Add a notebook test script.

.gitignore

@@ -2,3 +2,13 @@
 **/.ipynb_checkpoints
 **/venv
 **/.python-version
+**/*.json
+**/*.jpg
+**/*.mp3
+**/*.mp4
+**/*.pdf
+**/*.txt
+**/*.cpp
+**/*.m4a
+**/*.png
+**/*.md

examples/Agents_Function_Calling_Barista_Bot.ipynb

@@ -89,8 +89,17 @@
         "from typing import Iterable\n",
         "\n",
         "import google.generativeai as genai\n",
-        "from google.api_core import retry\n",
-        "\n",
+        "from google.api_core import retry"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "b3eb439fb7a2"
+      },
+      "outputs": [],
+      "source": [
         "from google.colab import userdata\n",
         "genai.configure(api_key=userdata.get('GOOGLE_API_KEY'))"
       ]

examples/Anomaly_detection_with_embeddings.ipynb

@@ -92,9 +92,6 @@
         "import google.generativeai as genai\n",
         "import google.ai.generativelanguage as glm\n",
         "\n",
-        "# Used to securely store your API key\n",
-        "from google.colab import userdata\n",
-        "\n",
         "from sklearn.datasets import fetch_20newsgroups\n",
         "from sklearn.manifold import TSNE"
       ]
@@ -116,6 +113,8 @@
       },
       "outputs": [],
       "source": [
+        "# Used to securely store your API key\n",
+        "from google.colab import userdata\n",
         "API_KEY=userdata.get('GOOGLE_API_KEY')\n",
         "genai.configure(api_key=API_KEY)"
       ]

examples/Apollo_11.ipynb

@@ -143,7 +143,7 @@
         }
       ],
       "source": [
-        "!wget https://storage.googleapis.com/generativeai-downloads/data/a11.txt"
+        "!curl -O https://storage.googleapis.com/generativeai-downloads/data/a11.txt"
       ]
     },
     {

examples/Classify_text_with_embeddings.ipynb

@@ -92,8 +92,6 @@
         "import google.generativeai as genai\n",
         "import google.ai.generativelanguage as glm\n",
         "\n",
-        "from google.colab import userdata\n",
-        "\n",
         "import seaborn as sns\n",
         "import matplotlib.pyplot as plt\n",
         "\n",
@@ -120,6 +118,7 @@
       },
       "outputs": [],
       "source": [
+        "from google.colab import userdata\n",
         "API_KEY=userdata.get('GOOGLE_API_KEY')\n",
         "genai.configure(api_key=API_KEY)"
       ]
@@ -689,7 +688,7 @@
       "outputs": [],
       "source": [
         "def build_classification_model(input_size: int, num_classes: int) -> keras.Model:\n",
-        "  inputs = x = keras.Input(input_size)\n",
+        "  inputs = x = keras.Input([input_size])\n",
         "  x = layers.Dense(input_size, activation='relu')(x)\n",
         "  x = layers.Dense(num_classes, activation='sigmoid')(x)\n",
         "  return keras.Model(inputs=[inputs], outputs=x)"

examples/Market_a_Jet_Backpack.ipynb

@@ -76,7 +76,6 @@
       },
       "outputs": [],
       "source": [
-        "from google.colab import userdata\n",
         "import google.generativeai as genai\n",
         "import PIL.Image\n",
         "from IPython.display import display, Image\n",
@@ -98,8 +97,21 @@
       "metadata": {
         "id": "mIUxhHbFyZlf"
       },
-      "outputs": [],
+      "outputs": [
+        {
+          "ename": "ModuleNotFoundError",
+          "evalue": "No module named 'google.colab'",
+          "output_type": "error",
+          "traceback": [
+            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+            "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
+            "Cell \u001b[0;32mIn[35], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mgoogle\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mcolab\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m userdata\n\u001b[1;32m      2\u001b[0m GOOGLE_API_KEY\u001b[38;5;241m=\u001b[39muserdata\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mGOOGLE_API_KEY\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m      3\u001b[0m genai\u001b[38;5;241m.\u001b[39mconfigure(api_key\u001b[38;5;241m=\u001b[39mGOOGLE_API_KEY)\n",
+            "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'google.colab'"
+          ]
+        }
+      ],
       "source": [
+        "from google.colab import userdata\n",
         "GOOGLE_API_KEY=userdata.get('GOOGLE_API_KEY')\n",
         "genai.configure(api_key=GOOGLE_API_KEY)"
       ]
@@ -245,7 +257,8 @@
       },
       "outputs": [],
       "source": [
-        "response = model.generate_content([analyzePrompt, img])"
+        "json_config=genai.GenerationConfig(response_mime_type=\"application/json\")\n",
+        "response = model.generate_content([analyzePrompt, img], generation_config=json_config)"
       ]
     },
     {
@@ -308,7 +321,7 @@
         "to return a valid array in the format described above, and no other text.\n",
         "The most important thing is that you stick to the array format.\"\"\"\n",
         "\n",
-        "response = model.generate_content([namePrompt, img])\n",
+        "response = model.generate_content([namePrompt, img], generation_config=json_config)\n",
         "\n",
         "names = eval(response.text)\n",
         "# Create a Dropdown widget to choose a name from the\n",
@@ -379,7 +392,7 @@
       },
       "outputs": [],
       "source": [
-        "copyResponse = model.generate_content([websiteCopyPrompt, img])"
+        "copyResponse = model.generate_content([websiteCopyPrompt, img], generation_config=json_config)"
       ]
     },
     {
@@ -518,6 +531,65 @@
         "response = model.generate_content([htmlPrompt])\n",
         "print(response.text)"
       ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 62,
+      "metadata": {
+        "id": "4bd0452be139"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "\n",
+              "<!DOCTYPE html>\n",
+              "<html>\n",
+              "<head>\n",
+              "  <meta charset=\"utf-8\">\n",
+              "  <title>Nimbus</title>\n",
+              "  <style>\n",
+              "    body {\n",
+              "      margin: 0;\n",
+              "      padding: 0;\n",
+              "      font-family: sans-serif;\n",
+              "      background-color: #000;\n",
+              "      color: #fff;\n",
+              "      text-align: center;\n",
+              "    }\n",
+              "\n",
+              "    h1 {\n",
+              "      font-size: 3em;\n",
+              "      margin-top: 0;\n",
+              "      padding-top: 20vh;\n",
+              "    }\n",
+              "\n",
+              "    h2 {\n",
+              "      font-size: 1.5em;\n",
+              "      margin-bottom: 30vh;\n",
+              "    }\n",
+              "  </style>\n",
+              "</head>\n",
+              "<body>\n",
+              "  <h1>Reach new heights</h1>\n",
+              "  <h2>With Nimbus, the sky's the limit. Explore new heights and see the world from a whole new perspective.</h2>\n",
+              "</body>\n",
+              "</html>\n"
+            ],
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ]
+          },
+          "execution_count": 62,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "from IPython.display import HTML\n",
+        "\n",
+        "HTML(response.text.removeprefix('```html').strip('`'))"
+      ]
     }
   ],
   "metadata": {