Gemini_01_Prompting_video_with_gemini_1_5_github.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "256859c1-4ea8-45c1-be06-0e2e4d017b7b",
   "metadata": {},
   "source": [
    "# 🔥 Prompting Video with Gemini 1.5 🔥"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5fa2a677-0ea1-4eb9-bf4e-f70226c1e456",
   "metadata": {},
   "source": [
    "Une démo sur l'utilisation de plusieurs API de Google pour la génération automatique d'un transcript timé d'une vidéo.\n",
    "\n",
    "\n"
   ]
  },
  {
   "attachments": {
    "9ac9ca54-eb53-46ac-ab53-4ae94dabc6e4.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "626a2413-90ab-4b9c-b4af-f857fbeac41c",
   "metadata": {},
   "source": [
    "![image.png](attachment:9ac9ca54-eb53-46ac-ab53-4ae94dabc6e4.png)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "de45f081-1b4f-417a-b4df-d24af1387e3c",
   "metadata": {},
   "source": [
    "# -4) Seting up a venv in Vertex AI Workbench\n",
    "\n",
    "Look at : https://cloud.google.com/vertex-ai/docs/workbench/instances/add-environment to create a python env"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9bb57413-1aa8-4109-ab88-577cbedf5aa9",
   "metadata": {},
   "outputs": [],
   "source": [
    "requirements_txt = \"\"\"\n",
    "google-cloud-aiplatform\n",
    "varname\n",
    "unidecode\n",
    "pytube\n",
    "google-cloud-videointelligence\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "fed12a26-3d71-46d4-bfac-8ca8aa904779",
   "metadata": {},
   "outputs": [],
   "source": [
    "shell_code = \"\"\"\n",
    "\n",
    "    myenv=\"gemini1.5\" \n",
    "    \n",
    "    conda create -n $myenv\n",
    "    conda activate $myenv\n",
    "    \n",
    "    conda install pip\n",
    "    pip install -r requirements.txt\n",
    "    \n",
    "# installting & creating the env : \n",
    "    DL_ANACONDA_ENV_HOME=\"${DL_ANACONDA_HOME}/envs/myenv\"\n",
    "    python -m ipykernel install --prefix \"${DL_ANACONDA_ENV_HOME}\" --name $myenv --display-name $myenv\n",
    "\n",
    "#simlinking to vertex's default folder\n",
    "    ln -s /opt/conda/envs/myenv/share/jupyter/kernels/$myenv ls /opt/conda/share/jupyter/kernels\n",
    "\n",
    "\"\"\"# to execute as a shell command"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "df7e3d6c-1415-495e-b868-99cd34bca3e5",
   "metadata": {},
   "source": [
    "# -3) Install python libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e2df855b-3d0d-434c-ae23-94f4510523a5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[33mWARNING: Ignoring invalid distribution -oogle-auth (/opt/conda/lib/python3.10/site-packages)\u001b[0m\u001b[33m\n",
      "\u001b[0mRequirement already satisfied: varname in /opt/conda/lib/python3.10/site-packages (0.13.0)\n",
      "Collecting executing<3.0,>=2.0 (from varname)\n",
      "  Using cached executing-2.0.1-py2.py3-none-any.whl.metadata (9.0 kB)\n",
      "Using cached executing-2.0.1-py2.py3-none-any.whl (24 kB)\n",
      "\u001b[33mWARNING: Error parsing requirements for executing: [Errno 2] No such file or directory: '/opt/conda/lib/python3.10/site-packages/executing-1.2.0.dist-info/METADATA'\u001b[0m\u001b[33m\n",
      "\u001b[0m\u001b[33mWARNING: Ignoring invalid distribution -oogle-auth (/opt/conda/lib/python3.10/site-packages)\u001b[0m\u001b[33m\n",
      "\u001b[0mInstalling collected packages: executing\n",
      "  Attempting uninstall: executing\n",
      "\u001b[33m    WARNING: No metadata found in /opt/conda/lib/python3.10/site-packages\u001b[0m\u001b[33m\n",
      "\u001b[0m    Found existing installation: executing 1.2.0\n",
      "\u001b[31mERROR: Cannot uninstall executing 1.2.0, RECORD file not found. You might be able to recover from this via: 'pip install --force-reinstall --no-deps executing==1.2.0'.\u001b[0m\u001b[31m\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "!pip install varname"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "7d601bad-97b4-46cb-8ec6-a1c81d333893",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[33mWARNING: Ignoring invalid distribution -oogle-auth (/opt/conda/lib/python3.10/site-packages)\u001b[0m\u001b[33m\n",
      "\u001b[0mRequirement already satisfied: unidecode in /opt/conda/lib/python3.10/site-packages (1.3.8)\n",
      "\u001b[33mWARNING: Error parsing requirements for executing: [Errno 2] No such file or directory: '/opt/conda/lib/python3.10/site-packages/executing-1.2.0.dist-info/METADATA'\u001b[0m\u001b[33m\n",
      "\u001b[0m\u001b[33mWARNING: Ignoring invalid distribution -oogle-auth (/opt/conda/lib/python3.10/site-packages)\u001b[0m\u001b[33m\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "!pip install unidecode"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "25f03914-2ab7-4f6f-affe-dfc39b412b8b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[33mWARNING: Ignoring invalid distribution -oogle-auth (/opt/conda/lib/python3.10/site-packages)\u001b[0m\u001b[33m\n",
      "\u001b[0mRequirement already satisfied: pytube in /opt/conda/lib/python3.10/site-packages (15.0.0)\n",
      "\u001b[33mWARNING: Error parsing requirements for executing: [Errno 2] No such file or directory: '/opt/conda/lib/python3.10/site-packages/executing-1.2.0.dist-info/METADATA'\u001b[0m\u001b[33m\n",
      "\u001b[0m\u001b[33mWARNING: Ignoring invalid distribution -oogle-auth (/opt/conda/lib/python3.10/site-packages)\u001b[0m\u001b[33m\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "!pip install pytube"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "35bd7789-67a0-4243-9650-bb091b1204f0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[33mWARNING: Ignoring invalid distribution -oogle-auth (/opt/conda/lib/python3.10/site-packages)\u001b[0m\u001b[33m\n",
      "\u001b[0mRequirement already satisfied: google-cloud-videointelligence in /opt/conda/lib/python3.10/site-packages (2.11.4)\n",
      "Requirement already satisfied: google-api-core!=2.0.*,!=2.1.*,!=2.10.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,!=2.8.*,!=2.9.*,<3.0.0dev,>=1.34.0 in /opt/conda/lib/python3.10/site-packages (from google-api-core[grpc]!=2.0.*,!=2.1.*,!=2.10.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,!=2.8.*,!=2.9.*,<3.0.0dev,>=1.34.0->google-cloud-videointelligence) (2.18.0)\n",
      "Requirement already satisfied: proto-plus<2.0.0dev,>=1.22.0 in /opt/conda/lib/python3.10/site-packages (from google-cloud-videointelligence) (1.23.0)\n",
      "Requirement already satisfied: protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5 in /opt/conda/lib/python3.10/site-packages (from google-cloud-videointelligence) (3.20.3)\n",
      "Requirement already satisfied: googleapis-common-protos<2.0.dev0,>=1.56.2 in /opt/conda/lib/python3.10/site-packages (from google-api-core!=2.0.*,!=2.1.*,!=2.10.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,!=2.8.*,!=2.9.*,<3.0.0dev,>=1.34.0->google-api-core[grpc]!=2.0.*,!=2.1.*,!=2.10.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,!=2.8.*,!=2.9.*,<3.0.0dev,>=1.34.0->google-cloud-videointelligence) (1.59.1)\n",
      "Requirement already satisfied: google-auth<3.0.dev0,>=2.14.1 in /opt/conda/lib/python3.10/site-packages (from google-api-core!=2.0.*,!=2.1.*,!=2.10.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,!=2.8.*,!=2.9.*,<3.0.0dev,>=1.34.0->google-api-core[grpc]!=2.0.*,!=2.1.*,!=2.10.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,!=2.8.*,!=2.9.*,<3.0.0dev,>=1.34.0->google-cloud-videointelligence) (2.27.0)\n",
      "Requirement already satisfied: requests<3.0.0.dev0,>=2.18.0 in /opt/conda/lib/python3.10/site-packages (from google-api-core!=2.0.*,!=2.1.*,!=2.10.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,!=2.8.*,!=2.9.*,<3.0.0dev,>=1.34.0->google-api-core[grpc]!=2.0.*,!=2.1.*,!=2.10.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,!=2.8.*,!=2.9.*,<3.0.0dev,>=1.34.0->google-cloud-videointelligence) (2.31.0)\n",
      "Requirement already satisfied: grpcio<2.0dev,>=1.33.2 in /opt/conda/lib/python3.10/site-packages (from google-api-core[grpc]!=2.0.*,!=2.1.*,!=2.10.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,!=2.8.*,!=2.9.*,<3.0.0dev,>=1.34.0->google-cloud-videointelligence) (1.51.3)\n",
      "Requirement already satisfied: grpcio-status<2.0.dev0,>=1.33.2 in /opt/conda/lib/python3.10/site-packages (from google-api-core[grpc]!=2.0.*,!=2.1.*,!=2.10.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,!=2.8.*,!=2.9.*,<3.0.0dev,>=1.34.0->google-cloud-videointelligence) (1.48.2)\n",
      "Requirement already satisfied: cachetools<6.0,>=2.0.0 in /opt/conda/lib/python3.10/site-packages (from google-auth<3.0.dev0,>=2.14.1->google-api-core!=2.0.*,!=2.1.*,!=2.10.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,!=2.8.*,!=2.9.*,<3.0.0dev,>=1.34.0->google-api-core[grpc]!=2.0.*,!=2.1.*,!=2.10.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,!=2.8.*,!=2.9.*,<3.0.0dev,>=1.34.0->google-cloud-videointelligence) (5.3.1)\n",
      "Requirement already satisfied: pyasn1-modules>=0.2.1 in /opt/conda/lib/python3.10/site-packages (from google-auth<3.0.dev0,>=2.14.1->google-api-core!=2.0.*,!=2.1.*,!=2.10.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,!=2.8.*,!=2.9.*,<3.0.0dev,>=1.34.0->google-api-core[grpc]!=2.0.*,!=2.1.*,!=2.10.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,!=2.8.*,!=2.9.*,<3.0.0dev,>=1.34.0->google-cloud-videointelligence) (0.3.0)\n",
      "Requirement already satisfied: rsa<5,>=3.1.4 in /opt/conda/lib/python3.10/site-packages (from google-auth<3.0.dev0,>=2.14.1->google-api-core!=2.0.*,!=2.1.*,!=2.10.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,!=2.8.*,!=2.9.*,<3.0.0dev,>=1.34.0->google-api-core[grpc]!=2.0.*,!=2.1.*,!=2.10.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,!=2.8.*,!=2.9.*,<3.0.0dev,>=1.34.0->google-cloud-videointelligence) (4.9)\n",
      "Requirement already satisfied: charset-normalizer<4,>=2 in /opt/conda/lib/python3.10/site-packages (from requests<3.0.0.dev0,>=2.18.0->google-api-core!=2.0.*,!=2.1.*,!=2.10.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,!=2.8.*,!=2.9.*,<3.0.0dev,>=1.34.0->google-api-core[grpc]!=2.0.*,!=2.1.*,!=2.10.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,!=2.8.*,!=2.9.*,<3.0.0dev,>=1.34.0->google-cloud-videointelligence) (3.1.0)\n",
      "Requirement already satisfied: idna<4,>=2.5 in /opt/conda/lib/python3.10/site-packages (from requests<3.0.0.dev0,>=2.18.0->google-api-core!=2.0.*,!=2.1.*,!=2.10.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,!=2.8.*,!=2.9.*,<3.0.0dev,>=1.34.0->google-api-core[grpc]!=2.0.*,!=2.1.*,!=2.10.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,!=2.8.*,!=2.9.*,<3.0.0dev,>=1.34.0->google-cloud-videointelligence) (3.4)\n",
      "Requirement already satisfied: urllib3<3,>=1.21.1 in /opt/conda/lib/python3.10/site-packages (from requests<3.0.0.dev0,>=2.18.0->google-api-core!=2.0.*,!=2.1.*,!=2.10.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,!=2.8.*,!=2.9.*,<3.0.0dev,>=1.34.0->google-api-core[grpc]!=2.0.*,!=2.1.*,!=2.10.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,!=2.8.*,!=2.9.*,<3.0.0dev,>=1.34.0->google-cloud-videointelligence) (2.0.3)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /opt/conda/lib/python3.10/site-packages (from requests<3.0.0.dev0,>=2.18.0->google-api-core!=2.0.*,!=2.1.*,!=2.10.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,!=2.8.*,!=2.9.*,<3.0.0dev,>=1.34.0->google-api-core[grpc]!=2.0.*,!=2.1.*,!=2.10.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,!=2.8.*,!=2.9.*,<3.0.0dev,>=1.34.0->google-cloud-videointelligence) (2024.2.2)\n",
      "Requirement already satisfied: pyasn1<0.6.0,>=0.4.6 in /opt/conda/lib/python3.10/site-packages (from pyasn1-modules>=0.2.1->google-auth<3.0.dev0,>=2.14.1->google-api-core!=2.0.*,!=2.1.*,!=2.10.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,!=2.8.*,!=2.9.*,<3.0.0dev,>=1.34.0->google-api-core[grpc]!=2.0.*,!=2.1.*,!=2.10.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,!=2.8.*,!=2.9.*,<3.0.0dev,>=1.34.0->google-cloud-videointelligence) (0.5.0)\n",
      "\u001b[33mWARNING: Error parsing requirements for executing: [Errno 2] No such file or directory: '/opt/conda/lib/python3.10/site-packages/executing-1.2.0.dist-info/METADATA'\u001b[0m\u001b[33m\n",
      "\u001b[0m\u001b[33mWARNING: Ignoring invalid distribution -oogle-auth (/opt/conda/lib/python3.10/site-packages)\u001b[0m\u001b[33m\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "!pip install google-cloud-videointelligence\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "285d16c4-9d60-40d1-9384-93280a3b582a",
   "metadata": {},
   "source": [
    "# -2) import des librairies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "04a49e82-0b32-473b-803f-34caec64ec72",
   "metadata": {},
   "outputs": [],
   "source": [
    "\"\"\"Transcribe speech from a video stored on GCS.\"\"\"\n",
    "from google.cloud import videointelligence\n",
    "from pytube import YouTube\n",
    "# Install pytube if not already installed\n",
    "from pytube import YouTube\n",
    "from google.cloud import storage\n",
    "import vertexai\n",
    "import json\n",
    "import unidecode\n",
    "from varname import nameof\n",
    "\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "from IPython.display import Markdown, display\n",
    "from sklearn.metrics.pairwise import cosine_similarity\n",
    "from vertexai.preview.language_models import (ChatModel, InputOutputTextPair,\n",
    "                                              TextEmbeddingModel,\n",
    "                                              TextGenerationModel)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "5cb6ec9f-c18d-4efa-932a-400aefabf201",
   "metadata": {},
   "outputs": [],
   "source": [
    "from vertexai.generative_models import GenerativeModel\n",
    "\n",
    "import base64\n",
    "import vertexai\n",
    "from vertexai.generative_models import GenerativeModel, Part, FinishReason\n",
    "\n",
    "\"\"\"\n",
    "Dans l'import from vertexai.generative_models import part, l'objet part représente une composante d'un modèle génératif Vertex AI. Il s'agit d'une unité de base qui peut être assemblée avec d'autres parties pour créer un modèle plus complexe.\n",
    "\n",
    "Chaque partie possède ses propres fonctionnalités et caractéristiques, et peut être utilisée pour générer différents types de contenu. Voici quelques exemples de parties :\n",
    "\n",
    "Texte: génère du texte, comme des phrases, des paragraphes ou des articles entiers.\n",
    "Code: génère du code, comme des scripts Python ou des fonctions Java.\n",
    "Image: génère des images, comme des photos ou des illustrations.\n",
    "Audio: génère du son, comme de la musique ou des voix.\n",
    "En plus de ces types de base, il existe également des parties plus spécialisées qui peuvent être utilisées pour des tâches spécifiques, comme la traduction, la synthèse de discours ou la génération de questions/réponses.\n",
    "\"\"\"\n",
    "import vertexai.preview.generative_models as generative_models\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "8e47c12d-6c9b-4f36-b1d3-2dd5363a3bdf",
   "metadata": {},
   "outputs": [],
   "source": [
    "from google.cloud import storage"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f076da06-a4fc-4918-ae56-72e316cfb0e6",
   "metadata": {},
   "source": [
    "# -1) Helper functions for bucket management"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "93c66310-3d58-43ed-b0b7-81c2bc4b1543",
   "metadata": {},
   "source": [
    "## -1.1) Fetching from youtube "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "1711581b-80f3-4068-bbbb-6a21ac000487",
   "metadata": {},
   "outputs": [],
   "source": [
    "def download_video(video_url):\n",
    "    # Create a YouTube object\n",
    "    yt = YouTube(video_url)\n",
    "    \n",
    "    # Filter to get the highest resolution stream that includes both video and audio\n",
    "    stream = yt.streams.filter(progressive=True, file_extension='mp4').order_by('resolution').desc().first()\n",
    "    \n",
    "    # Download the video\n",
    "    if stream:\n",
    "        print(f\"Going to download {video_url}\")\n",
    "        stream.download()\n",
    "        print(f\"Downloaded into {stream.default_filename}\")\n",
    "    else:\n",
    "        print(\"No suitable stream found\")\n",
    "    return stream.default_filename"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "c2763199-df3f-4184-ba5b-20d24e2fac43",
   "metadata": {},
   "outputs": [],
   "source": [
    "def upload_video_sur_bucket(video_url):\n",
    "    downloaded_video     = download_video(video_url)\n",
    "    uploaded_video       = upload_file_to_bucket(bucket_name, downloaded_video)\n",
    "    \n",
    "    uri_video_sur_bucket = f\"gs://{bucket_name}/{uploaded_video}\"\n",
    "\n",
    "    return uri_video_sur_bucket"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a800ad3a-74b5-400f-be1e-2f1faaa91657",
   "metadata": {},
   "source": [
    "## -1.2) Managing buckets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "8524b8f7-f0a2-46c2-9e4d-c36f030a09a5",
   "metadata": {},
   "outputs": [],
   "source": [
    "def list_buckets_names():\n",
    "    storage_client = storage.Client()\n",
    "    buckets        = storage_client.list_buckets()\n",
    "    return [bucket.name for bucket in buckets]\n",
    "\n",
    "\n",
    "def create_bucket_class_location(bucket_name, storage_class = \"STANDARD\", location=\"us\"):\n",
    "    storage_client       = storage.Client()\n",
    "    bucket               = storage_client.bucket(bucket_name)\n",
    "    bucket.storage_class = storage_class\n",
    "    new_bucket           = storage_client.create_bucket(bucket, location=location)\n",
    "    print(f\"Created bucket {new_bucket.name} in {new_bucket.location} with storage class {new_bucket.storage_class}\")\n",
    "    return new_bucket\n",
    "\n",
    "\n",
    "def upload_file_to_gcs(bucket_name, source_file_path, destination_blob_name):\n",
    "    client = storage.Client()\n",
    "    bucket = client.bucket(bucket_name)\n",
    "    blob = bucket.blob(destination_blob_name)\n",
    "    blob.upload_from_filename(source_file_path)\n",
    "    return blob"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "31038d14-bde4-4af1-8a62-ece2ba17e2cd",
   "metadata": {},
   "outputs": [],
   "source": [
    "def upload_file_to_bucket(bucket_name, source_file_path): \n",
    "    source_file_path = f\"./{source_file_path}\"\n",
    "    destination_blob_name = source_file_path.replace(' ', '_')\n",
    "    destination_blob_name = unidecode.unidecode(destination_blob_name)\n",
    "    uploaded_blob         = upload_file_to_gcs(bucket_name, source_file_path, destination_blob_name)\n",
    "    print(f\"File [{source_file_path}] \\nUploaded to [{uploaded_blob.name}] \\nIn bucket [{bucket_name}]\")\n",
    "    return destination_blob_name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "cf523e6a-842d-4449-814e-4a8ccaa83dca",
   "metadata": {},
   "outputs": [],
   "source": [
    "def create_bucket_if_doesnt_exist(bucket_name):\n",
    "    if bucket_name not in list_buckets_names():\n",
    "        print(f\"Going to create bucket :{bucket_name}\")\n",
    "        create_bucket_class_location(bucket_name)\n",
    "        \n",
    "    assert(bucket_name in list_buckets_names())\n",
    "\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c2993d8-f692-4f79-b9cc-cbc6a8726abb",
   "metadata": {},
   "source": [
    "## - 1.3) 🔥 Calling Gemini 🔥 (the magic is here ! )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "bd33028e-8f7a-4975-99aa-2c19a2c3e4af",
   "metadata": {},
   "outputs": [],
   "source": [
    "def generate(input_array, max_output_tokens=8192, temperature=1, top_p=0.95):\n",
    "    model = GenerativeModel(\"gemini-1.5-pro-preview-0409\")\n",
    "    params = {}\n",
    "    params[\"safety_settings\"] = {\n",
    "        generative_models.HarmCategory.HARM_CATEGORY_HATE_SPEECH: generative_models.HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE,\n",
    "        generative_models.HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT: generative_models.HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE,\n",
    "        generative_models.HarmCategory.HARM_CATEGORY_SEXUALLY_EXPLICIT: generative_models.HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE,\n",
    "        generative_models.HarmCategory.HARM_CATEGORY_HARASSMENT: generative_models.HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE,\n",
    "    }\n",
    "    params[\"generation_config\"] = {\"max_output_tokens\": max_output_tokens,\"temperature\": temperature,\"top_p\": top_p}\n",
    "    params[\"stream\"] = True\n",
    "    ##responses = model.generate_content(input_array,generation_config=generation_config,safety_settings=safety_settings, stream=True)\n",
    "    responses = model.generate_content(input_array,**params)\n",
    "    return responses\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c5ae5118-8cf5-441c-913d-6c5f09edd8b3",
   "metadata": {},
   "source": [
    "# 0) Parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "24e78c06-b0d7-4ad7-b10e-705d3dcc10f0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define the video URL\n",
    "video_url = \"https://www.youtube.com/watch?v=MFp4avqwJME\"\n",
    "video_url = \"https://youtu.be/REeUEBmvJqY\"\n",
    "video_url = \"https://www.youtube.com/watch?v=mEhoD5cGDOs\"\n",
    "video_url = \"https://www.youtube.com/watch?v=TowOva8ll3Q\"\n",
    "\n",
    "\n",
    "# Set with your own parameters\n",
    "PROJECT_ID = \"YOUR_PROJECT_ID\"\n",
    "bucket_name = \"NAME_YOUR_BUCKET\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd6881bd-04d4-400b-8638-be21f6d7e83c",
   "metadata": {},
   "source": [
    "# 1) Fetch the video"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "24c0ba65-56e6-4c5b-a941-c2f45319fed8",
   "metadata": {},
   "source": [
    "## 1.1) verify Vertex AI & bucket accessibility"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "611947aa-5e41-416c-94d8-b38bef176997",
   "metadata": {},
   "outputs": [],
   "source": [
    "vertexai.init(project=PROJECT_ID, location=\"us-central1\")\n",
    "create_bucket_if_doesnt_exist(bucket_name)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c3bbcddf-b16c-4e22-a6b3-c6adedbcf413",
   "metadata": {},
   "source": [
    "## 1.2) transfer youtube video to the bucket"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "0b257d81-b4bf-4301-9af5-28d7c6f80231",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Going to download https://www.youtube.com/watch?v=TowOva8ll3Q\n",
      "Downloaded into Budget participatif Saison 3   votez jusquau 11 juin !.mp4\n",
      "File [./Budget participatif Saison 3   votez jusquau 11 juin !.mp4] \n",
      "Uploaded to [./Budget_participatif_Saison_3___votez_jusquau_11_juin_!.mp4] \n",
      "In bucket [input-video-files-jr]\n"
     ]
    }
   ],
   "source": [
    "downloaded_video = download_video(video_url)\n",
    "uploaded_video = upload_file_to_bucket(bucket_name, downloaded_video)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3a9f1517-1b8e-418b-9406-34a8df0a6712",
   "metadata": {},
   "source": [
    "## 1.3) Add the video as a Part of the model\n",
    "Dans l'import from vertexai.generative_models import part, l'objet part représente une composante d'un modèle génératif Vertex AI. Il s'agit d'une unité de base qui peut être assemblée avec d'autres parties pour créer un modèle plus complexe.\n",
    "\n",
    "Chaque partie possède ses propres fonctionnalités et caractéristiques, et peut être utilisée pour générer différents types de contenu. Voici quelques exemples de parties :\n",
    "\n",
    "- Texte: génère du texte, comme des phrases, des paragraphes ou des articles entiers.\n",
    "- Code: génère du code, comme des scripts Python ou des fonctions Java.\n",
    "- Image: génère des images, comme des photos ou des illustrations.\n",
    "- Audio: génère du son, comme de la musique ou des voix.\n",
    "\n",
    "En plus de ces types de base, il existe également des parties plus spécialisées qui peuvent être utilisées pour des tâches spécifiques, comme :\n",
    "- la traduction, \n",
    "- la synthèse de discours \n",
    "- la génération de questions/réponses."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "906b36e0-22e6-4a3c-85a9-db5e6450278f",
   "metadata": {},
   "outputs": [],
   "source": [
    "uri_video_sur_bucket = f\"gs://{bucket_name}/{uploaded_video}\"\n",
    "mime_type = \"video/mp4\"\n",
    "parameters = {\"mime_type\"  : mime_type, \n",
    "              \"uri\"        : uri_video_sur_bucket }\n",
    "video = Part.from_uri(**parameters)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4bfb24f3-edc2-48be-a800-13cfd7ac60c7",
   "metadata": {},
   "source": [
    "# 2) Call Gemini to do the work"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "7394a75d-3b53-4b8e-aae1-bff14d392662",
   "metadata": {},
   "outputs": [],
   "source": [
    "prompt = \"\"\"Fais un chapitrage de cette video, et sors moi un joli code html pour présenter le chapitrage\"\"\"\n",
    "responses = generate([prompt, video])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8bad5d3d-0e3a-47e9-bc8e-601ae4113c1b",
   "metadata": {},
   "source": [
    "# 3) analyse the results"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f4798763-1204-4459-958c-0413cd424604",
   "metadata": {},
   "source": [
    "## 3.1) responses are in a generator, so we copy the answer in an array \n",
    "(not using a comprehension list so that we can have a user-interface feedback on on-going process)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "b9901903-2db7-45de-b79d-e3cffdd9746f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "..................."
     ]
    }
   ],
   "source": [
    "result = []\n",
    "for response in responses :\n",
    "    print(\".\",end=\"\")\n",
    "    result.append(response.text)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0bf65bfb-c491-4bae-a5ce-cf3c5213a1eb",
   "metadata": {},
   "source": [
    "## 3.2) Printing the result in the screen :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "d13526ca-8729-4094-8f29-0552a30a9661",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "##\n",
      " Chapitrage de la vidéo \"Budget Participatif - Saison 3\"\n",
      "\n",
      "\n",
      "**00:00** - Introduction : Titre \"Budget Participatif -\n",
      " Saison 3\"\n",
      "**00:01** - Témoignage d'une participante à la saison 2 \n",
      "**00:\n",
      "09** - \"Vous proposez\" : Mise en avant de la phase de proposition des projets par les citoyens\n",
      "**00:10** -\n",
      " \"Vous votez\" : Mise en avant de la phase de vote pour les projets proposés\n",
      "**00:11** - \"Nous réalisons\" : Mise en avant de la concrétisation des projets choisis par les citoyens\n",
      "\n",
      "**00:12** - Exemple de projet réalisé : Installation de composteurs\n",
      "**00:14** - Exemple de projet réalisé : Intervention de chiens en EHPAD\n",
      "**00:16**\n",
      " - Exemple de projet réalisé : Installation de nichoirs à oiseaux\n",
      "**00:17** - Exemple de projet réalisé : Création d'un jardin partagé\n",
      "**00:19** - Exemple de projet réalisé : Conférence TEDx\n",
      "**00:20** - Exemple\n",
      " de projet réalisé : Installation de tables de pique-nique \n",
      "**00:22** - Exemple de projet réalisé : Acquisition de casques d'audiodescription pour le cinéma\n",
      "**00:23** - Exemple de projet réalisé : Ateliers du rire pour seniors\n",
      "**00:\n",
      "29** - Appel à la participation : \"Vous avez jusqu'au 11 juin pour voter\"\n",
      "**00:31** - Information sur le site web : \"Rendez-vous sur jeparticipe.suresnes.fr\"\n",
      "**00:33** - Logo de la\n",
      " ville de Suresnes\n",
      "**00:34** - Fin de la vidéo \n",
      "\n",
      "## Code HTML pour présenter le chapitrage :\n",
      "\n",
      "```html\n",
      "<!DOCTYPE html>\n",
      "<html>\n",
      "<head>\n",
      "  <title>Chapitrage - Budget Participatif Suresnes</title>\n",
      "\n",
      "</head>\n",
      "<body>\n",
      "  <h1>Chapitrage de la vidéo \"Budget Participatif - Saison 3\"</h1>\n",
      "  <ul>\n",
      "    <li><strong>00:00</strong> - Introduction</li>\n",
      "    <li><strong>00:01</strong> - Témo\n",
      "ignage d'une participante</li>\n",
      "    <li><strong>00:09</strong> - Phase de proposition des projets</li>\n",
      "    <li><strong>00:10</strong> - Phase de vote</li>\n",
      "    <li><strong>00:11</strong> - Concré\n",
      "tisation des projets</li>\n",
      "    <li><strong>00:12</strong> - Exemple : Composteurs</li>\n",
      "    <li><strong>00:14</strong> - Exemple : Chiens en EHPAD</li>\n",
      "    <li><strong>00:16</strong>\n",
      " - Exemple : Nichoirs à oiseaux</li>\n",
      "    <li><strong>00:17</strong> - Exemple : Jardin partagé</li>\n",
      "    <li><strong>00:19</strong> - Exemple : Conférence TEDx</li>\n",
      "    <li><strong>00:2\n",
      "0</strong> - Exemple : Tables de pique-nique</li>\n",
      "    <li><strong>00:22</strong> - Exemple : Casques d'audiodescription</li>\n",
      "    <li><strong>00:23</strong> - Exemple : Ateliers du rire</li>\n",
      "    \n",
      "<li><strong>00:29</strong> - Appel à la participation</li>\n",
      "    <li><strong>00:31</strong> - Site web</li>\n",
      "    <li><strong>00:33</strong> - Logo de Suresnes</li>\n",
      "    <li><strong>0\n",
      "0:34</strong> - Fin</li>\n",
      "  </ul>\n",
      "</body>\n",
      "</html>\n",
      "```\n",
      "\n",
      "**Ce code HTML crée une page web simple avec un titre et une liste à puces pour présenter le chapitrage de la vidéo. Vous pouvez personnaliser le style de la page avec du\n",
      " CSS.** \n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(\"\\n\".join(result))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cf3e80f5-9bc9-47b2-8cfb-6f33890bfb8b",
   "metadata": {},
   "source": [
    "# 4) Putting every thing in a function : "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b32ad8bb-5a99-4449-8143-5ef605bb9e30",
   "metadata": {},
   "source": [
    "## 4.1) Creating the sum-up function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "f1afb011-aee4-492c-9133-f67f4bcd0363",
   "metadata": {},
   "outputs": [],
   "source": [
    "def prompt_video(prompt, uri_video_sur_bucket, verbose=False):\n",
    "    mime_type            = \"video/mp4\"\n",
    "    parameters           = {\"mime_type\"  : mime_type, \n",
    "                            \"uri\"        : uri_video_sur_bucket }\n",
    "    \n",
    "    video                = Part.from_uri(**parameters)    \n",
    "    if verbose: print(f\"going to generate : \\n{prompt}\\n {parameters}\")\n",
    "    responses            = generate([prompt, video])\n",
    "    return responses\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "defd4e53-f302-4998-a3e4-e70f5fc4ae2f",
   "metadata": {},
   "source": [
    "## 4.2) Testing "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "ec26afb1-bde1-4bb6-b93a-a95261289664",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Going to download https://www.youtube.com/watch?v=TowOva8ll3Q\n",
      "Downloaded into Budget participatif Saison 3   votez jusquau 11 juin !.mp4\n",
      "File [./Budget participatif Saison 3   votez jusquau 11 juin !.mp4] \n",
      "Uploaded to [./Budget_participatif_Saison_3___votez_jusquau_11_juin_!.mp4] \n",
      "In bucket [input-video-files-jr]\n",
      "................."
     ]
    }
   ],
   "source": [
    "prompt = \"\"\"Fais un chapitrage de cette video, et sors moi un joli code html pour présenter le chapitrage\"\"\"\n",
    "video_url = \"https://www.youtube.com/watch?v=TowOva8ll3Q\"\n",
    "\n",
    "uri_video_sur_bucket = upload_video_sur_bucket(video_url)\n",
    "responses            = prompt_video(prompt, uri_video_sur_bucket)\n",
    "result = []\n",
    "for response in responses :\n",
    "    result.append(response.text)\n",
    "    print(\".\",end=\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "657ff5e7-b61f-4c43-9204-cd21347e256d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "## Chapitrage de la vidéo \"Budget Participatif - Saison 3\"\n",
      "\n",
      "**Voici un chapitrage possible de la vidéo, avec les codes temporels et les titres des sections**:\n",
      "\n",
      "```html\n",
      "<!DOCTYPE html>\n",
      "<html>\n",
      "<head>\n",
      "  <title>Chapitrage - Budget Participatif Saison 3</title>\n",
      "</head>\n",
      "<body>\n",
      "  <h1>Chapitrage - Budget Participatif Saison 3</h1>\n",
      "  <ul>\n",
      "    <li><a href=\"#00:00\">Introduction</a> (00:00)</li>\n",
      "    <li><a href=\"#00:01\">Votez pour vos projets favoris !</a> (00:01)</li>\n",
      "    <li><a href=\"#00:09\">Vous proposez, vous votez, nous réalisons</a> (00:09)</li>\n",
      "    <li><a href=\"#00:12\">Exemples de projets réalisés</a> (00:12)\n",
      "      <ul>\n",
      "        <li><a href=\"#00:12\">Composteur</a> (00:12)</li>\n",
      "        <li><a href=\"#00:14\">Chiens dans les EHPAD</a> (00:14)</li>\n",
      "        <li><a href=\"#00:16\">Nichoirs à oiseaux</a> (00:16)</li>\n",
      "        <li><a href=\"#00:17\">Jardin partagé</a> (00:17)</li>\n",
      "        <li><a href=\"#00:19\">Tables de pique-nique</a> (00:19)</li>\n",
      "        <li><a href=\"#00:22\">Casques audiodescription</a> (00:22)</li>\n",
      "        <li><a href=\"#00:23\">Ateliers du rire pour séniors</a> (00:23)</li>\n",
      "      </ul>\n",
      "    </li>\n",
      "    <li><a href=\"#00:29\">Votez jusqu'au 11 juin !</a> (00:29)</li>\n",
      "    <li><a href=\"#00:31\">Rendez-vous sur jeparticipe.suresnes.fr</a> (00:31)</li>\n",
      "  </ul>\n",
      "</body>\n",
      "</html>\n",
      "```\n",
      "\n",
      "**Explications**:\n",
      "\n",
      "*   Le code HTML utilise des titres (h1) et des listes à puces (ul et li) pour structurer le chapitrage. \n",
      "*   Chaque section du chapitrage a un lien (a) avec un identifiant unique (href=\"#00:00\") qui permet de naviguer directement à la section correspondante dans la vidéo.\n",
      "*   La section \"Exemples de projets réalisés\" est une sous-liste pour montrer la diversité des projets. \n",
      "\n",
      "**Pour utiliser ce code**:\n",
      "\n",
      "1.  Enregistrez le code dans un fichier HTML (par exemple, chapitrage.html).\n",
      "2.  Ouvrez le fichier HTML dans un navigateur web.\n",
      "3.  Cliquez sur les liens pour accéder aux différentes sections de la vidéo. \n",
      "\n",
      "**Améliorations possibles**:\n",
      "\n",
      "*   Ajouter des descriptions plus détaillées pour chaque section.\n",
      "*   Intégrer la vidéo dans la page HTML avec les liens du chapitrage.\n",
      "*   Utiliser du CSS pour améliorer la présentation visuelle du chapitrage. \n",
      "\n",
      "\n",
      "**J'espère que ce chapitrage vous sera utile!** \n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(\"\".join(result))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7494f6b3-a317-484c-af21-f694f7985892",
   "metadata": {},
   "source": [
    "# 5) Playing with prompting the video 😊"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6ac634b9-da51-4c52-8c1b-8ef75b97e8d5",
   "metadata": {},
   "source": [
    "## 5.1) Asking Gemini to create interesting questions about the video"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "f508a50a-1cae-47fc-a680-064fafe84515",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "........."
     ]
    }
   ],
   "source": [
    "prompt = \"\"\"Génère moi une liste de cinq questions intéressantes qu'on pourrait se poser sur cette vidéo, et dont les réponses sont dans la vidéo.\"\"\"\n",
    "responses = prompt_video(prompt, uri_video_sur_bucket)\n",
    "result = []\n",
    "for response in responses :\n",
    "    result.append(response.text)\n",
    "    print(\".\",end=\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "fdac1795-bbf9-451c-9f47-be6b982967ec",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "## Questions sur la vidéo \"Budget participatif - Suresnes\":\n",
      "\n",
      "1. **À quelle saison du budget participatif la vidéo fait-elle référence?**  La vidéo mentionne clairement qu'il s'agit de la saison 3 du budget participatif. \n",
      "2. **Quelle est la date limite pour voter pour les projets?**  La vidéo indique que les citoyens ont jusqu'au 11 juin pour voter pour leurs projets favoris. \n",
      "3. **Quels sont quelques exemples de projets présentés dans la vidéo?**  Plusieurs exemples sont montrés, notamment l'installation d'un composteur, la visite de chiens en EHPAD, l'installation de nichoirs à oiseaux, la création d'un jardin partagé, la mise à disposition de tables de pique-nique, l'acquisition de casques d'audiodescription pour le cinéma et l'organisation d'ateliers du rire pour les séniors.\n",
      "4. **Quel est le site web mentionné pour participer?**  La vidéo invite les citoyens à se rendre sur le site \"jeparticipe.suresnes.fr\" pour participer au budget participatif. \n",
      "5. **Quel est l'organisme qui organise ce budget participatif?**   Le logo de la ville de Suresnes apparaît à la fin de la vidéo, indiquant qu'elle est l'organisatrice du budget participatif. \n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(\"\".join(result))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9e02b0c9-cd26-4e76-8fb0-e80483632274",
   "metadata": {},
   "source": [
    "## 5.2) Asking Gemini to answer to his own-created questions"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9439df52-fd11-428a-b4e8-e1d012e972df",
   "metadata": {},
   "source": [
    "### 5.2.1) extracting the questions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "889452c7-6697-405f-95b5-a6c98e662c74",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['À quelle saison du budget participatif la vidéo fait-elle référence?',\n",
       " 'Quelle est la date limite pour voter pour les projets?',\n",
       " 'Quels sont quelques exemples de projets présentés dans la vidéo?',\n",
       " 'Quel est le site web mentionné pour participer?',\n",
       " \"Quel est l'organisme qui organise ce budget participatif?\"]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prompts = \"\".join(result)\n",
    "questions = list(filter(lambda x: \"?\" in x, prompts.split(\"**\")))\n",
    "questions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "db5c80db-0c37-4e3d-8276-859c45b3cf3d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "À quelle saison du budget participatif la vidéo fait-elle référence?\n",
      "La vidéo fait référence à la saison 3 du budget participatif.\n",
      " ________________________________________________________________________________\n",
      "Quelle est la date limite pour voter pour les projets?\n",
      "La date limite pour voter pour les projets du budget participatif était le 11 juin.\n",
      " ________________________________________________________________________________\n",
      "Quels sont quelques exemples de projets présentés dans la vidéo?\n",
      "## Exemples de projets présentés dans la vidéo :\n",
      "\n",
      "La vidéo met en avant plusieurs exemples de projets soumis au budget participatif de Suresnes. Voici quelques exemples :\n",
      "\n",
      "* **Composteur :** Mise en place d'un composteur collectif pour les habitants.\n",
      "* **Chiens dans les EHPAD :** Visite de chiens aux résidents des EHPAD pour apporter du réconfort et de la compagnie.\n",
      "* **Nichoirs à oiseaux :** Installation de nichoirs à oiseaux pour favoriser la biodiversité.\n",
      "* **Jardin partagé :** Création d'un jardin partagé où les habitants peuvent cultiver des fruits et légumes ensemble.\n",
      "* **Tables de pique-nique :** Installation de tables de pique-nique dans les parcs et espaces verts.\n",
      "* **Casques audiodescription :** Mise à disposition de casques audiodescription au cinéma pour les personnes malvoyantes.\n",
      "* **Ateliers du rire pour séniors :** Organisation d'ateliers du rire pour les séniors afin de favoriser le bien-être et la convivialité.\n",
      "\n",
      "Ces exemples illustrent la diversité des projets proposés dans le cadre du budget participatif et montrent comment les habitants peuvent contribuer à améliorer leur cadre de vie.\n",
      "\n",
      " ________________________________________________________________________________\n",
      "Quel est le site web mentionné pour participer?\n",
      "Le site web mentionné pour participer est jeparticipe.suresnes.fr.\n",
      " ________________________________________________________________________________\n",
      "Quel est l'organisme qui organise ce budget participatif?\n",
      "## Budget Participatif de Suresnes\n",
      "\n",
      "L'organisme qui organise ce budget participatif est la **ville de Suresnes**, située dans le département des Hauts-de-Seine en France. \n",
      "\n",
      " ________________________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "for prompt in questions : \n",
    "    print(prompt)\n",
    "    responses = prompt_video(prompt, uri_video_sur_bucket)\n",
    "    for response in responses :\n",
    "        print(response.text,end=\"\")\n",
    "    print(\"\\n\", \"_\"*80)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7ee3fa3c-c6e4-4b65-b88d-6fc7dc9a951f",
   "metadata": {},
   "source": [
    "# End 🎉"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dc593a3c-422c-4485-99b0-cb14fd8042f8",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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