Add tool calling example to Ollama ntbk (#24522)

docs/docs/integrations/chat/ollama.ipynb

@@ -110,7 +110,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "id": "cb09c344-1836-4e0c-acf8-11d13ac1dbae",
    "metadata": {},
    "outputs": [],
@@ -134,18 +134,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 4,
    "id": "62e0dbc3",
    "metadata": {
     "tags": []
    },
    "outputs": [
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "AIMessage(content='Je adore le programmation.\\n\\n(Note: \"programmation\" is the feminine form of the noun in French, but if you want to use the masculine form, it would be \"le programme\" instead.)' response_metadata={'model': 'llama3', 'created_at': '2024-07-04T04:20:28.138164Z', 'message': {'role': 'assistant', 'content': ''}, 'done_reason': 'stop', 'done': True, 'total_duration': 1943337750, 'load_duration': 1128875, 'prompt_eval_count': 33, 'prompt_eval_duration': 322813000, 'eval_count': 43, 'eval_duration': 1618213000} id='run-ed8c17ab-7fc2-4c90-a88a-f6273b49bc78-0')\n"
-     ]
+     "data": {
+      "text/plain": [
+       "AIMessage(content='Je adore le programmation.\\n\\n(Note: \"programmation\" is not commonly used in French, but I translated it as \"le programmation\" to maintain the same grammatical structure and meaning as the original English sentence.)', response_metadata={'model': 'llama3', 'created_at': '2024-07-22T17:43:54.731273Z', 'message': {'role': 'assistant', 'content': ''}, 'done_reason': 'stop', 'done': True, 'total_duration': 11094839375, 'load_duration': 10121854667, 'prompt_eval_count': 36, 'prompt_eval_duration': 146569000, 'eval_count': 46, 'eval_duration': 816593000}, id='run-befccbdc-e1f9-42a9-85cf-e69b926d6b8b-0', usage_metadata={'input_tokens': 36, 'output_tokens': 46, 'total_tokens': 82})"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
    "source": [
@@ -164,7 +167,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 5,
    "id": "d86145b3-bfef-46e8-b227-4dda5c9c2705",
    "metadata": {},
    "outputs": [
@@ -174,7 +177,7 @@
      "text": [
       "Je adore le programmation.\n",
       "\n",
-      "(Note: \"programmation\" is the feminine form of the noun in French, but if you want to use the masculine form, it would be \"le programme\" instead.)\n"
+      "(Note: \"programmation\" is not commonly used in French, but I translated it as \"le programmation\" to maintain the same grammatical structure and meaning as the original English sentence.)\n"
      ]
     }
    ],
@@ -232,6 +235,86 @@
     ")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "0f51345d-0a9d-43f1-8fca-d0662cb8e21b",
+   "metadata": {},
+   "source": [
+    "## Tool calling\n",
+    "\n",
+    "We can use [tool calling](https://blog.langchain.dev/improving-core-tool-interfaces-and-docs-in-langchain/) with an LLM [that has been fine-tuned for tool use](https://ollama.com/library/llama3-groq-tool-use): \n",
+    "\n",
+    "```\n",
+    "ollama pull llama3-groq-tool-use\n",
+    "```\n",
+    "\n",
+    "We can just pass normal Python functions directly as tools."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "5250bceb-1029-41ff-b447-983518704d88",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[{'name': 'validate_user',\n",
+       "  'args': {'addresses': ['123 Fake St, Boston MA',\n",
+       "    '234 Pretend Boulevard, Houston TX'],\n",
+       "   'user_id': 123},\n",
+       "  'id': 'fe2148d3-95fb-48e9-845a-4bfecc1f1f96',\n",
+       "  'type': 'tool_call'}]"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from typing import List\n",
+    "\n",
+    "from langchain_ollama import ChatOllama\n",
+    "from typing_extensions import TypedDict\n",
+    "\n",
+    "\n",
+    "def validate_user(user_id: int, addresses: List) -> bool:\n",
+    "    \"\"\"Validate user using historical addresses.\n",
+    "\n",
+    "    Args:\n",
+    "        user_id: (int) the user ID.\n",
+    "        addresses: Previous addresses.\n",
+    "    \"\"\"\n",
+    "    return True\n",
+    "\n",
+    "\n",
+    "llm = ChatOllama(\n",
+    "    model=\"llama3-groq-tool-use\",\n",
+    "    temperature=0,\n",
+    ").bind_tools([validate_user])\n",
+    "\n",
+    "result = llm.invoke(\n",
+    "    \"Could you validate user 123? They previously lived at \"\n",
+    "    \"123 Fake St in Boston MA and 234 Pretend Boulevard in \"\n",
+    "    \"Houston TX.\"\n",
+    ")\n",
+    "result.tool_calls"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2bb034ff-218f-4865-afea-3f5e57d3bdee",
+   "metadata": {},
+   "source": [
+    "We look at the LangSmith trace to see that the tool call was performed: \n",
+    "\n",
+    "https://smith.langchain.com/public/4169348a-d6be-45df-a7cf-032f6baa4697/r\n",
+    "\n",
+    "In particular, the trace shows how the tool schema was populated."
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "4c5e0197",
@@ -384,7 +467,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.3"
+   "version": "3.11.8"
   }
  },
  "nbformat": 4,