{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "bWCevV4Dcqfp",
    "outputId": "aa5d1c2c-9ab2-4d5a-d1ed-e2a78d4f2648"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: tiktoken in /usr/local/lib/python3.10/dist-packages (0.8.0)\n",
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      "Requirement already satisfied: pinecone in /usr/local/lib/python3.10/dist-packages (5.4.0)\n",
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      "Requirement already satisfied: propcache>=0.2.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp<4.0.0,>=3.8.3->langchain-community) (0.2.0)\n",
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      "Requirement already satisfied: async-timeout<6.0,>=4.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp<4.0.0,>=3.8.3->langchain-community) (4.0.3)\n",
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      "Requirement already satisfied: typing-inspect<1,>=0.4.0 in /usr/local/lib/python3.10/dist-packages (from dataclasses-json<0.7,>=0.5.7->langchain-community) (0.9.0)\n",
      "Requirement already satisfied: langchain-text-splitters<0.4.0,>=0.3.0 in /usr/local/lib/python3.10/dist-packages (from langchain<0.4.0,>=0.3.7->langchain-community) (0.3.2)\n",
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      "Requirement already satisfied: anyio in /usr/local/lib/python3.10/dist-packages (from httpx<1,>=0.23.0->langsmith<0.2.0,>=0.1.125->langchain-community) (3.7.1)\n",
      "Requirement already satisfied: httpcore==1.* in /usr/local/lib/python3.10/dist-packages (from httpx<1,>=0.23.0->langsmith<0.2.0,>=0.1.125->langchain-community) (1.0.7)\n",
      "Requirement already satisfied: sniffio in /usr/local/lib/python3.10/dist-packages (from httpx<1,>=0.23.0->langsmith<0.2.0,>=0.1.125->langchain-community) (1.3.1)\n",
      "Requirement already satisfied: h11<0.15,>=0.13 in /usr/local/lib/python3.10/dist-packages (from httpcore==1.*->httpx<1,>=0.23.0->langsmith<0.2.0,>=0.1.125->langchain-community) (0.14.0)\n",
      "Requirement already satisfied: jsonpointer>=1.9 in /usr/local/lib/python3.10/dist-packages (from jsonpatch<2.0,>=1.33->langchain-core<0.4.0,>=0.3.17->langchain-community) (3.0.0)\n",
      "Requirement already satisfied: annotated-types>=0.6.0 in /usr/local/lib/python3.10/dist-packages (from pydantic<3.0.0,>=2.7.4->langchain<0.4.0,>=0.3.7->langchain-community) (0.7.0)\n",
      "Requirement already satisfied: pydantic-core==2.23.4 in /usr/local/lib/python3.10/dist-packages (from pydantic<3.0.0,>=2.7.4->langchain<0.4.0,>=0.3.7->langchain-community) (2.23.4)\n",
      "Requirement already satisfied: mypy-extensions>=0.3.0 in /usr/local/lib/python3.10/dist-packages (from typing-inspect<1,>=0.4.0->dataclasses-json<0.7,>=0.5.7->langchain-community) (1.0.0)\n",
      "Requirement already satisfied: exceptiongroup in /usr/local/lib/python3.10/dist-packages (from anyio->httpx<1,>=0.23.0->langsmith<0.2.0,>=0.1.125->langchain-community) (1.2.2)\n"
     ]
    }
   ],
   "source": [
    "# Dependencies\n",
    "!pip install tiktoken\n",
    "!pip install groq\n",
    "!pip install langchain-groq\n",
    "!pip install pinecone\n",
    "!pip install langchain-community"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "5xY3Bah2c07v",
    "outputId": "647c33d0-f1c0-4bdf-9084-749e7e3db37d"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n",
      "Archive:  /content/drive/MyDrive/IMDB_Dataset.zip\n",
      "replace IMDB_Dataset.csv? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
      "  inflating: IMDB_Dataset.csv        \n"
     ]
    }
   ],
   "source": [
    "# Mount Dataset from Google Drive\n",
    "from google.colab import drive\n",
    "drive.mount('/content/drive')\n",
    "!unzip /content/drive/MyDrive/IMDB_Dataset.zip"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "WaKOeRVWdVEJ"
   },
   "outputs": [],
   "source": [
    "# Import Libraries\n",
    "import os\n",
    "import pandas as pd\n",
    "import tiktoken\n",
    "\n",
    "from groq import Groq\n",
    "from langchain_groq import ChatGroq\n",
    "from langchain.chains import RetrievalQA\n",
    "from langchain.prompts import PromptTemplate\n",
    "from langchain_community.embeddings import HuggingFaceEmbeddings\n",
    "from langchain_core.documents import Document\n",
    "\n",
    "from pinecone import Pinecone, ServerlessSpec\n",
    "from langchain_community.vectorstores import Pinecone as PineconeVectorStore\n",
    "\n",
    "import io\n",
    "from contextlib import redirect_stdout\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "sLED8nWs_s_5"
   },
   "outputs": [],
   "source": [
    "#Groq API Key\n",
    "groq_api_key = \"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "UeRNSsk1__9J"
   },
   "outputs": [],
   "source": [
    "# Load and preprocess data\n",
    "imdb= pd.read_csv('/content/IMDB_Dataset.csv')\n",
    "imdb = imdb.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "F-mePCMfAFfi"
   },
   "outputs": [],
   "source": [
    "# Create combined information column\n",
    "imdb['combined_info'] = imdb.apply(lambda row: f\"Title: {row['movie_name']}. Overview: {row['description']} Genres: {row['genre']} Certificate: {row['certificate']} Director: {row['director']} Actors: {row['star']}\", axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 483
    },
    "id": "xXRf0LKHAMUI",
    "outputId": "5b108e48-ef87-48b9-e856-ee7bff6adb46"
   },
   "outputs": [
    {
     "data": {
      "application/vnd.google.colaboratory.intrinsic+json": {
       "summary": "{\n  \"name\": \"imdb\",\n  \"rows\": 13001,\n  \"fields\": [\n    {\n      \"column\": \"movie_name\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 12500,\n        \"samples\": [\n          \"Slaughterhouse Rulez\",\n          \"A Chemical Skyline\",\n          \"Yaan\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"certificate\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 27,\n        \"samples\": [\n          \"13+\",\n          \"M\",\n          \"G\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"genre\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 254,\n        \"samples\": [\n          \"Action, Crime, Western\",\n          \"Action, Drama, War\",\n          \"Action, War\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"rating\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.303996714573187,\n        \"min\": 1.2,\n        \"max\": 9.7,\n        \"num_unique_values\": 83,\n        \"samples\": [\n          8.1,\n          6.9,\n          4.8\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"description\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 12867,\n        \"samples\": [\n          \"A vicious biker gang is intent on destroying a small town in Arizona. A war veteran visiting an old friend and a few locals with nothing to lose go to war with the gang's ruthless leader.\",\n          \"In the aftermath of a massive earthquake in California, a rescue-chopper pilot makes a dangerous journey with his ex-wife across the state in order to rescue his daughter.\",\n          \"After thirty years, Maverick is still pushing the envelope as a top naval aviator, but must confront ghosts of his past when he leads TOP GUN's elite graduates on a mission that demands the ultimate sacrifice from those chosen to fly it.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"director\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 7192,\n        \"samples\": [\n          \"Dan Neira\",\n          \"Lew Landers\",\n          \"Ray O'Neill\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"star\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 12923,\n        \"samples\": [\n          \"Douglas Fairbanks, \\nWilliam Farnum, \\nEarle Browne, \\nMaria Alba\",\n          \"Junko Takeuchi, \\nChie Nakamura, \\nSatoshi Hino, \\nRikiya Koyama\",\n          \"Martin Kove, \\nRobert Loggia, \\nJoyce DeWitt, \\nCharles Durning\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"combined_info\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 13001,\n        \"samples\": [\n          \"Title: Versus. Overview: There are 666 portals that connect this world to the other side. These are concealed from all human beings. Somewhere in Japan exists the 444th portal.... The forest of resurrection. Genres: Action, Drama, Fantasy Certificate: R Director: Ry\\u00fbhei Kitamura Actors: Tak Sakaguchi, \\nHideo Sakaki, \\nChieko Misaka, \\nKenji Matsuda\",\n          \"Title: The Eight Hundred. Overview: From the acclaimed filmmaker behind Mr. Six comes a riveting war epic. In 1937, eight hundred Chinese soldiers fight under siege from a warehouse in the middle of the Shanghai battlefield, completely surrounded by the Japanese army. Genres: Action, Drama, History Certificate: Not Rated Director: Hu Guan Actors: Zhizhong Huang, \\nJunyi Zhang, \\nHao Ou, \\nXiaoguang Hu\",\n          \"Title: S*P*Y*S. Overview: Two spies end up being chased by the CIA, the KGB, and a group of anarchists after a botched mission invoked an unwritten \\\"corpse for a corpse\\\" pact. Genres: Action, Comedy Certificate: PG Director: Irvin Kershner Actors: Donald Sutherland, \\nElliott Gould, \\nZouzou, \\nJoss Ackland\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"n_tokens\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 14,\n        \"min\": 36,\n        \"max\": 294,\n        \"num_unique_values\": 106,\n        \"samples\": [\n          44,\n          91,\n          100\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"vector\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}",
       "type": "dataframe",
       "variable_name": "imdb"
      },
      "text/html": [
       "\n",
       "  <div id=\"df-93faacb0-143f-42c2-93a3-e29203e1fcb3\" class=\"colab-df-container\">\n",
       "    <div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>movie_name</th>\n",
       "      <th>certificate</th>\n",
       "      <th>genre</th>\n",
       "      <th>rating</th>\n",
       "      <th>description</th>\n",
       "      <th>director</th>\n",
       "      <th>star</th>\n",
       "      <th>combined_info</th>\n",
       "      <th>n_tokens</th>\n",
       "      <th>vector</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Black Panther: Wakanda Forever</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>Action, Adventure, Drama</td>\n",
       "      <td>6.9</td>\n",
       "      <td>The people of Wakanda fight to protect their h...</td>\n",
       "      <td>Ryan Coogler</td>\n",
       "      <td>Letitia Wright, \\nLupita Nyong'o, \\nDanai Guri...</td>\n",
       "      <td>Title: Black Panther: Wakanda Forever. Overvie...</td>\n",
       "      <td>80</td>\n",
       "      <td>[-0.026855934411287308, 0.05683119595050812, -...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Avatar: The Way of Water</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>Action, Adventure, Fantasy</td>\n",
       "      <td>7.8</td>\n",
       "      <td>Jake Sully lives with his newfound family form...</td>\n",
       "      <td>James Cameron</td>\n",
       "      <td>Sam Worthington, \\nZoe Saldana, \\nSigourney We...</td>\n",
       "      <td>Title: Avatar: The Way of Water. Overview: Jak...</td>\n",
       "      <td>99</td>\n",
       "      <td>[-0.080960214138031, 0.012261789292097092, 0.0...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Plane</td>\n",
       "      <td>R</td>\n",
       "      <td>Action, Thriller</td>\n",
       "      <td>6.5</td>\n",
       "      <td>A pilot finds himself caught in a war zone aft...</td>\n",
       "      <td>Jean-François Richet</td>\n",
       "      <td>Gerard Butler, \\nMike Colter, \\nTony Goldwyn, ...</td>\n",
       "      <td>Title: Plane. Overview: A pilot finds himself ...</td>\n",
       "      <td>67</td>\n",
       "      <td>[0.02219153568148613, -0.0190700925886631, -0....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Everything Everywhere All at Once</td>\n",
       "      <td>R</td>\n",
       "      <td>Action, Adventure, Comedy</td>\n",
       "      <td>8.0</td>\n",
       "      <td>A middle-aged Chinese immigrant is swept up in...</td>\n",
       "      <td>Dan Kwan, \\nDaniel Scheinert</td>\n",
       "      <td>Michelle Yeoh, \\nStephanie Hsu, \\nJamie Lee Cu...</td>\n",
       "      <td>Title: Everything Everywhere All at Once. Over...</td>\n",
       "      <td>90</td>\n",
       "      <td>[0.038551680743694305, -0.023787647485733032, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Ant-Man and the Wasp: Quantumania</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>Action, Adventure, Comedy</td>\n",
       "      <td>6.6</td>\n",
       "      <td>Scott Lang and Hope Van Dyne, along with Hank ...</td>\n",
       "      <td>Peyton Reed</td>\n",
       "      <td>Paul Rudd, \\nEvangeline Lilly, \\nJonathan Majo...</td>\n",
       "      <td>Title: Ant-Man and the Wasp: Quantumania. Over...</td>\n",
       "      <td>100</td>\n",
       "      <td>[-0.07330965995788574, -0.046703167259693146, ...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>\n",
       "    <div class=\"colab-df-buttons\">\n",
       "\n",
       "  <div class=\"colab-df-container\">\n",
       "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-93faacb0-143f-42c2-93a3-e29203e1fcb3')\"\n",
       "            title=\"Convert this dataframe to an interactive table.\"\n",
       "            style=\"display:none;\">\n",
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       "    </button>\n",
       "\n",
       "  <style>\n",
       "    .colab-df-container {\n",
       "      display:flex;\n",
       "      gap: 12px;\n",
       "    }\n",
       "\n",
       "    .colab-df-convert {\n",
       "      background-color: #E8F0FE;\n",
       "      border: none;\n",
       "      border-radius: 50%;\n",
       "      cursor: pointer;\n",
       "      display: none;\n",
       "      fill: #1967D2;\n",
       "      height: 32px;\n",
       "      padding: 0 0 0 0;\n",
       "      width: 32px;\n",
       "    }\n",
       "\n",
       "    .colab-df-convert:hover {\n",
       "      background-color: #E2EBFA;\n",
       "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
       "      fill: #174EA6;\n",
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       "\n",
       "    .colab-df-buttons div {\n",
       "      margin-bottom: 4px;\n",
       "    }\n",
       "\n",
       "    [theme=dark] .colab-df-convert {\n",
       "      background-color: #3B4455;\n",
       "      fill: #D2E3FC;\n",
       "    }\n",
       "\n",
       "    [theme=dark] .colab-df-convert:hover {\n",
       "      background-color: #434B5C;\n",
       "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
       "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
       "      fill: #FFFFFF;\n",
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       "  </style>\n",
       "\n",
       "    <script>\n",
       "      const buttonEl =\n",
       "        document.querySelector('#df-93faacb0-143f-42c2-93a3-e29203e1fcb3 button.colab-df-convert');\n",
       "      buttonEl.style.display =\n",
       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
       "\n",
       "      async function convertToInteractive(key) {\n",
       "        const element = document.querySelector('#df-93faacb0-143f-42c2-93a3-e29203e1fcb3');\n",
       "        const dataTable =\n",
       "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
       "                                                    [key], {});\n",
       "        if (!dataTable) return;\n",
       "\n",
       "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
       "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
       "          + ' to learn more about interactive tables.';\n",
       "        element.innerHTML = '';\n",
       "        dataTable['output_type'] = 'display_data';\n",
       "        await google.colab.output.renderOutput(dataTable, element);\n",
       "        const docLink = document.createElement('div');\n",
       "        docLink.innerHTML = docLinkHtml;\n",
       "        element.appendChild(docLink);\n",
       "      }\n",
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       "\n",
       "\n",
       "<div id=\"df-8786586b-889b-4a6e-8bda-351b74b07c68\">\n",
       "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-8786586b-889b-4a6e-8bda-351b74b07c68')\"\n",
       "            title=\"Suggest charts\"\n",
       "            style=\"display:none;\">\n",
       "\n",
       "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
       "     width=\"24px\">\n",
       "    <g>\n",
       "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
       "    </g>\n",
       "</svg>\n",
       "  </button>\n",
       "\n",
       "<style>\n",
       "  .colab-df-quickchart {\n",
       "      --bg-color: #E8F0FE;\n",
       "      --fill-color: #1967D2;\n",
       "      --hover-bg-color: #E2EBFA;\n",
       "      --hover-fill-color: #174EA6;\n",
       "      --disabled-fill-color: #AAA;\n",
       "      --disabled-bg-color: #DDD;\n",
       "  }\n",
       "\n",
       "  [theme=dark] .colab-df-quickchart {\n",
       "      --bg-color: #3B4455;\n",
       "      --fill-color: #D2E3FC;\n",
       "      --hover-bg-color: #434B5C;\n",
       "      --hover-fill-color: #FFFFFF;\n",
       "      --disabled-bg-color: #3B4455;\n",
       "      --disabled-fill-color: #666;\n",
       "  }\n",
       "\n",
       "  .colab-df-quickchart {\n",
       "    background-color: var(--bg-color);\n",
       "    border: none;\n",
       "    border-radius: 50%;\n",
       "    cursor: pointer;\n",
       "    display: none;\n",
       "    fill: var(--fill-color);\n",
       "    height: 32px;\n",
       "    padding: 0;\n",
       "    width: 32px;\n",
       "  }\n",
       "\n",
       "  .colab-df-quickchart:hover {\n",
       "    background-color: var(--hover-bg-color);\n",
       "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
       "    fill: var(--button-hover-fill-color);\n",
       "  }\n",
       "\n",
       "  .colab-df-quickchart-complete:disabled,\n",
       "  .colab-df-quickchart-complete:disabled:hover {\n",
       "    background-color: var(--disabled-bg-color);\n",
       "    fill: var(--disabled-fill-color);\n",
       "    box-shadow: none;\n",
       "  }\n",
       "\n",
       "  .colab-df-spinner {\n",
       "    border: 2px solid var(--fill-color);\n",
       "    border-color: transparent;\n",
       "    border-bottom-color: var(--fill-color);\n",
       "    animation:\n",
       "      spin 1s steps(1) infinite;\n",
       "  }\n",
       "\n",
       "  @keyframes spin {\n",
       "    0% {\n",
       "      border-color: transparent;\n",
       "      border-bottom-color: var(--fill-color);\n",
       "      border-left-color: var(--fill-color);\n",
       "    }\n",
       "    20% {\n",
       "      border-color: transparent;\n",
       "      border-left-color: var(--fill-color);\n",
       "      border-top-color: var(--fill-color);\n",
       "    }\n",
       "    30% {\n",
       "      border-color: transparent;\n",
       "      border-left-color: var(--fill-color);\n",
       "      border-top-color: var(--fill-color);\n",
       "      border-right-color: var(--fill-color);\n",
       "    }\n",
       "    40% {\n",
       "      border-color: transparent;\n",
       "      border-right-color: var(--fill-color);\n",
       "      border-top-color: var(--fill-color);\n",
       "    }\n",
       "    60% {\n",
       "      border-color: transparent;\n",
       "      border-right-color: var(--fill-color);\n",
       "    }\n",
       "    80% {\n",
       "      border-color: transparent;\n",
       "      border-right-color: var(--fill-color);\n",
       "      border-bottom-color: var(--fill-color);\n",
       "    }\n",
       "    90% {\n",
       "      border-color: transparent;\n",
       "      border-bottom-color: var(--fill-color);\n",
       "    }\n",
       "  }\n",
       "</style>\n",
       "\n",
       "  <script>\n",
       "    async function quickchart(key) {\n",
       "      const quickchartButtonEl =\n",
       "        document.querySelector('#' + key + ' button');\n",
       "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
       "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
       "      try {\n",
       "        const charts = await google.colab.kernel.invokeFunction(\n",
       "            'suggestCharts', [key], {});\n",
       "      } catch (error) {\n",
       "        console.error('Error during call to suggestCharts:', error);\n",
       "      }\n",
       "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
       "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
       "    }\n",
       "    (() => {\n",
       "      let quickchartButtonEl =\n",
       "        document.querySelector('#df-8786586b-889b-4a6e-8bda-351b74b07c68 button');\n",
       "      quickchartButtonEl.style.display =\n",
       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
       "    })();\n",
       "  </script>\n",
       "</div>\n",
       "\n",
       "    </div>\n",
       "  </div>\n"
      ],
      "text/plain": [
       "                          movie_name certificate                       genre  \\\n",
       "0     Black Panther: Wakanda Forever       PG-13    Action, Adventure, Drama   \n",
       "1           Avatar: The Way of Water       PG-13  Action, Adventure, Fantasy   \n",
       "2                              Plane           R            Action, Thriller   \n",
       "3  Everything Everywhere All at Once           R   Action, Adventure, Comedy   \n",
       "5  Ant-Man and the Wasp: Quantumania       PG-13   Action, Adventure, Comedy   \n",
       "\n",
       "   rating                                        description  \\\n",
       "0     6.9  The people of Wakanda fight to protect their h...   \n",
       "1     7.8  Jake Sully lives with his newfound family form...   \n",
       "2     6.5  A pilot finds himself caught in a war zone aft...   \n",
       "3     8.0  A middle-aged Chinese immigrant is swept up in...   \n",
       "5     6.6  Scott Lang and Hope Van Dyne, along with Hank ...   \n",
       "\n",
       "                       director  \\\n",
       "0                  Ryan Coogler   \n",
       "1                 James Cameron   \n",
       "2          Jean-François Richet   \n",
       "3  Dan Kwan, \\nDaniel Scheinert   \n",
       "5                   Peyton Reed   \n",
       "\n",
       "                                                star  \\\n",
       "0  Letitia Wright, \\nLupita Nyong'o, \\nDanai Guri...   \n",
       "1  Sam Worthington, \\nZoe Saldana, \\nSigourney We...   \n",
       "2  Gerard Butler, \\nMike Colter, \\nTony Goldwyn, ...   \n",
       "3  Michelle Yeoh, \\nStephanie Hsu, \\nJamie Lee Cu...   \n",
       "5  Paul Rudd, \\nEvangeline Lilly, \\nJonathan Majo...   \n",
       "\n",
       "                                       combined_info  n_tokens  \\\n",
       "0  Title: Black Panther: Wakanda Forever. Overvie...        80   \n",
       "1  Title: Avatar: The Way of Water. Overview: Jak...        99   \n",
       "2  Title: Plane. Overview: A pilot finds himself ...        67   \n",
       "3  Title: Everything Everywhere All at Once. Over...        90   \n",
       "5  Title: Ant-Man and the Wasp: Quantumania. Over...       100   \n",
       "\n",
       "                                              vector  \n",
       "0  [-0.026855934411287308, 0.05683119595050812, -...  \n",
       "1  [-0.080960214138031, 0.012261789292097092, 0.0...  \n",
       "2  [0.02219153568148613, -0.0190700925886631, -0....  \n",
       "3  [0.038551680743694305, -0.023787647485733032, ...  \n",
       "5  [-0.07330965995788574, -0.046703167259693146, ...  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# View Dataframe with combined info\n",
    "imdb.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 563,
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    "id": "iqtXSVLSAQjV",
    "outputId": "8719b8ff-3d46-4394-f666-000a011e5db2"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-10-7c9c09a7ef16>:10: LangChainDeprecationWarning: The class `HuggingFaceEmbeddings` was deprecated in LangChain 0.2.2 and will be removed in 1.0. An updated version of the class exists in the :class:`~langchain-huggingface package and should be used instead. To use it run `pip install -U :class:`~langchain-huggingface` and import as `from :class:`~langchain_huggingface import HuggingFaceEmbeddings``.\n",
      "  embeddings = HuggingFaceEmbeddings(\n",
      "/usr/local/lib/python3.10/dist-packages/sentence_transformers/cross_encoder/CrossEncoder.py:13: TqdmExperimentalWarning: Using `tqdm.autonotebook.tqdm` in notebook mode. Use `tqdm.tqdm` instead to force console mode (e.g. in jupyter console)\n",
      "  from tqdm.autonotebook import tqdm, trange\n",
      "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_auth.py:94: UserWarning: \n",
      "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
      "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
      "You will be able to reuse this secret in all of your notebooks.\n",
      "Please note that authentication is recommended but still optional to access public models or datasets.\n",
      "  warnings.warn(\n"
     ]
    },
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       "modules.json:   0%|          | 0.00/349 [00:00<?, ?B/s]"
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      "text/plain": [
       "config_sentence_transformers.json:   0%|          | 0.00/116 [00:00<?, ?B/s]"
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      "text/plain": [
       "README.md:   0%|          | 0.00/10.7k [00:00<?, ?B/s]"
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     },
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       "sentence_bert_config.json:   0%|          | 0.00/53.0 [00:00<?, ?B/s]"
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       "model.safetensors:   0%|          | 0.00/90.9M [00:00<?, ?B/s]"
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     "output_type": "display_data"
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      "text/plain": [
       "vocab.txt:   0%|          | 0.00/232k [00:00<?, ?B/s]"
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    {
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    {
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      "text/plain": [
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    },
    {
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      "text/plain": [
       "1_Pooling/config.json:   0%|          | 0.00/190 [00:00<?, ?B/s]"
      ]
     },
     "metadata": {},
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   ],
   "source": [
    "# Token encoding\n",
    "encoding = tiktoken.get_encoding('cl100k_base')\n",
    "max_tokens = 8000\n",
    "\n",
    "# Omit descriptions that are too long to embed\n",
    "imdb[\"n_tokens\"] = imdb.combined_info.apply(lambda x: len(encoding.encode(x)))\n",
    "imdb = imdb[imdb.n_tokens <= max_tokens]\n",
    "\n",
    "# Use HuggingFace embeddings instead of OpenAI\n",
    "embeddings = HuggingFaceEmbeddings(\n",
    "    model_name=\"sentence-transformers/all-MiniLM-L6-v2\"\n",
    ")\n",
    "\n",
    "# Generate embeddings\n",
    "imdb[\"vector\"] = imdb.combined_info.apply(lambda x: embeddings.embed_query(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 483
    },
    "id": "IZqXex8TAYac",
    "outputId": "6d650462-bbac-4af9-9b3a-c4b8d3bd6baa"
   },
   "outputs": [
    {
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       "summary": "{\n  \"name\": \"imdb\",\n  \"rows\": 13001,\n  \"fields\": [\n    {\n      \"column\": \"movie_name\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 12500,\n        \"samples\": [\n          \"Slaughterhouse Rulez\",\n          \"A Chemical Skyline\",\n          \"Yaan\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"certificate\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 27,\n        \"samples\": [\n          \"13+\",\n          \"M\",\n          \"G\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"genre\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 254,\n        \"samples\": [\n          \"Action, Crime, Western\",\n          \"Action, Drama, War\",\n          \"Action, War\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"rating\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.303996714573187,\n        \"min\": 1.2,\n        \"max\": 9.7,\n        \"num_unique_values\": 83,\n        \"samples\": [\n          8.1,\n          6.9,\n          4.8\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"description\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 12867,\n        \"samples\": [\n          \"A vicious biker gang is intent on destroying a small town in Arizona. A war veteran visiting an old friend and a few locals with nothing to lose go to war with the gang's ruthless leader.\",\n          \"In the aftermath of a massive earthquake in California, a rescue-chopper pilot makes a dangerous journey with his ex-wife across the state in order to rescue his daughter.\",\n          \"After thirty years, Maverick is still pushing the envelope as a top naval aviator, but must confront ghosts of his past when he leads TOP GUN's elite graduates on a mission that demands the ultimate sacrifice from those chosen to fly it.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"director\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 7192,\n        \"samples\": [\n          \"Dan Neira\",\n          \"Lew Landers\",\n          \"Ray O'Neill\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"star\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 12923,\n        \"samples\": [\n          \"Douglas Fairbanks, \\nWilliam Farnum, \\nEarle Browne, \\nMaria Alba\",\n          \"Junko Takeuchi, \\nChie Nakamura, \\nSatoshi Hino, \\nRikiya Koyama\",\n          \"Martin Kove, \\nRobert Loggia, \\nJoyce DeWitt, \\nCharles Durning\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"combined_info\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 13001,\n        \"samples\": [\n          \"Title: Versus. Overview: There are 666 portals that connect this world to the other side. These are concealed from all human beings. Somewhere in Japan exists the 444th portal.... The forest of resurrection. Genres: Action, Drama, Fantasy Certificate: R Director: Ry\\u00fbhei Kitamura Actors: Tak Sakaguchi, \\nHideo Sakaki, \\nChieko Misaka, \\nKenji Matsuda\",\n          \"Title: The Eight Hundred. Overview: From the acclaimed filmmaker behind Mr. Six comes a riveting war epic. In 1937, eight hundred Chinese soldiers fight under siege from a warehouse in the middle of the Shanghai battlefield, completely surrounded by the Japanese army. Genres: Action, Drama, History Certificate: Not Rated Director: Hu Guan Actors: Zhizhong Huang, \\nJunyi Zhang, \\nHao Ou, \\nXiaoguang Hu\",\n          \"Title: S*P*Y*S. Overview: Two spies end up being chased by the CIA, the KGB, and a group of anarchists after a botched mission invoked an unwritten \\\"corpse for a corpse\\\" pact. Genres: Action, Comedy Certificate: PG Director: Irvin Kershner Actors: Donald Sutherland, \\nElliott Gould, \\nZouzou, \\nJoss Ackland\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"n_tokens\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 14,\n        \"min\": 36,\n        \"max\": 294,\n        \"num_unique_values\": 106,\n        \"samples\": [\n          44,\n          91,\n          100\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"vector\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>movie_name</th>\n",
       "      <th>certificate</th>\n",
       "      <th>genre</th>\n",
       "      <th>rating</th>\n",
       "      <th>description</th>\n",
       "      <th>director</th>\n",
       "      <th>star</th>\n",
       "      <th>combined_info</th>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Black Panther: Wakanda Forever</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>Action, Adventure, Drama</td>\n",
       "      <td>6.9</td>\n",
       "      <td>The people of Wakanda fight to protect their h...</td>\n",
       "      <td>Ryan Coogler</td>\n",
       "      <td>Letitia Wright, \\nLupita Nyong'o, \\nDanai Guri...</td>\n",
       "      <td>Title: Black Panther: Wakanda Forever. Overvie...</td>\n",
       "      <td>80</td>\n",
       "      <td>[-0.026855934411287308, 0.05683119595050812, -...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Avatar: The Way of Water</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>Action, Adventure, Fantasy</td>\n",
       "      <td>7.8</td>\n",
       "      <td>Jake Sully lives with his newfound family form...</td>\n",
       "      <td>James Cameron</td>\n",
       "      <td>Sam Worthington, \\nZoe Saldana, \\nSigourney We...</td>\n",
       "      <td>Title: Avatar: The Way of Water. Overview: Jak...</td>\n",
       "      <td>99</td>\n",
       "      <td>[-0.080960214138031, 0.012261789292097092, 0.0...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Plane</td>\n",
       "      <td>R</td>\n",
       "      <td>Action, Thriller</td>\n",
       "      <td>6.5</td>\n",
       "      <td>A pilot finds himself caught in a war zone aft...</td>\n",
       "      <td>Jean-François Richet</td>\n",
       "      <td>Gerard Butler, \\nMike Colter, \\nTony Goldwyn, ...</td>\n",
       "      <td>Title: Plane. Overview: A pilot finds himself ...</td>\n",
       "      <td>67</td>\n",
       "      <td>[0.02219153568148613, -0.0190700925886631, -0....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Everything Everywhere All at Once</td>\n",
       "      <td>R</td>\n",
       "      <td>Action, Adventure, Comedy</td>\n",
       "      <td>8.0</td>\n",
       "      <td>A middle-aged Chinese immigrant is swept up in...</td>\n",
       "      <td>Dan Kwan, \\nDaniel Scheinert</td>\n",
       "      <td>Michelle Yeoh, \\nStephanie Hsu, \\nJamie Lee Cu...</td>\n",
       "      <td>Title: Everything Everywhere All at Once. Over...</td>\n",
       "      <td>90</td>\n",
       "      <td>[0.038551680743694305, -0.023787647485733032, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Ant-Man and the Wasp: Quantumania</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>Action, Adventure, Comedy</td>\n",
       "      <td>6.6</td>\n",
       "      <td>Scott Lang and Hope Van Dyne, along with Hank ...</td>\n",
       "      <td>Peyton Reed</td>\n",
       "      <td>Paul Rudd, \\nEvangeline Lilly, \\nJonathan Majo...</td>\n",
       "      <td>Title: Ant-Man and the Wasp: Quantumania. Over...</td>\n",
       "      <td>100</td>\n",
       "      <td>[-0.07330965995788574, -0.046703167259693146, ...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>\n",
       "    <div class=\"colab-df-buttons\">\n",
       "\n",
       "  <div class=\"colab-df-container\">\n",
       "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-7be4fc18-c12d-470b-b3d2-b63ec044bee5')\"\n",
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       "\n",
       "  <style>\n",
       "    .colab-df-container {\n",
       "      display:flex;\n",
       "      gap: 12px;\n",
       "    }\n",
       "\n",
       "    .colab-df-convert {\n",
       "      background-color: #E8F0FE;\n",
       "      border: none;\n",
       "      border-radius: 50%;\n",
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       "      height: 32px;\n",
       "      padding: 0 0 0 0;\n",
       "      width: 32px;\n",
       "    }\n",
       "\n",
       "    .colab-df-convert:hover {\n",
       "      background-color: #E2EBFA;\n",
       "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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       "    }\n",
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       "    .colab-df-buttons div {\n",
       "      margin-bottom: 4px;\n",
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       "\n",
       "    [theme=dark] .colab-df-convert {\n",
       "      background-color: #3B4455;\n",
       "      fill: #D2E3FC;\n",
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       "\n",
       "    [theme=dark] .colab-df-convert:hover {\n",
       "      background-color: #434B5C;\n",
       "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
       "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
       "      fill: #FFFFFF;\n",
       "    }\n",
       "  </style>\n",
       "\n",
       "    <script>\n",
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       "        document.querySelector('#df-7be4fc18-c12d-470b-b3d2-b63ec044bee5 button.colab-df-convert');\n",
       "      buttonEl.style.display =\n",
       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
       "\n",
       "      async function convertToInteractive(key) {\n",
       "        const element = document.querySelector('#df-7be4fc18-c12d-470b-b3d2-b63ec044bee5');\n",
       "        const dataTable =\n",
       "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
       "                                                    [key], {});\n",
       "        if (!dataTable) return;\n",
       "\n",
       "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
       "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
       "          + ' to learn more about interactive tables.';\n",
       "        element.innerHTML = '';\n",
       "        dataTable['output_type'] = 'display_data';\n",
       "        await google.colab.output.renderOutput(dataTable, element);\n",
       "        const docLink = document.createElement('div');\n",
       "        docLink.innerHTML = docLinkHtml;\n",
       "        element.appendChild(docLink);\n",
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       "            title=\"Suggest charts\"\n",
       "            style=\"display:none;\">\n",
       "\n",
       "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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       "    </g>\n",
       "</svg>\n",
       "  </button>\n",
       "\n",
       "<style>\n",
       "  .colab-df-quickchart {\n",
       "      --bg-color: #E8F0FE;\n",
       "      --fill-color: #1967D2;\n",
       "      --hover-bg-color: #E2EBFA;\n",
       "      --hover-fill-color: #174EA6;\n",
       "      --disabled-fill-color: #AAA;\n",
       "      --disabled-bg-color: #DDD;\n",
       "  }\n",
       "\n",
       "  [theme=dark] .colab-df-quickchart {\n",
       "      --bg-color: #3B4455;\n",
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       "      --hover-bg-color: #434B5C;\n",
       "      --hover-fill-color: #FFFFFF;\n",
       "      --disabled-bg-color: #3B4455;\n",
       "      --disabled-fill-color: #666;\n",
       "  }\n",
       "\n",
       "  .colab-df-quickchart {\n",
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       "    fill: var(--fill-color);\n",
       "    height: 32px;\n",
       "    padding: 0;\n",
       "    width: 32px;\n",
       "  }\n",
       "\n",
       "  .colab-df-quickchart:hover {\n",
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       "    fill: var(--button-hover-fill-color);\n",
       "  }\n",
       "\n",
       "  .colab-df-quickchart-complete:disabled,\n",
       "  .colab-df-quickchart-complete:disabled:hover {\n",
       "    background-color: var(--disabled-bg-color);\n",
       "    fill: var(--disabled-fill-color);\n",
       "    box-shadow: none;\n",
       "  }\n",
       "\n",
       "  .colab-df-spinner {\n",
       "    border: 2px solid var(--fill-color);\n",
       "    border-color: transparent;\n",
       "    border-bottom-color: var(--fill-color);\n",
       "    animation:\n",
       "      spin 1s steps(1) infinite;\n",
       "  }\n",
       "\n",
       "  @keyframes spin {\n",
       "    0% {\n",
       "      border-color: transparent;\n",
       "      border-bottom-color: var(--fill-color);\n",
       "      border-left-color: var(--fill-color);\n",
       "    }\n",
       "    20% {\n",
       "      border-color: transparent;\n",
       "      border-left-color: var(--fill-color);\n",
       "      border-top-color: var(--fill-color);\n",
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       "      border-top-color: var(--fill-color);\n",
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       "    60% {\n",
       "      border-color: transparent;\n",
       "      border-right-color: var(--fill-color);\n",
       "    }\n",
       "    80% {\n",
       "      border-color: transparent;\n",
       "      border-right-color: var(--fill-color);\n",
       "      border-bottom-color: var(--fill-color);\n",
       "    }\n",
       "    90% {\n",
       "      border-color: transparent;\n",
       "      border-bottom-color: var(--fill-color);\n",
       "    }\n",
       "  }\n",
       "</style>\n",
       "\n",
       "  <script>\n",
       "    async function quickchart(key) {\n",
       "      const quickchartButtonEl =\n",
       "        document.querySelector('#' + key + ' button');\n",
       "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
       "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
       "      try {\n",
       "        const charts = await google.colab.kernel.invokeFunction(\n",
       "            'suggestCharts', [key], {});\n",
       "      } catch (error) {\n",
       "        console.error('Error during call to suggestCharts:', error);\n",
       "      }\n",
       "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
       "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
       "    }\n",
       "    (() => {\n",
       "      let quickchartButtonEl =\n",
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       "      quickchartButtonEl.style.display =\n",
       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
       "    })();\n",
       "  </script>\n",
       "</div>\n",
       "\n",
       "    </div>\n",
       "  </div>\n"
      ],
      "text/plain": [
       "                          movie_name certificate                       genre  \\\n",
       "0     Black Panther: Wakanda Forever       PG-13    Action, Adventure, Drama   \n",
       "1           Avatar: The Way of Water       PG-13  Action, Adventure, Fantasy   \n",
       "2                              Plane           R            Action, Thriller   \n",
       "3  Everything Everywhere All at Once           R   Action, Adventure, Comedy   \n",
       "5  Ant-Man and the Wasp: Quantumania       PG-13   Action, Adventure, Comedy   \n",
       "\n",
       "   rating                                        description  \\\n",
       "0     6.9  The people of Wakanda fight to protect their h...   \n",
       "1     7.8  Jake Sully lives with his newfound family form...   \n",
       "2     6.5  A pilot finds himself caught in a war zone aft...   \n",
       "3     8.0  A middle-aged Chinese immigrant is swept up in...   \n",
       "5     6.6  Scott Lang and Hope Van Dyne, along with Hank ...   \n",
       "\n",
       "                       director  \\\n",
       "0                  Ryan Coogler   \n",
       "1                 James Cameron   \n",
       "2          Jean-François Richet   \n",
       "3  Dan Kwan, \\nDaniel Scheinert   \n",
       "5                   Peyton Reed   \n",
       "\n",
       "                                                star  \\\n",
       "0  Letitia Wright, \\nLupita Nyong'o, \\nDanai Guri...   \n",
       "1  Sam Worthington, \\nZoe Saldana, \\nSigourney We...   \n",
       "2  Gerard Butler, \\nMike Colter, \\nTony Goldwyn, ...   \n",
       "3  Michelle Yeoh, \\nStephanie Hsu, \\nJamie Lee Cu...   \n",
       "5  Paul Rudd, \\nEvangeline Lilly, \\nJonathan Majo...   \n",
       "\n",
       "                                       combined_info  n_tokens  \\\n",
       "0  Title: Black Panther: Wakanda Forever. Overvie...        80   \n",
       "1  Title: Avatar: The Way of Water. Overview: Jak...        99   \n",
       "2  Title: Plane. Overview: A pilot finds himself ...        67   \n",
       "3  Title: Everything Everywhere All at Once. Over...        90   \n",
       "5  Title: Ant-Man and the Wasp: Quantumania. Over...       100   \n",
       "\n",
       "                                              vector  \n",
       "0  [-0.026855934411287308, 0.05683119595050812, -...  \n",
       "1  [-0.080960214138031, 0.012261789292097092, 0.0...  \n",
       "2  [0.02219153568148613, -0.0190700925886631, -0....  \n",
       "3  [0.038551680743694305, -0.023787647485733032, ...  \n",
       "5  [-0.07330965995788574, -0.046703167259693146, ...  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#View Dataframe after creating Embeddings\n",
    "imdb.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "mkmy3X0cAhPt",
    "outputId": "d5c79f82-e201-44e7-af7b-5502e011f786"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Embedding Dimensions: 384\n"
     ]
    }
   ],
   "source": [
    "# Get dimensions of Embeddings\n",
    "embedding_dimensions = len(imdb['vector'].iloc[0])\n",
    "print(f\"Embedding Dimensions: {embedding_dimensions}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "xNK4u9_4AiJx"
   },
   "outputs": [],
   "source": [
    "# Save preprocessed data\n",
    "imdb.to_pickle('imdb.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "I_ny8MU8Ezw5",
    "outputId": "ccf5d736-a9a0-4223-915f-bccc1a22dd80"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Colab Notebooks', 'english-handwritten-characters-dataset', 'Sleepy.ai Project Proposal.gdoc', 'Untitled document (2).gdoc', '21K-4839 IS (SEED) Lab 1.zip', 'FYP_I_Proposal_Update_1.gdoc', 'FYP_I_Proposal_Update_1 (1).gdoc', 'Untitled document (1).gdoc', 'Final Year Project Proposal (Smart Sub_ Intelligent Football Substitution Planning).gdoc', 'Final Year Project Proposal (Smart Sub_ Intelligent Football Substitution Recommender System) (1) (1) (1).gdoc', 'Final Year Project Proposal (Smart Sub_ Intelligent Football Substitution Recommender System) (1) (1).gdoc', 'Final Year Project Proposal (Smart Sub: Intelligent Football Substitution Recommender System).gdoc', 'CV (Fahad Yousuf).gdoc', 'FYP WORKFLOW.gdoc', 'football-dataset', 'deedy-cv (1).gdoc', 'Untitled document.gdoc', 'deedy-cv.gdoc', 'Fahad Yousuf (Curriculum Vitae).gdoc', 'Fahad Yousuf (Curriculum Vitae) (1).pdf', 'Fahad Yousuf (Curriculum Vitae).pdf', '(Fahad Yousuf) Role of Civil Engagement in Bringing Social Change.gdoc', '(Fahad Yousuf) Benefits of Attending the AIPS Workshop .gdoc', 'FYP_Project.zip', 'IMDB_Dataset.zip', 'imdb.pkl']\n"
     ]
    }
   ],
   "source": [
    "# Save Pickle File to Drive\n",
    "!cp /content/imdb.pkl /content/drive/MyDrive/imdb.pkl\n",
    "print(os.listdir('/content/drive/MyDrive'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "YGnOYHONAkyX"
   },
   "outputs": [],
   "source": [
    "# Set the API key as an environment variable\n",
    "os.environ[\"PINECONE_API_KEY\"] = \"\"\n",
    "\n",
    "# Initialize Pinecone client\n",
    "pc = Pinecone(api_key=os.environ[\"PINECONE_API_KEY\"])\n",
    "\n",
    "# Create or connect to a Pinecone index\n",
    "index_name = \"imdb-index\"\n",
    "\n",
    "if index_name not in pc.list_indexes():\n",
    "    pc.create_index(\n",
    "        name=index_name,\n",
    "        dimension=embedding_dimensions,\n",
    "        metric=\"cosine\",\n",
    "        spec=ServerlessSpec(\n",
    "            cloud=\"aws\",\n",
    "            region=\"us-east-1\"\n",
    "        )\n",
    "    )\n",
    "else:\n",
    "    print(f\"Index '{index_name}' already exists.\")\n",
    "\n",
    "# Prepare documents\n",
    "documents = [\n",
    "    Document(\n",
    "        page_content=row['combined_info'],\n",
    "        metadata={\n",
    "            'title': row['movie_name'],\n",
    "        }\n",
    "    ) for _, row in imdb.iterrows()\n",
    "]\n",
    "\n",
    "# Create vector store with Pinecone\n",
    "docsearch = PineconeVectorStore.from_documents(\n",
    "    documents=documents,\n",
    "    embedding=embeddings,\n",
    "    index_name=index_name\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "sFMDGQ-pBtbO"
   },
   "outputs": [],
   "source": [
    "# Define LLM using Groq (Llama model)\n",
    "llm = ChatGroq(\n",
    "    model_name=\"llama3-8b-8192\",  # or another Llama model available\n",
    "    api_key=\"\",\n",
    "    temperature=0\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "lq_I3GlfBvbB"
   },
   "outputs": [],
   "source": [
    "# Define custom prompt template\n",
    "template = \"\"\"You are a movie recommender system that helps users find movie that match their preferences.\n",
    "Use the following pieces of context to answer the question at the end.\n",
    "For each question, suggest three movies, with a short description of the plot and the reason why the user might like it.\n",
    "If you don't know the answer, just say that you don't know, don't try to make up an answer.\n",
    "\n",
    "{context}\n",
    "\n",
    "Question: {question}\n",
    "Your response:\"\"\"\n",
    "\n",
    "PROMPT = PromptTemplate(\n",
    "    template=template, input_variables=[\"context\", \"question\"]\n",
    ")\n",
    "\n",
    "def retrieve_ranked_context(query):\n",
    "    results = docsearch.similarity_search(query, k=100)  # Retrieve top 10 matches\n",
    "    # Sort by rating (descending) before creating the context\n",
    "    ranked_results = sorted(\n",
    "        results,\n",
    "        key=lambda x: float(x.metadata.get(\"rating\", 0)),  # Sort by rating\n",
    "        reverse=True\n",
    "    )\n",
    "    print(ranked_results)\n",
    "    context = \"\\n\".join([doc.page_content for doc in ranked_results[:3]])  # Top 3\n",
    "    return context\n",
    "\n",
    "# Create QA chain\n",
    "qa_chain = RetrievalQA.from_chain_type(\n",
    "    llm=llm,\n",
    "    chain_type=\"stuff\",\n",
    "    retriever=docsearch.as_retriever(),\n",
    "    return_source_documents=True,\n",
    "    chain_type_kwargs={\"prompt\": PROMPT}\n",
    ")\n",
    "\n",
    "def get_movie_recommendations(query):\n",
    "    # Suppress any print outputs during the execution\n",
    "    with io.StringIO() as buf, redirect_stdout(buf):\n",
    "        context = retrieve_ranked_context(query)\n",
    "        qa_input = {\"context\": context, \"query\": query}\n",
    "        result = qa_chain(qa_input)\n",
    "\n",
    "    # Return the final result without any intermediate prints\n",
    "    return result['result']\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "FfuEBzBZEUWa",
    "outputId": "a9f7745b-098f-4923-cb17-0cff61e0afff"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "What's Your Query?\n",
      "Recommend me some good movies using the dataset I provided to you\n",
      "Based on the dataset you provided, I'll recommend three movies that match your preferences. Since I don't have any specific information about your preferences, I'll try to suggest movies that belong to a mix of genres (comedy, crime, action, sci-fi, thriller, and drama).\n",
      "\n",
      "Here are three movie recommendations:\n",
      "\n",
      "1. **District 9**: This sci-fi thriller won critical acclaim and explores themes of segregation, humanity, and action. The movie's unique blend of action, mystery, and social commentary might appeal to viewers looking for a thought-provoking film.\n",
      "2. **One Way**: This unrated action-comedy seems to have a mix of fast-paced action and humor, which could be an appealing combination for fans of the genres. The movie's production values and performances might also be worth checking out.\n",
      "3. **America America**: This crime-drama from India might offer a gripping story with complex characters, morality, and action. The movie's themes of identity, loyalty, and betrayal could resonate with viewers interested in character-driven stories.\n",
      "\n",
      "These movies might not be exactly what you're looking for, but they seem to have some common elements across the genres and themes represented in the dataset. I hope you find something you enjoy!\n"
     ]
    }
   ],
   "source": [
    "# Example usage\n",
    "if __name__ == \"__main__\":\n",
    "    query = input(\"What's Your Query?\\n\")\n",
    "    recommendations = get_movie_recommendations(query)\n",
    "    print(recommendations)"
   ]
  }
 ],
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