refresh Jupyter Notebook examples (#599)

11_notebooks/basic.ipynb

@@ -6,7 +6,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%pip install modal-client\n",
+    "%pip install --upgrade modal\n",
     "%pip install ipywidgets"
    ]
   },
@@ -18,7 +18,8 @@
    "source": [
     "import modal\n",
     "\n",
-    "assert modal.__version__ > \"0.49.0\""
+    "assert modal.__version__ > \"0.49.0\"\n",
+    "modal.__version__"
    ]
   },
   {
@@ -29,7 +30,7 @@
    "source": [
     "import modal\n",
     "\n",
-    "stub = modal.Stub(name=\"example-basic-notebook\")"
+    "stub = modal.Stub(name=\"example-basic-notebook-app\")"
    ]
   },
   {
@@ -65,10 +66,7 @@
     "the function with the Modal stub.\n",
     "\n",
     "To demonstrate that Modal functions you define in the notebook can be called by _other_ Modal functions, there's another function, `quadruple`, which uses `double` and `double_with_modal`.\n",
-    "For numbers greater than 1 million, this function spins up containers that run in Modal, which is a _very_ inefficient way to multiply a number by four, but you can do it if you please!\n",
-    "\n",
-    "Be aware that all Modal functions are defined and run using `with stub.run()` in a single cell. Currently, putting all Modal functions in a single-cell is a limitation of the Modal client.\n",
-    "We aim to make notebook code organization more flexible in the future."
+    "For numbers greater than 1 million, this function spins up containers that run in Modal, which is a _very_ inefficient way to multiply a number by four, but you can do it if you please!"
    ]
   },
   {
@@ -91,8 +89,9 @@
     "\n",
     "\n",
     "with stub.run():\n",
-    "    print(quadruple.local(100))\n",
+    "    print(quadruple.local(100))   # running locally\n",
     "    print(quadruple.remote(100))  # run remotely\n",
+    "    print(\"Doing a very inefficient remote multiplication just for fun!\")\n",
     "    result = quadruple.remote(10_000_000)"
    ]
   },
@@ -102,21 +101,47 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Evaluate the result created above.\n",
+    "# Evaluate the result created in above cell\n",
     "result"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### GPU-powered notebook cells!\n",
+    "\n",
+    "Thanks to Modal's remote execution capabilities, your notebook can be running on your laptop or a cheap CPU-only instance and take advantage of serverless GPU container execution. Here's the basics."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "# Define a Modal function with a GPU attached.\n",
+    "@stub.function(gpu=\"any\")\n",
+    "def hello_gpu():\n",
+    "    import subprocess\n",
+    "    subprocess.run(\"nvidia-smi\", shell=True, check=True)\n",
+    "    return \"hello from a remote GPU!\"\n",
+    "\n",
+    "\n",
+    "# Start and run an ephemeral modal.App and execute the GPU-powered modal Function!\n",
+    "with stub.run():\n",
+    "    result = hello_gpu.remote()\n",
+    "    assert result == \"hello from a remote GPU!\"\n",
+    "\n",
+    "# After the app is finished you can continue executing other function's defined in your notebook and\n",
+    "# use the results of your GPU functions!\n",
+    "\"This is the remote GPU's return value: \" + result"
+   ]
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3.9.5 ('.venv': venv)",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },

11_notebooks/jupyter_inside_modal.py

@@ -1,11 +1,15 @@
 # ---
 # args: ["--timeout", 10]
 # ---
+
+# ## Overview
 #
-# Quick snippet to connect to a Jupyter notebook server running inside a Modal container,
+# Quick snippet showing how to connect to a Jupyter notebook server running inside a Modal container,
 # especially useful for exploring the contents of Modal network file systems.
 # This uses [Modal Tunnels](https://modal.com/docs/guide/tunnels#tunnels-beta)
 # to create a tunnel between the running Jupyter instance and the internet.
+#
+# If you want to your Jupyter notebook to run _locally_ and execute remote Modal Functions in certain cells, see the `basic.ipynb` example :)
 
 import os
 import subprocess