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‎docs/ais-templates/aistudio_gemini_prompt_freeform_nofiles.ipynb‎

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "Tce3stUlHN0L"
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},
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"source": [
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"##### Copyright 2023 Google LLC"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {
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"id": "tuOe1ymfHZPu"
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},
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"outputs": [],
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"source": [
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"# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n",
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"# you may not use this file except in compliance with the License.\n",
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"# You may obtain a copy of the License at\n",
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"#\n",
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"# https://www.apache.org/licenses/LICENSE-2.0\n",
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"#\n",
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"# Unless required by applicable law or agreed to in writing, software\n",
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"# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
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"# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
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"# See the License for the specific language governing permissions and\n",
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"# limitations under the License."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "FKwyTRdwB8aW"
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},
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"source": [
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"## Setup"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {
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"id": "RXInneX6xx7c"
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},
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"outputs": [],
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"source": [
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"!pip install -U -q \"google-generativeai>=0.8.2\""
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]
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},
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{
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"cell_type": "code",
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"source": [],
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"metadata": {
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"id": "Yw7aMYZ2t0N-"
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},
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"execution_count": 5,
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"outputs": []
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {
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"id": "kWIuwKG2_oWE",
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"outputId": "31dc66f5-5c9f-4102-e2e6-781b3106d0c9",
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"colab": {
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"base_uri": "https://localhost:8080/",
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"height": 564
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}
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},
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"outputs": [
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{
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"output_type": "error",
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"ename": "MessageError",
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"evalue": "Error: credential propagation was unsuccessful",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mMessageError\u001b[0m Traceback (most recent call last)",
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"\u001b[0;32m<ipython-input-7-cf3dd51f0a0c>\u001b[0m in \u001b[0;36m<cell line: 0>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mgoogle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolab\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mdrive\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 12\u001b[0;31m \u001b[0mdrive\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmount\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"/gdrive\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 13\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 14\u001b[0m \u001b[0;31m# The SDK will automatically read it from the GOOGLE_API_KEY environment variable.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;32m/usr/local/lib/python3.11/dist-packages/google/colab/drive.py\u001b[0m in \u001b[0;36mmount\u001b[0;34m(mountpoint, force_remount, timeout_ms, readonly)\u001b[0m\n\u001b[1;32m 98\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mmount\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmountpoint\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mforce_remount\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtimeout_ms\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m120000\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mreadonly\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 99\u001b[0m \u001b[0;34m\"\"\"Mount your Google Drive at the specified mountpoint path.\"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 100\u001b[0;31m return _mount(\n\u001b[0m\u001b[1;32m 101\u001b[0m \u001b[0mmountpoint\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 102\u001b[0m \u001b[0mforce_remount\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mforce_remount\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;32m/usr/local/lib/python3.11/dist-packages/google/colab/drive.py\u001b[0m in \u001b[0;36m_mount\u001b[0;34m(mountpoint, force_remount, timeout_ms, ephemeral, readonly)\u001b[0m\n\u001b[1;32m 135\u001b[0m )\n\u001b[1;32m 136\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mephemeral\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 137\u001b[0;31m _message.blocking_request(\n\u001b[0m\u001b[1;32m 138\u001b[0m \u001b[0;34m'request_auth'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 139\u001b[0m \u001b[0mrequest\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0;34m'authType'\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m'dfs_ephemeral'\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;32m/usr/local/lib/python3.11/dist-packages/google/colab/_message.py\u001b[0m in \u001b[0;36mblocking_request\u001b[0;34m(request_type, request, timeout_sec, parent)\u001b[0m\n\u001b[1;32m 174\u001b[0m \u001b[0mrequest_type\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrequest\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparent\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mparent\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mexpect_reply\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 175\u001b[0m )\n\u001b[0;32m--> 176\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mread_reply_from_input\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrequest_id\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtimeout_sec\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
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"\u001b[0;32m/usr/local/lib/python3.11/dist-packages/google/colab/_message.py\u001b[0m in \u001b[0;36mread_reply_from_input\u001b[0;34m(message_id, timeout_sec)\u001b[0m\n\u001b[1;32m 101\u001b[0m ):\n\u001b[1;32m 102\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;34m'error'\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mreply\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 103\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mMessageError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreply\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'error'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 104\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mreply\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'data'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 105\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;31mMessageError\u001b[0m: Error: credential propagation was unsuccessful"
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]
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}
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],
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"source": [
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"# import necessary modules.\n",
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"\n",
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"import google.generativeai as genai\n",
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"\n",
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"import base64\n",
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"import json\n",
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"\n",
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"try:\n",
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" # Mount google drive\n",
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" from google.colab import drive\n",
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"\n",
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" drive.mount(\"/gdrive\")\n",
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"\n",
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" # The SDK will automatically read it from the GOOGLE_API_KEY environment variable.\n",
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" # In Colab get the key from Colab-secrets (\"🔑\" in the left panel).\n",
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" import os\n",
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" from google.colab import userdata\n",
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"\n",
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" os.environ[\"GOOGLE_API_KEY\"] = userdata.get(\"GOOGLE_API_KEY\")\n",
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"except ImportError:\n",
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" pass\n",
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"\n",
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"# Parse the arguments\n",
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"\n",
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"model = \"gemini-1.5-flash\" # @param {isTemplate: true}\n",
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"contents_b64 = b'W3sicGFydHMiOiBbeyJ0ZXh0IjogIkhlbGxvIn1dfV0='\n",
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"generation_config_b64 = \"e30=\" # @param {isTemplate: true}\n",
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"safety_settings_b64 = \"e30=\" # @param {isTemplate: true}\n",
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"\n",
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"contents = json.loads(base64.b64decode(contents_b64))\n",
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"\n",
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"generation_config = json.loads(base64.b64decode(generation_config_b64))\n",
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"safety_settings = json.loads(base64.b64decode(safety_settings_b64))\n",
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"\n",
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"stream = False\n",
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"\n",
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"print(json.dumps(contents, indent=4))"
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]
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},
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{
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"cell_type": "code",
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"source": [
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"# @title Example form fields\n",
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"# @markdown Forms support many types of fields.\n",
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"\n",
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"no_type_checking = '' # @param\n",
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"string_type = 'example' # @param {type: \"string\"}\n",
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"slider_value = 142 # @param {type: \"slider\", min: 100, max: 200}\n",
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"number = 102 # @param {type: \"number\"}\n",
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"date = '2010-11-05' # @param {type: \"date\"}\n",
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"pick_me = \"monday\" # @param ['monday', 'tuesday', 'wednesday', 'thursday']\n",
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"select_or_input = \"apples\" # @param [\"apples\", \"bananas\", \"oranges\"] {allow-input: true}\n",
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"# @markdown ---"
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],
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"metadata": {
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"id": "g1gW9mM_ubOf"
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},
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "code",
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"source": [
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"# @title Example form fields\n",
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"# @markdown Forms support many types of fields.\n",
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"\n",
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"no_type_checking = '' # @param\n",
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"string_type = 'example' # @param {type: \"string\"}\n",
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"slider_value = 142 # @param {type: \"slider\", min: 100, max: 200}\n",
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"number = 102 # @param {type: \"number\"}\n",
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"date = '2010-11-05' # @param {type: \"date\"}\n",
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"pick_me = \"monday\" # @param ['monday', 'tuesday', 'wednesday', 'thursday']\n",
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"select_or_input = \"apples\" # @param [\"apples\", \"bananas\", \"oranges\"] {allow-input: true}\n",
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"# @markdown ---"
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],
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"metadata": {
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"id": "h-iZ7VmkueMp"
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},
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "code",
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"source": [
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"# @title Example form fields\n",
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"# @markdown Forms support many types of fields.\n",
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"\n",
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"no_type_checking = '' # @param\n",
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"string_type = 'example' # @param {type: \"string\"}\n",
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"slider_value = 142 # @param {type: \"slider\", min: 100, max: 200}\n",
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"number = 102 # @param {type: \"number\"}\n",
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"date = '2010-11-05' # @param {type: \"date\"}\n",
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"pick_me = \"monday\" # @param ['monday', 'tuesday', 'wednesday', 'thursday']\n",
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"select_or_input = \"apples\" # @param [\"apples\", \"bananas\", \"oranges\"] {allow-input: true}\n",
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"# @markdown ---"
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],
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"metadata": {
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"id": "hhcqKxL3ufQN"
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},
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "E7zAD69vE92b"
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},
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"source": [
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"## Call `generate_content`"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "LB2LxPmAB95V"
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},
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"outputs": [],
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"source": [
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"from IPython.display import display\n",
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"from IPython.display import Markdown\n",
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"\n",
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"# Call the model and print the response.\n",
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"gemini = genai.GenerativeModel(model_name=model)\n",
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"\n",
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"response = gemini.generate_content(\n",
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" contents,\n",
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" generation_config=generation_config,\n",
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" safety_settings=safety_settings,\n",
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" stream=stream,\n",
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")\n",
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"\n",
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"display(Markdown(response.text))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "9c9d345e9868"
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},
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"source": [
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"<table class=\"tfo-notebook-buttons\" align=\"left\">\n",
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" <td>\n",
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" <a target=\"_blank\" href=\"https://ai.google.dev/gemini-api/docs\"><img src=\"https://ai.google.dev/static/site-assets/images/docs/notebook-site-button.png\" height=\"32\" width=\"32\" />Docs on ai.google.dev</a>\n",
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" </td>\n",
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" <td>\n",
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" <a target=\"_blank\" href=\"https://github.com/google-gemini/cookbook/blob/main/quickstarts\"><img src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" />More notebooks in the Cookbook</a>\n",
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" </td>\n",
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"</table>"
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]
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},
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{
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"cell_type": "code",
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"source": [],
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"metadata": {
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"id": "NrPCiw9Lt_LM"
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},
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "code",
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"source": [
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"from google.colab import drive\n",
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"drive.mount('/content/drive')"
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],
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"metadata": {
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"id": "98RE5lG5uE57"
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},
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"execution_count": null,
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"outputs": []
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}
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],
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"metadata": {
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"colab": {
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"collapsed_sections": [
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"Tce3stUlHN0L"
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],
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"name": "aistudio_gemini_prompt_freeform_nofiles.ipynb",
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"provenance": []
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},
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"kernelspec": {
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"display_name": "Python 3",
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"name": "python3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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}

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