "## API reference\n",
     "\n",
-    "(TODO: update with API reference once built.)\n",
-    "\n",
-    "See https://github.com/apisani1/langchain-prolog/tree/main for detail."
+    "See https://langchain-prolog.readthedocs.io/en/latest/modules.html for detail."
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a95afa82",
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3.9 (test-env)",
+   "display_name": "Python 3.10 (test-again)",
    "language": "python",
-   "name": "test-env"
+   "name": "test-again"
   },
   "language_info": {
    "codemirror_mode": {
@@ -368,7 +362,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.21"
+   "version": "3.10.16"
   }
  },
  "nbformat": 4,