00_exploration.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Semantic Search using the best tools available"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We are going to use the best tools available to perform semantic search on the dataset. We will use the following tools:\n",
    "- OpenAI Embedding models\n",
    "- MongoDb Vectore Database funtionality\n",
    "- Spacy for some data preprpocessing\n",
    "- Monggregate as a query builder\n",
    "- Good old Pandas for data manipulation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import spacy\n",
    "from langdetect import detect\n",
    "from langdetect.lang_detect_exception import LangDetectException\n",
    "\n",
    "from openai import OpenAI\n",
    "from dotenv import load_dotenv\n",
    "\n",
    "from pymongo import MongoClient\n",
    "from monggregate import Pipeline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Loading Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>artist</th>\n",
       "      <th>song</th>\n",
       "      <th>link</th>\n",
       "      <th>text</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ABBA</td>\n",
       "      <td>Ahe's My Kind Of Girl</td>\n",
       "      <td>/a/abba/ahes+my+kind+of+girl_20598417.html</td>\n",
       "      <td>Look at her face, it's a wonderful face  \\nAnd...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ABBA</td>\n",
       "      <td>Andante, Andante</td>\n",
       "      <td>/a/abba/andante+andante_20002708.html</td>\n",
       "      <td>Take it easy with me, please  \\nTouch me gentl...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ABBA</td>\n",
       "      <td>As Good As New</td>\n",
       "      <td>/a/abba/as+good+as+new_20003033.html</td>\n",
       "      <td>I'll never know why I had to go  \\nWhy I had t...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ABBA</td>\n",
       "      <td>Bang</td>\n",
       "      <td>/a/abba/bang_20598415.html</td>\n",
       "      <td>Making somebody happy is a question of give an...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ABBA</td>\n",
       "      <td>Bang-A-Boomerang</td>\n",
       "      <td>/a/abba/bang+a+boomerang_20002668.html</td>\n",
       "      <td>Making somebody happy is a question of give an...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  artist                   song                                        link  \\\n",
       "0   ABBA  Ahe's My Kind Of Girl  /a/abba/ahes+my+kind+of+girl_20598417.html   \n",
       "1   ABBA       Andante, Andante       /a/abba/andante+andante_20002708.html   \n",
       "2   ABBA         As Good As New        /a/abba/as+good+as+new_20003033.html   \n",
       "3   ABBA                   Bang                  /a/abba/bang_20598415.html   \n",
       "4   ABBA       Bang-A-Boomerang      /a/abba/bang+a+boomerang_20002668.html   \n",
       "\n",
       "                                                text  \n",
       "0  Look at her face, it's a wonderful face  \\nAnd...  \n",
       "1  Take it easy with me, please  \\nTouch me gentl...  \n",
       "2  I'll never know why I had to go  \\nWhy I had t...  \n",
       "3  Making somebody happy is a question of give an...  \n",
       "4  Making somebody happy is a question of give an...  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"data/57k_spotify_songs.csv\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exploration"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Basics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(57650, 4)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>artist</th>\n",
       "      <th>song</th>\n",
       "      <th>link</th>\n",
       "      <th>text</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>57650</td>\n",
       "      <td>57650</td>\n",
       "      <td>57650</td>\n",
       "      <td>57650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>643</td>\n",
       "      <td>44824</td>\n",
       "      <td>57650</td>\n",
       "      <td>57494</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>Donna Summer</td>\n",
       "      <td>Have Yourself A Merry Little Christmas</td>\n",
       "      <td>/a/abba/ahes+my+kind+of+girl_20598417.html</td>\n",
       "      <td>I just came back from a lovely trip along the ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>191</td>\n",
       "      <td>35</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              artist                                    song  \\\n",
       "count          57650                                   57650   \n",
       "unique           643                                   44824   \n",
       "top     Donna Summer  Have Yourself A Merry Little Christmas   \n",
       "freq             191                                      35   \n",
       "\n",
       "                                              link  \\\n",
       "count                                        57650   \n",
       "unique                                       57650   \n",
       "top     /a/abba/ahes+my+kind+of+girl_20598417.html   \n",
       "freq                                             1   \n",
       "\n",
       "                                                     text  \n",
       "count                                               57650  \n",
       "unique                                              57494  \n",
       "top     I just came back from a lovely trip along the ...  \n",
       "freq                                                    6  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe(include=\"all\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Observations**:\n",
    "\n",
    "* No missing data\n",
    "* Each row represent a song\n",
    "* 4 columns\n",
    "   * artist : artist name\n",
    "   * song : song title\n",
    "   * link : link to ???. I don't understand those links and I won't use them anyway\n",
    "   * text : the lyrics of the song\n",
    "* There are 57650 songs coming from \"only\" 643 artists. (Assuming there are no typos in the artist names)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Domain specific exploration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8368     [Verse:]  \\nWhatever it takes, whatever Your w...\n",
       "26601    Well she drew out all her money from the south...\n",
       "34690    Introducing..Tre' Cool..  \\nHi!..um..I wrote t...\n",
       "1277     Where are you ? I love you . Where are you ? I...\n",
       "22875    Funny how everything changes for me  \\nMemorie...\n",
       "                               ...                        \n",
       "4181     Tak tertahan Berdiam diri... sakit  \\nSementar...\n",
       "18723    Get down deeper and down  \\nDown down deeper a...\n",
       "10157    You're such a poet  \\nI wish I could be Wesley...\n",
       "16484    [Jessica Rivera]  \\n\"Hmmm, so you're the one t...\n",
       "40079    Baby when I met you there was peace unknown  \\...\n",
       "Name: text, Length: 100, dtype: object"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"text\"].sample(100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['ABBA', 'Ace Of Base', 'Adam Sandler', 'Adele', 'Aerosmith',\n",
       "       'Air Supply', 'Aiza Seguerra', 'Alabama', 'Alan Parsons Project',\n",
       "       'Aled Jones', 'Alice Cooper', 'Alice In Chains', 'Alison Krauss',\n",
       "       'Allman Brothers Band', 'Alphaville', 'America', 'Amy Grant',\n",
       "       'Andrea Bocelli', 'Andy Williams', 'Annie', 'Ariana Grande',\n",
       "       'Ariel Rivera', 'Arlo Guthrie', 'Arrogant Worms', 'Avril Lavigne',\n",
       "       'Backstreet Boys', 'Barbie', 'Barbra Streisand', 'Beach Boys',\n",
       "       'The Beatles', 'Beautiful South', 'Beauty And The Beast',\n",
       "       'Bee Gees', 'Bette Midler', 'Bill Withers', 'Billie Holiday',\n",
       "       'Billy Joel', 'Bing Crosby', 'Black Sabbath', 'Blur', 'Bob Dylan',\n",
       "       'Bob Marley', 'Bob Rivers', 'Bob Seger', 'Bon Jovi', 'Boney M.',\n",
       "       'Bonnie Raitt', 'Bosson', 'Bread', 'Britney Spears',\n",
       "       'Bruce Springsteen', 'Bruno Mars', 'Bryan White', 'Cake',\n",
       "       'Carly Simon', 'Carol Banawa', 'Carpenters', 'Cat Stevens',\n",
       "       'Celine Dion', 'Chaka Khan', 'Cheap Trick', 'Cher', 'Chicago',\n",
       "       'Children', 'Chris Brown', 'Chris Rea', 'Christina Aguilera',\n",
       "       'Christina Perri', 'Christmas Songs', 'Christy Moore',\n",
       "       'Chuck Berry', 'Cinderella', 'Clash', 'Cliff Richard', 'Coldplay',\n",
       "       'Cole Porter', 'Conway Twitty', 'Counting Crows',\n",
       "       'Creedence Clearwater Revival', 'Crowded House', 'Culture Club',\n",
       "       'Cyndi Lauper', 'Dan Fogelberg', 'Dave Matthews Band',\n",
       "       'David Allan Coe', 'David Bowie', 'David Guetta', 'David Pomeranz',\n",
       "       'Dean Martin', 'Death', 'Deep Purple', 'Def Leppard',\n",
       "       'Demi Lovato', 'Depeche Mode', 'Devo', 'Dewa 19', 'Diana Ross',\n",
       "       'Dire Straits', 'Divine', 'Dolly Parton', 'Don Henley',\n",
       "       'Don McLean', 'Don Moen', 'Donna Summer', 'Doobie Brothers',\n",
       "       'Doors', 'Doris Day', 'Drake', 'Dream Theater',\n",
       "       'Dusty Springfield', 'Eagles', 'Ed Sheeran', 'Eddie Cochran',\n",
       "       'Electric Light Orchestra', 'Ella Fitzgerald', 'Ellie Goulding',\n",
       "       'Elton John', 'Elvis Costello', 'Elvis Presley', 'Eminem',\n",
       "       'Emmylou Harris', 'Engelbert Humperdinck', 'Enigma',\n",
       "       'Enrique Iglesias', 'Enya', 'Eppu Normaali', 'Erasure',\n",
       "       'Eric Clapton', 'Erik Santos', 'Etta James', 'Europe',\n",
       "       'Eurythmics', 'Evanescence', 'Everclear', 'Everlast', 'Exo',\n",
       "       'Exo-K', 'Extreme', 'Fabolous', 'Face To Face', 'Faces',\n",
       "       'Faith Hill', 'Faith No More', 'Falco', 'Fall Out Boy', 'Fastball',\n",
       "       'Fatboy Slim', 'Fifth Harmony', 'Fiona Apple', 'Fleetwood Mac',\n",
       "       'Flo-Rida', 'Foo Fighters', 'Foreigner', 'Frank Sinatra',\n",
       "       'Frank Zappa', 'Frankie Goes To Hollywood', 'Frankie Laine',\n",
       "       'Frankie Valli', 'Freddie Aguilar', 'Freddie King', 'Free',\n",
       "       'Freestyle', 'Fun.', 'Garth Brooks', 'Gary Numan',\n",
       "       'Gary Valenciano', 'Genesis', 'George Formby', 'George Harrison',\n",
       "       'George Jones', 'George Michael', 'George Strait', 'Gino Vannelli',\n",
       "       'Gipsy Kings', 'Glee', 'Glen Campbell', 'Gloria Estefan',\n",
       "       'Gloria Gaynor', 'GMB', 'Gordon Lightfoot', 'Grand Funk Railroad',\n",
       "       'Grateful Dead', 'Grease', 'Great Big Sea', 'Green Day',\n",
       "       'Gucci Mane', 'Guided By Voices', \"Guns N' Roses\", 'Halloween',\n",
       "       'Hank Snow', 'Hank Williams', 'Hank Williams Jr.', 'Hanson',\n",
       "       'Happy Mondays', 'Harry Belafonte', 'Harry Connick, Jr.', 'Heart',\n",
       "       'Helloween', 'High School Musical', 'Hillsong', 'Hillsong United',\n",
       "       'HIM', 'Hollies', 'Hooverphonic', 'Horrible Histories',\n",
       "       'Housemartins', 'Howard Jones', 'Human League', 'Ian Hunter',\n",
       "       'Ice Cube', 'Idina Menzel', 'Iggy Pop', 'Il Divo',\n",
       "       'Imagine Dragons', 'Imago', 'Imperials', 'Incognito', 'Incubus',\n",
       "       'Independence Day', 'Indiana Bible College', 'Indigo Girls',\n",
       "       'Ingrid Michaelson', 'Inna', 'Insane Clown Posse', 'Inside Out',\n",
       "       'INXS', 'Iron Butterfly', 'Iron Maiden', 'Irving Berlin',\n",
       "       'Isley Brothers', 'Israel', 'Israel Houghton', 'Iwan Fals',\n",
       "       'J Cole', 'Jackson Browne', 'The Jam', 'James Taylor',\n",
       "       'Janis Joplin', 'Jason Mraz', 'Jennifer Lopez', 'Jim Croce',\n",
       "       'Jimi Hendrix', 'Jimmy Buffett', 'John Denver', 'John Legend',\n",
       "       'John Martyn', 'John McDermott', 'John Mellencamp', 'John Prine',\n",
       "       'John Waite', 'Johnny Cash', 'Joni Mitchell', 'Jose Mari Chan',\n",
       "       'Josh Groban', 'Journey', 'Joy Division', 'Judas Priest', 'Judds',\n",
       "       'Judy Garland', 'Justin Bieber', 'Justin Timberlake', 'Kanye West',\n",
       "       'Kari Jobe', 'Kate Bush', 'Katy Perry', 'Keith Green',\n",
       "       'Keith Urban', 'Kelly Clarkson', 'Kelly Family', 'Kenny Chesney',\n",
       "       'Kenny Loggins', 'Kenny Rogers', 'Kid Rock', 'The Killers',\n",
       "       'Kim Wilde', 'King Crimson', 'King Diamond', 'Kinks',\n",
       "       'Kirk Franklin', 'Kirsty Maccoll', 'Kiss', 'Koes Plus', 'Korn',\n",
       "       'Kris Kristofferson', 'Kyla', 'Kylie Minogue', 'Lady Gaga',\n",
       "       'Lana Del Rey', 'Lata Mangeshkar', 'Lauryn Hill', 'Lea Salonga',\n",
       "       'Leann Rimes', 'Lenny Kravitz', 'Leo Sayer', 'Leonard Cohen',\n",
       "       'Les Miserables', 'Lil Wayne', 'Linda Ronstadt', 'Linkin Park',\n",
       "       'Lionel Richie', 'Little Mix', 'Little Walter', 'LL Cool J',\n",
       "       'Lloyd Cole', 'Lorde', 'Loretta Lynn', 'Lou Reed',\n",
       "       'Louis Armstrong', 'Louis Jordan', 'Lucky Dube', 'Luther Vandross',\n",
       "       'Lynyrd Skynyrd', 'Madonna', 'Manowar', 'Mariah Carey',\n",
       "       'Marianne Faithfull', 'Marillion', 'Marilyn Manson', 'Mark Ronson',\n",
       "       'Maroon 5', 'Mary Black', 'Matt Monro', 'Matt Redman',\n",
       "       'Mazzy Star', 'Mc Hammer', 'Meat Loaf', 'Megadeth', 'Men At Work',\n",
       "       'Metallica', 'Michael Bolton', 'Michael Buble', 'Michael Jackson',\n",
       "       'Michael W. Smith', 'Migos', 'Miley Cyrus', 'Misfits',\n",
       "       'Modern Talking', 'The Monkees', 'Moody Blues', 'Morrissey', 'Mud',\n",
       "       \"'n Sync\", 'Nat King Cole', 'Natalie Cole', 'Natalie Grant',\n",
       "       'Natalie Imbruglia', 'Nazareth', 'Ne-Yo', 'Neil Diamond',\n",
       "       'Neil Sedaka', 'Neil Young', 'New Order', 'Next To Normal',\n",
       "       'Nick Cave', 'Nick Drake', 'Nickelback', 'Nicki Minaj',\n",
       "       'Nightwish', 'Nina Simone', 'Nine Inch Nails', 'Nirvana',\n",
       "       'Nitty Gritty Dirt Band', 'Noa', 'NOFX', 'Norah Jones',\n",
       "       'Notorious B.I.G.', 'O-Zone', 'O.A.R.', 'Oasis',\n",
       "       'Ocean Colour Scene', 'Offspring', 'Ofra Haza', 'Oingo Boingo',\n",
       "       \"Old 97's\", 'Oliver', 'Olivia Newton-John', 'Olly Murs', 'Omd',\n",
       "       'One Direction', 'OneRepublic', 'Opeth', 'Orphaned Land',\n",
       "       'Oscar Hammerstein', 'Otis Redding', 'Our Lady Peace',\n",
       "       'Out Of Eden', 'Outkast', 'Overkill', 'Owl City', 'Ozzy Osbourne',\n",
       "       'Passenger', 'Pat Benatar', 'Patsy Cline', 'Patti Smith',\n",
       "       'Paul McCartney', 'Paul Simon', 'Pearl Jam', 'Perry Como',\n",
       "       'Pet Shop Boys', 'Peter Cetera', 'Peter Gabriel', 'Peter Tosh',\n",
       "       'Pharrell Williams', 'Phil Collins', 'Phineas And Ferb', 'Phish',\n",
       "       'Pink Floyd', 'Pitbull', 'Planetshakers', 'P!nk', 'Pogues',\n",
       "       'Point Of Grace', 'Poison', 'Pretenders', 'Primus', 'Prince',\n",
       "       'Proclaimers', 'Procol Harum', 'Puff Daddy', 'Q-Tip', 'Qntal',\n",
       "       'Quarashi', 'Quarterflash', 'Quasi', 'Queen', 'Queen Adreena',\n",
       "       'Queen Latifah', 'Queens Of The Stone Age', 'Queensryche',\n",
       "       'Quicksand', 'Quicksilver Messenger Service', 'Quiet Riot',\n",
       "       'Quietdrive', 'Quincy Jones', 'Quincy Punx', 'R. Kelly',\n",
       "       'Radiohead', 'Raffi', 'Rage Against The Machine', 'Rainbow',\n",
       "       'Rammstein', 'Ramones', 'Randy Travis', 'Rascal Flatts',\n",
       "       'Ray Boltz', 'Ray Charles', 'Reba Mcentire',\n",
       "       'Red Hot Chili Peppers', 'Regine Velasquez', 'Religious Music',\n",
       "       'Rem', 'Reo Speedwagon', 'Richard Marx', 'Rick Astley', 'Rihanna',\n",
       "       'Robbie Williams', 'Rod Stewart', 'Rolling Stones', 'Roxette',\n",
       "       'Roxy Music', 'Roy Orbison', 'Rush', 'Sam Smith', 'Santana',\n",
       "       'Savage Garden', 'Scorpions', 'Selah', 'Selena Gomez', 'Sia',\n",
       "       'Side A', 'Slayer', 'Smiths', 'Snoop Dogg', 'Soundgarden',\n",
       "       'Spandau Ballet', 'Squeeze', 'Starship', 'Status Quo',\n",
       "       'Steely Dan', 'Steve Miller Band', 'Stevie Ray Vaughan',\n",
       "       'Stevie Wonder', 'Sting', 'Stone Roses', 'Stone Temple Pilots',\n",
       "       'Styx', 'Sublime', 'Supertramp', 'System Of A Down',\n",
       "       'Talking Heads', 'Taylor Swift', 'Tears For Fears',\n",
       "       'The Temptations', 'Ten Years After', 'The Broadways',\n",
       "       'The Script', 'The Weeknd', 'Thin Lizzy', 'Tiffany', 'Tim Buckley',\n",
       "       'Tim McGraw', 'Tina Turner', 'Tom Jones', 'Tom Lehrer',\n",
       "       'Tom T. Hall', 'Tom Waits', 'Tool', 'Tori Amos', 'Toto',\n",
       "       'Townes Van Zandt', 'Tracy Chapman', 'Tragically Hip', 'Train',\n",
       "       'Travis', 'Twenty One Pilots', 'U. D. O.', 'U-Kiss', 'U2', 'UB40',\n",
       "       'Ufo', 'Ugly Kid Joe', \"Ultramagnetic Mc's\", 'Ultravox',\n",
       "       'Uncle Kracker', 'Uncle Tupelo', 'Underoath', 'Underworld',\n",
       "       'Unearth', 'Ungu', 'Unkle', 'Unknown', 'Unseen', 'Unwritten Law',\n",
       "       'Uriah Heep', 'Used', 'Usher', 'Utada Hikaru', 'Utopia',\n",
       "       'Van Halen', 'Van Morrison', 'Vanessa Williams', 'Vangelis',\n",
       "       'Vanilla Ice', 'Velvet Underground', 'Vengaboys', 'Venom',\n",
       "       'Vera Lynn', 'Vertical Horizon', 'Veruca Salt', 'Verve',\n",
       "       'Vince Gill', 'Violent Femmes', 'Virgin Steele', 'Vonda Shepard',\n",
       "       'Vybz Kartel', 'Walk The Moon', 'Wanda Jackson', 'Wang Chung',\n",
       "       'Warren Zevon', 'W.A.S.P.', 'Waterboys', 'Waylon Jennings', 'Ween',\n",
       "       'Weezer', 'Weird Al Yankovic', 'Westlife', 'Wet Wet Wet', 'Wham!',\n",
       "       'Whiskeytown', 'The White Stripes', 'Whitesnake',\n",
       "       'Whitney Houston', 'Who', 'Widespread Panic', 'Will Smith',\n",
       "       'Willie Nelson', 'Wilson Phillips', 'Wilson Pickett',\n",
       "       'Wishbone Ash', 'Within Temptation', 'Wiz Khalifa', 'Wu-Tang Clan',\n",
       "       'Wyclef Jean', 'X', 'X Japan', 'X-Raided', 'X-Ray Spex', 'X-Treme',\n",
       "       'Xandria', 'Xavier Naidoo', 'Xavier Rudd', 'Xentrix', 'Xiu Xiu',\n",
       "       'Xscape', 'XTC', 'Xzibit', 'Yazoo', 'Yeah Yeah Yeahs', 'Yelawolf',\n",
       "       'Yello', 'Yellowcard', 'Yeng Constantino', 'Yes', 'YG',\n",
       "       'Ying Yang Twins', 'Yngwie Malmsteen', 'Yo Gotti', 'Yo La Tengo',\n",
       "       'Yoko Ono', 'Yolanda Adams', 'Yonder Mountain String Band',\n",
       "       'You Am I', 'Young Buck', 'Young Dro', 'Young Jeezy',\n",
       "       'Youngbloodz', 'Youth Of Today', 'Yukmouth', 'Yung Joc',\n",
       "       'Yusuf Islam', 'Z-Ro', 'Zac Brown Band', 'Zakk Wylde', 'Zao',\n",
       "       'Zayn Malik', 'Zebra', 'Zebrahead', 'Zed', 'Zero 7', 'Zeromancer',\n",
       "       'Ziggy Marley', 'Zoe', 'Zoegirl', 'Zornik', 'Zox', 'Zucchero',\n",
       "       'Zwan', 'ZZ Top', 'Joseph And The Amazing Technicolor Dreamcoat',\n",
       "       'Soundtracks', 'Van Der Graaf Generator', 'Various Artists',\n",
       "       'Zazie'], dtype=object)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"artist\"].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Observations**:\n",
    "\n",
    "* Most of the songs seem to be in English\n",
    "* ==> let's verify this"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def robust_detect(text):\n",
    "    try:\n",
    "        return detect(text)\n",
    "    except LangDetectException:\n",
    "        return \"N/A\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    en\n",
       "1    en\n",
       "2    en\n",
       "3    en\n",
       "4    en\n",
       "Name: language, dtype: object"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"language\"] = df[\"text\"].apply(robust_detect)\n",
    "df[\"language\"].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As the above step is time consuming, let's save the results in a file to avoid doing it again."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv(\"data/57k_spotify_songs.csv\", index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "language\n",
       "en    57189\n",
       "tl      133\n",
       "id       93\n",
       "fr       38\n",
       "so       36\n",
       "it       34\n",
       "sw       24\n",
       "de       24\n",
       "es       18\n",
       "ca       13\n",
       "nl       10\n",
       "ro        8\n",
       "cy        8\n",
       "pt        6\n",
       "af        4\n",
       "et        3\n",
       "da        3\n",
       "hr        2\n",
       "no        1\n",
       "sv        1\n",
       "sq        1\n",
       "sl        1\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"language\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "99.20034692107545"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(df[df[\"language\"]==\"en\"].shape[0] / df.shape[0]) * 100"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "99.2 % of the songs are indeed in English."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Filtering Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "selected_artist = [\"David Bowie\", \"Drake\", \"Adele\", \"Vybz Kartel\", \"Lauryn Hill\", \"Gucci Mane\", \"Chris Brown\", \"Bob Marley\", \"Britney Spears\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(950, 5)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filtered_df = df[(df[\"artist\"].isin(selected_artist))|(df[\"language\"].isin([\"fr\", \"es\"]))]\n",
    "filtered_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Saving the results\n",
    "filtered_df.to_csv(\"data/cache/sample.csv\", index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Embedding"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cost Estimation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\viann\\AppData\\Local\\Temp\\ipykernel_16856\\1728482146.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  filtered_df[\"raw_size\"] = filtered_df[\"text\"].apply(len)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "19     1564\n",
       "133    1494\n",
       "134    1402\n",
       "135     990\n",
       "136    1025\n",
       "Name: raw_size, dtype: int64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filtered_df[\"raw_size\"] = filtered_df[\"text\"].apply(len)\n",
    "filtered_df[\"raw_size\"].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# NOTE: You need to first run spacy download en_core_web_sm in the terminal for the below line to work\n",
    "nlp = spacy.load('en_core_web_sm')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "def count_token(text):\n",
    "    try:\n",
    "        doc = nlp(text)\n",
    "        return len(doc)\n",
    "    except:\n",
    "        return np.nan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "openai_price_min = 0.00002\n",
    "openai_price_med = 0.00010\n",
    "openai_price_max = 0.00013"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\viann\\AppData\\Local\\Temp\\ipykernel_16856\\2096108662.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  filtered_df[\"token_counts\"] = filtered_df[\"text\"].apply(count_token)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "token_counts\n",
       "210    7\n",
       "246    7\n",
       "286    7\n",
       "268    6\n",
       "244    6\n",
       "      ..\n",
       "536    1\n",
       "403    1\n",
       "603    1\n",
       "245    1\n",
       "145    1\n",
       "Name: count, Length: 537, dtype: int64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filtered_df[\"token_counts\"] = filtered_df[\"text\"].apply(count_token)\n",
    "filtered_df[\"token_counts\"].value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\viann\\AppData\\Local\\Temp\\ipykernel_16856\\3460347049.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  filtered_df[\"price_max\"] = filtered_df[\"token_counts\"] * openai_price_max / 1000\n",
      "C:\\Users\\viann\\AppData\\Local\\Temp\\ipykernel_16856\\3460347049.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  filtered_df[\"price_med\"] = filtered_df[\"token_counts\"] * openai_price_med / 1000\n",
      "C:\\Users\\viann\\AppData\\Local\\Temp\\ipykernel_16856\\3460347049.py:3: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  filtered_df[\"price_min\"] = filtered_df[\"token_counts\"] * openai_price_min / 1000\n"
     ]
    }
   ],
   "source": [
    "filtered_df[\"price_max\"] = filtered_df[\"token_counts\"] * openai_price_max / 1000\n",
    "filtered_df[\"price_med\"] = filtered_df[\"token_counts\"] * openai_price_med / 1000\n",
    "filtered_df[\"price_min\"] = filtered_df[\"token_counts\"] * openai_price_min / 1000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.05262582"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filtered_df[\"price_max\"].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4537     1028\n",
       "4529     1026\n",
       "41293    1024\n",
       "34812    1017\n",
       "7284      979\n",
       "30515     977\n",
       "30467     976\n",
       "30507     949\n",
       "30452     943\n",
       "30478     943\n",
       "Name: token_counts, dtype: int64"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filtered_df[\"token_counts\"].sort_values(ascending=False).head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Embedding"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "keys = load_dotenv(\".env\")\n",
    "keys"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "openai_client = OpenAI(\n",
    "    api_key=os.environ[\"OPENAI_API_KEY\"],\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_name = \"text-embedding-3-large\"\n",
    "max_dimensions = 2048 \n",
    "# NOTE: text-embedding-3-large returns by default embeddings with 3072 dimensions, \n",
    "# however MongoDb vector search indexes can't handle more than 2048 dimensions\n",
    "# Cf : https://www.mongodb.com/community/forums/t/vector-search-dimensions-limited-to-2048/257718"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def _get_embedding(text:str, model:str=model_name):\n",
    "   text = text.replace(\"\\n\", \" \")\n",
    "   return openai_client.embeddings.create(input = [text], model=model, dimensions=max_dimensions).data[0]\n",
    "\n",
    "def get_embedding(text:str, model_name:str=model_name):\n",
    "    try:\n",
    "        return _get_embedding(text, model_name).embedding\n",
    "    except Exception as e:\n",
    "        print(e)\n",
    "        return np.nan"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Testing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'filtered_df' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[7], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m sample_text \u001b[38;5;241m=\u001b[39m \u001b[43mfiltered_df\u001b[49m\u001b[38;5;241m.\u001b[39mreset_index()\u001b[38;5;241m.\u001b[39mloc[\u001b[38;5;241m0\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtext\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n\u001b[0;32m      2\u001b[0m sample_text\n",
      "\u001b[1;31mNameError\u001b[0m: name 'filtered_df' is not defined"
     ]
    }
   ],
   "source": [
    "sample_text = filtered_df.reset_index().loc[0, \"text\"]\n",
    "sample_text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Embedding(embedding=[-0.021085655316710472, 0.007618457544595003, -0.010882432572543621, 0.006392108276486397, -0.0009174033766612411, 0.01473128143697977, 0.002773435553535819, 0.006920381914824247, -0.0038431892171502113, 0.011576734483242035, -0.053853701800107956, 0.04398253560066223, 0.01691984198987484, 0.05131798982620239, 0.018066950142383575, 0.02750040404498577, -0.03380949795246124, 0.013833216391503811, -0.02075359784066677, -0.0057242196053266525, 0.029326722025871277, 0.01752358302474022, -0.014414317905902863, 0.0012763462727889419, 0.0075392164289951324, 0.017900921404361725, 0.00042615627171471715, 0.02476847730576992, 0.006229852791875601, -0.033869873732328415, 0.000345264415955171, 0.020210230723023415, 0.01457279920578003, -0.013772842474281788, -0.03700932487845421, -0.010444720275700092, -0.007456202059984207, 0.01528974249958992, -0.006452482659369707, -0.01468600146472454, -0.02922106720507145, 0.006837367545813322, 0.00613174494355917, -0.0010565468110144138, -0.005109158810228109, 0.010565468110144138, -0.030534204095602036, 0.014074712991714478, -0.018142418935894966, -0.0084221875295043, 0.02416473627090454, -0.0025866529904305935, -0.011040914803743362, 0.0006377014797180891, 0.04860115423798561, 0.0028564499225467443, 0.05605735629796982, -0.12280093133449554, 0.010037194937467575, -0.010799418203532696, 0.00829389225691557, 0.007184518501162529, -0.002375343581661582, 0.006886421237140894, -0.05158967152237892, -0.03906204551458359, 0.04872190207242966, -0.050352003425359726, -0.004452590364962816, -0.011222036555409431, -0.015093525871634483, 0.009622123092412949, -0.013538893312215805, -0.006626057904213667, 0.01768961362540722, -0.02179505117237568, 0.0181273240596056, -0.017372649163007736, -0.019515929743647575, -0.0008499542018398643, 0.03679801523685455, -0.022232763469219208, -0.023123282939195633, 0.03546978533267975, -0.044556088745594025, -0.0026791009586304426, -0.03166621923446655, 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      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "_embedding = _get_embedding(sample_text)\n",
    "_embedding"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'embedding': [-0.021085655316710472,\n",
       "  0.007618457544595003,\n",
       "  -0.010882432572543621,\n",
       "  0.006392108276486397,\n",
       "  -0.0009174033766612411,\n",
       "  0.01473128143697977,\n",
       "  0.002773435553535819,\n",
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       "  -0.010656029917299747,\n",
       "  -0.027530591934919357,\n",
       "  0.024300577118992805,\n",
       "  0.011448439210653305,\n",
       "  -0.04313729703426361,\n",
       "  0.025070346891880035,\n",
       "  -0.02709287963807583,\n",
       "  0.007527896203100681,\n",
       "  0.006807180121541023,\n",
       "  0.004931809846311808,\n",
       "  0.01178049761801958,\n",
       "  0.011146568693220615,\n",
       "  -0.006354374345391989,\n",
       "  -0.0011744650546461344,\n",
       "  -0.013342677615582943,\n",
       "  0.018142418935894966,\n",
       "  0.0060109966434538364,\n",
       "  0.011584280990064144,\n",
       "  0.020693223923444748,\n",
       "  0.0005211983225308359,\n",
       "  -0.015953857451677322,\n",
       "  0.0057279933243989944,\n",
       "  0.026881569996476173,\n",
       "  0.015938764438033104,\n",
       "  -0.015772735700011253,\n",
       "  0.015561425127089024,\n",
       "  0.007026036269962788,\n",
       "  0.029085224494338036,\n",
       "  -0.02715325355529785,\n",
       "  0.007795806508511305,\n",
       "  -0.026443857699632645,\n",
       "  0.07081882655620575,\n",
       "  -0.029432376846671104,\n",
       "  -0.002841356210410595,\n",
       "  0.03341706842184067,\n",
       "  0.021327152848243713,\n",
       "  -0.007399601396173239,\n",
       "  -0.009569295682013035,\n",
       "  -0.022232763469219208,\n",
       "  0.016331195831298828,\n",
       "  -0.03408118337392807,\n",
       "  -0.026957036927342415,\n",
       "  -0.03519810363650322,\n",
       "  0.022655382752418518,\n",
       "  -0.020180044695734978,\n",
       "  0.014723734930157661,\n",
       "  0.03226995840668678,\n",
       "  0.003535658586770296,\n",
       "  0.0005584604805335402,\n",
       "  -0.01649722456932068,\n",
       "  0.002171581145375967,\n",
       "  -0.005799687467515469,\n",
       "  -0.00028276778175495565,\n",
       "  -0.0014848256250843406,\n",
       "  -0.01563689298927784,\n",
       "  -0.018580131232738495,\n",
       "  -0.0017819794593378901,\n",
       "  -0.01439922396093607,\n",
       "  -0.0353490374982357,\n",
       "  0.03537922725081444,\n",
       "  0.013591720722615719,\n",
       "  -0.014293569140136242,\n",
       "  -0.012278583832085133,\n",
       "  0.005584604572504759,\n",
       "  0.012150288559496403,\n",
       "  -0.04153738543391228,\n",
       "  -0.00698075583204627,\n",
       "  0.010037194937467575,\n",
       "  0.03743194416165352,\n",
       "  0.012444612570106983,\n",
       "  -0.029070131480693817,\n",
       "  -0.024753382429480553,\n",
       "  0.0033318959176540375,\n",
       "  0.024210015311837196,\n",
       "  -0.02229313738644123,\n",
       "  -0.04368066415190697,\n",
       "  -0.022610101848840714,\n",
       "  -0.004475230351090431,\n",
       "  -0.012920058332383633,\n",
       "  -0.008641043677926064,\n",
       "  -0.009380626492202282,\n",
       "  0.01182577759027481,\n",
       "  0.00412430614233017,\n",
       "  -0.020466821268200874,\n",
       "  0.016270821914076805,\n",
       "  ...],\n",
       " 'index': 0,\n",
       " 'object': 'embedding'}"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "_embedding.dict()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2048"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(_embedding.embedding)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\viann\\AppData\\Local\\Temp\\ipykernel_16856\\2174229127.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  filtered_df[\"embedding\"] = filtered_df[\"text\"].apply(get_embedding)\n"
     ]
    }
   ],
   "source": [
    "filtered_df[\"embedding\"] = filtered_df[\"text\"].apply(get_embedding)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "filtered_df.to_csv(\"data/cache/sample_with_lang_and_embedding.csv\", index=False) \n",
    "#filtered_df.to_json(\"data/cache/sample_with_lang_and_embedding.json\", orient=\"records\")     "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Vector Search"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "mongo_client = MongoClient(os.environ[\"MONGODB_URI\"])\n",
    "db = mongo_client[\"spofity\"]\n",
    "collection = db[\"songs\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['songs']"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "db.list_collection_names()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "index = \"lyrics_semantics\"\n",
    "def find_songs(text:str)->list[dict]:\n",
    "\n",
    "    pipeline = Pipeline()\n",
    "    pipeline.vector_search(\n",
    "        index=index,\n",
    "        path=\"embedding\",\n",
    "        query_vector=get_embedding(text),\n",
    "        limit=10,\n",
    "        num_candidates=100\n",
    "        ).project(projection={\"_id\": 0, \"text\": 1, \"artist\": 1, \"song\": 1})\n",
    "\n",
    "    return list(collection.aggregate(pipeline.export()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Testing some queries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'artist': 'Bob Marley',\n",
       "  'song': 'Get Up, Stand Up',\n",
       "  'text': \"Get up, stand up, stand up for your right  \\nGet up, stand up, stand up for your right  \\nGet up, stand up, stand up for your right  \\nGet up, stand up, don't give up the fight  \\n  \\nPreacher man don't tell me heaven is under the earth  \\nI know you don't know what life is really worth  \\nIs not all that glitters in gold and  \\nHalf the story has never been told  \\nSo now you see the light, aay  \\nStand up for your right. Come on  \\n  \\nGet up, stand up, stand up for your right  \\nGet up, stand up, don't give up the fight  \\n(Repeat)  \\n  \\nMost people think great God will come from the sky  \\nTake away ev'rything, and make ev'rybody feel high  \\nBut if you know what life is worth  \\nYou would look for yours on earth  \\nAnd now you see the light  \\nYou stand up for your right, yeah!  \\n  \\nGet up, stand up, stand up for your right  \\nGet up, stand up, don't give up the fight  \\nGet up, stand up. Life is your right  \\nSo we can't give up the fight  \\nStand up for your right, Lord, Lord  \\nGet up, stand up. Keep on struggling on  \\nDon't give up the fight  \\n  \\nWe're sick and tired of your ism and skism game  \\nDie and go to heaven in Jesus' name, Lord  \\nWe know when we understand  \\nAlmighty God is a living man  \\nYou can fool some people sometimes  \\nBut you can't fool all the people all the time  \\nSo now we see the light  \\nWe gonna stand up for our right  \\n  \\nSo you'd better get up, stand up, stand up for your right  \\nGet up, stand up, don't give up the fight  \\nGet up, stand up, stand up for your right  \\nGet up, stand up, don't give up the fight\\n\\n\"},\n",
       " {'artist': 'Celine Dion',\n",
       "  'song': 'Laissons Entrer Le Soleil',\n",
       "  'text': \"On se guette  \\nTraqu? S? Bout de soufle, marchant  \\nP? Trifi? S dans nos manteaux d'hiver  \\nRefoul? S aux fronti? Res du mensonge des nations qui cr? Vent  \\n  \\nTu parles des are? Ves chim? Riques  \\n? Cras? S de certitudes  \\nDans un monde, glac? De solitude  \\n  \\nSavoir, si quelque part il y a l'espoir  \\nD'? Tre un jour les enfants du hasard  \\nJe vois ma vie projet? E son futur dans l'espace  \\n  \\nEt le silence nous are? Pond, en secret  \\nSon secret  \\n  \\nLaissons, laissons entrer le soleil  \\nLaissons, Laissons  \\nLaissez, laissez entrer le soleil  \\nLaissez, Laissez  \\n  \\nSavoir, si quelque part il y a l'espoir  \\nD'? Tre un jour les enfants du hasard  \\nJe vois ma vie projet? E son futur dans l'espace  \\n  \\nTu? S par des are? Ves chim? Riques  \\n? Cras? S de certitudes  \\nDans un monde, glac? De solitude  \\n  \\nLaissons, laissons entrer le soleil  \\nLaissons, Laissons  \\nLaissez, laissez entrer le soleil  \\nLaissez, Laissez  \\n  \\nLet the sunshine, Let the sunshine in  \\nThe sunshine in  \\nLet the sunshine, Let the sunshine in  \\nThe sunshine in  \\nLet the sunshine, Let the sunshine in  \\nThe sunshine in  \\nLet the sunshine, Let the sunshine in  \\nThe sunshine in  \\n  \\nLaissez le soleil, laissez le soleil entrer  \\n  \\nLaissez entrer le soleil  \\n  \\nLaissez le soleil, laissez le soleil entrer  \\n  \\nLaissez entrer le soleil  \\n  \\nLaissez le soleil, laissez le soleil entrer  \\n  \\nLaissez entrer le soleil  \\n  \\nLaissez le soleil, laissez le soleil entrer  \\n  \\nLaissez entrer le soleil\\n\\n\"},\n",
       " {'artist': 'Bob Marley',\n",
       "  'song': 'War',\n",
       "  'text': \"Until the philosophy which hold one race superior  \\nAnd another  \\nInferior  \\nIs finally  \\nAnd permanently  \\nDiscredited  \\nAnd abandoned  \\nEverywhere is war  \\nMe say war.  \\n  \\nThat until there no longer  \\nFirst class and second class citizens of any nation  \\nUntil the colour of a man's skin  \\nIs of no more significance than the colour of his eyes  \\nMe say war.  \\n  \\nThat until the basic human rights  \\nAre equally guaranteed to all,  \\nWithout regard to race  \\nThis is a war.  \\n  \\nThat until that day  \\nThe dream of lasting peace,  \\nWorld citizenship  \\nRule of international morality  \\nWill remain in but a fleeting illusion to be pursued,  \\nBut never attained  \\nNow everywhere is war - war.  \\n  \\nAnd until the ignoble and unhappy regimes  \\nThat hold our brothers in Angola,  \\nIn Mozambique,  \\nSouth Africa  \\nSub-human bondage  \\nHave been toppled,  \\nUtterly destroyed  \\nWell, everywhere is war  \\nMe say war.  \\n  \\nWar in the east,  \\nWar in the west,  \\nWar up north,  \\nWar down south  \\nWar - war  \\nRumours of war.  \\nAnd until that day,  \\nThe African continent  \\nWill not know peace,  \\nWe Africans will fight - we find it necessary  \\nAnd we know we shall win  \\nAs we are confident  \\nIn the victory  \\n  \\nOf good over evil  \\nGood over evil, yeah!  \\nGood over evil  \\nGood over evil, yeah!  \\nGood over evil  \\nGood over evil, yeah!\\n\\n\"},\n",
       " {'artist': 'Lauryn Hill',\n",
       "  'song': 'Freedom Time',\n",
       "  'text': \"Everybody knows that they guilty  \\nEverybody knows that they've lied  \\nEverybody knows that they guilty  \\nResting on their conscience eating their inside  \\nIt's freedom, said it's freedom time now  \\nIt's freedom, said it's freedom time now  \\nTime to get free, or give yourselves up now  \\nIt's freedom, said it's freedom time  \\n[Rapping]  \\nYo, there's a war in the mind, over territory  \\nFor the dominion  \\nWho will dominate the opinion  \\nSkisms and isms, keepin' us in forms of religion  \\nConformin' our vision  \\nTo the world church of decision  \\nTrapped in a section  \\nSubmitted to committing election  \\nMoral infection  \\nEpidemic lies and deception  \\nInsurrection  \\nOf the highest possible order  \\nDestortin' our tape recorders  \\nFrom hearin' like under water  \\nBeyond the borders  \\nFind the sin in disorder  \\nBound by the strategy  \\nA systematic deprivaty  \\nHeavy as gravity  \\nHead first in the cavity  \\nWithout a bottom  \\nA fate, worse than Sodom  \\nWhat's got 'em, drunk off the spirits  \\nTruth comes, we can't hear it  \\nWhen you've been, programmed to fear it  \\nI had a vision I was fallin' in indescision  \\nApallin', callin' religious  \\nSome program on television  \\nHow can, dominant wisdom  \\nBe recognized in the system  \\nOf Anti-Christ, the majority rules  \\nIntelligent fools  \\nPhD's in illusion  \\nMasters of massconfusion  \\nBachelors in past illusion  \\nNow who you choosin'  \\nThe head, the tail  \\nThe bloodshed of male  \\nOr confidence in the tale  \\nConference is in Yale  \\nDiscussin' doctrines of bail  \\nCausin' people to fail  \\nKeepin' the third in jail  \\nHis word is nail  \\nEverything to the tree  \\nSevering all of me  \\nFrom all that I used to be  \\nFormless and void  \\nTotally paranoid  \\nEnjoy darkness as Lord  \\nKeepin' me from the sword  \\nBlock for mercy  \\nBitter than cerasee  \\nHungry and thirsty  \\nFor good meat we would eat  \\nAnd still, dined at the table of deceit  \\nHow incomplete  \\nFrom confrontation to retreat  \\nWe belong, the true enemies defeat  \\nDestitute a necessity  \\nCausin' desperation to get the best of me  \\nPunishment 'til there was nothing left of me  \\nRealizin' the inescapable death of me  \\nNo options in the valley of decision  \\nThe only doctrine, supernatural circumcision  \\nInwardly, only water can purge the heart  \\nFrom words to fiery darts  \\nThrown by the workers of the arts  \\nIniquity, shapen in  \\nThere's no escapin' when  \\nYour whole philosophy is paper thin  \\nIn vanity  \\nThe wide road is insanity  \\nCould it be all of humanity  \\nPicture that  \\nScripture that  \\nThe origin of a man's heart is black  \\nHow can we show up for  \\nAn invisible war  \\nPreoccupied with a shadow, makin' love with a whore  \\nAchin' in sores  \\nBabylon, the great mystery  \\nMother of human history  \\nSystem of social sorcery  \\nOur present condition  \\nNeeds serious recognition  \\nWhere there's no repentance there can be no remission  \\nAnd that sentence, more serious than Vietnam  \\nThe atom bomb is Saddam and Minister Farakkkhan  \\nWhat's goin' on, what's the priority to you  \\nWhat authority do we do  \\nWhen the majority hasn't a clue  \\nWe majored in curses  \\nSearch the chapters, check the verses  \\nRecapture the land  \\nRemove the mark from off of our hands  \\nSo we can stand  \\nIn agreement with his command  \\nEverything else is damned  \\nLet them with ears understand  \\nEverything else is damned, let them with ears understand  \\nIt's freedom, said it's freedom time now  \\nIt's freedom, said it's freedom time now  \\nIt's freedom, I'ma be who I am  \\nIt's freedom time, said it's freedom time  \\nEverybody knows that they've lied  \\nEverybody knows that they've perpetrated inside  \\nEverybody knows that they guilty, yes  \\nResting on their conscience eating their insides  \\nGet free, be who you're suppost to be  \\nFreedom, said it's freedom time now  \\nFreedom, said it's freedom time  \\nFreedom, freedom time now\\n\\n\"},\n",
       " {'artist': 'Celine Dion',\n",
       "  'song': 'Les Derniers Seront Les Premiers',\n",
       "  'text': \"Quand marcher sans autre but  \\nPlus de pas demain fourbu  \\nDans le n'ant du froid de la rue  \\n  \\nQuand les mots n'existent plus  \\nQuand l'esp?rance oubli?e, dissolue  \\nQuand les alcools m?me ne sao?lent plus  \\nRestent les phrases ?corch?es  \\nDe ces phrases qu'on jette avant de renoncer  \\n  \\nLes derniers seront les premiers  \\nDans l'autre r'alit  \\nNous serons princes d'?ternit?  \\n  \\nUn billet sur le trottoir  \\nDans un journal d'autres histoires  \\nUn rayon de soleil au hasard  \\n  \\nUne fleur abandonne  \\nCe que les autres ont laisse de c'ete  \\nPlus assez neuf, plus assez  \\nQuand ta place est au-dehors  \\nNe reste que ces phrases comme l'autre soir  \\n  \\nLes derniers seront les premiers  \\nDans l'autre r'alit  \\nNous serons princes d'eternite\\n\\n\"},\n",
       " {'artist': 'Celine Dion',\n",
       "  'song': 'Cherche Encore',\n",
       "  'text': \"(Jean-Jacques Goldman)  \\n  \\nY'a tant de murs qui te retiennent  \\nTrop d'inaccessibles? Chelles  \\nDans tes are? Ves et dans tes mots  \\n  \\nTu as choisi l'envers? La peine  \\nAilleurs o? D'autres arcs-en-ciel  \\nTracent des mondes plus beaux  \\n  \\nCherche encore  \\nTant que br? Lera ta flamme  \\nLe paradis qui dort  \\nDans les secrets de ton? Me  \\nCherche encore  \\nSuis ta lumi? Re et tes lois  \\nSi tu peux cherche encore plus fort  \\nEt si jamais tu te perds  \\nJe serai l?, je serai l?  \\n  \\nJe veux rester dans ton histoire  \\nUne petite porte ouverte  \\nDans le couloir o? Tu fuis  \\nDerri? Re les barreaux de ta m? Moire  \\nM? Me o? La raison d? Serte  \\nJe t'entendrai sans un cri  \\n  \\nVa plus loin cherche encore  \\nTant que br? Lera ta flamme  \\nLe paradis qui dort  \\nDans les secrets de ton? Me  \\nCherche encore  \\nSuis ta lumi? Re et ta foi  \\nSi tu peux cherche encore plus fort  \\nEt si jamais tu te perds  \\nJe serai l?, je serai l?  \\n  \\nEt le temps les gens continuent d'avancer  \\nSi tu tombes avant je saurai te porter  \\nEt les vents, les ans, continuent de tourner  \\nSi l'oubli t'attend, moi aussi je l'attendrai\\n\\n\"},\n",
       " {'artist': 'Ween',\n",
       "  'song': 'Ode To Rene',\n",
       "  'text': \"We gotta be tight, why'know  \\nOk, here it goes  \\nThat's more like it  \\n  \\nCe soir, ajournai, et trois l'avec garcon  \\nTrouver poisson t'elle voux  \\nJambon ou deux Schweppes, oh bebe  \\nPour chous avec no nous, apres tu  \\nIl jamais coissants et tele vous  \\nL'amour, bien, bien  \\nA'vril til madame, monsieur, oui, oui  \\nA vous le vous, for you  \\n  \\nThat's right  \\n  \\nCe soir, ajournai, et trois l'avec garcon  \\nTrouver poisson t'elle voux  \\nJambon ou deux Schweppes, oh bebe  \\nPour chous avec no nous, apres tu  \\nIl jamais coissants et tele vous  \\nL'amour, bien, bien  \\nA'vril til madame, monsieur, oui, oui  \\nA vous le vous, for you  \\n  \\nCe soir, ajournai , et trois l'avec garcon  \\nTrouver poisson t'elle voux  \\nJambon ou deux Schweppes, bebe  \\nPour chous avec no nous, apres tu  \\nIl jamais coissants et tele vous  \\nL'amour, bien, bien  \\nA'vril til madame, monsieur, oui, oui  \\nA vous le vous, fuck you, apres tu  \\n  \\nThank you!\\n\\n\"},\n",
       " {'artist': 'Bob Marley',\n",
       "  'song': 'Redemption Song',\n",
       "  'text': \"Old pirates, yes, they rob I,  \\nSold I to the merchant ships,  \\nMinutes after they took I  \\nFrom the bottomless pit.  \\n  \\nBut my hand was made strong  \\nBy the hand of the Almighty.  \\nWe forward in this generation  \\nTriumphantly.  \\n  \\nWon't you help to sing  \\nThese songs of freedom?  \\n'Cause all I ever have,  \\nRedemption songs,  \\nRedemption songs.  \\n  \\nEmancipate yourself from mental slavery,  \\nNone but ourselves can free our minds.  \\nHave no fear for atomic energy,  \\n'Cause none of them can stop the time.  \\nHow long shall they kill our prophets,  \\nWhile we stand aside and look?  \\nSome say it's just a part of it,  \\nWe've got to fulfill the book.  \\n  \\nWon't you help to sing  \\nThese songs of freedom?  \\n'Cause all I ever have,  \\nRedemption songs,  \\nRedemption songs,  \\nRedemption songs.  \\n  \\nEmancipate yourself from mental slavery,  \\nNone but ourselves can free our mind.  \\nHave no fear for atomic energy,  \\n'Cause none of them can stop the time.  \\nHow long shall they kill our prophets,  \\nWhile we stand aside and look?  \\nSome say it's just a part of it,  \\nWe've got to fulfill the book.  \\n  \\nWon't you help to sing,  \\nThese songs of freedom?  \\n'Cause all I ever had,  \\nRedemption songs.  \\nAll I ever had,  \\nRedemption songs  \\nThese songs of freedom  \\nSongs of freedom\\n\\n\"},\n",
       " {'artist': 'Bob Marley',\n",
       "  'song': 'Cheer Up',\n",
       "  'text': \"Cheer up my brothers, cheer up my sisters  \\nCheer up my momma too, lord  \\nCheer up my father, let me say  \\nI know it won't be long  \\nThat change has got to come  \\nThat change has got to come  \\nAnd I know that it won't be long  \\nWe've been down in captivity [captivity] so long, so long  \\nIf we unite then we will be free [we will be free]  \\nSo strong, so strong, come I want you to  \\nCheer up my [brothers] my sisters  \\n[cheer up my sisters] let me say  \\nCheer up my my my momma too, lord  \\nCheer up my father  \\n  \\nLet me say, we've been down in captivity [captivity]  \\nSo long, so long  \\nWe unite we will be free [we will be free]  \\nSo strong, so strong  \\nCheer up my my my my my my brother  \\n[cheer up my sister] cheer up my sisters  \\n[cheer up my momma] my momma too lord  \\n[cheer up my] my father  \\nAnd I, I, I\\n\\n\"},\n",
       " {'artist': 'Celine Dion',\n",
       "  'song': \"L'Univers A Besoin D'Amour\",\n",
       "  'text': \"(Paul Baillargeon)  \\n  \\nOn est venu de la Terre  \\nEn explorateurs d'univers  \\nOn a quitt? La Voie Lact? E  \\nIl y a d? J? 50 ann? Es-lumi? Re  \\n  \\nDe tous les temps sur tous les continents  \\nDes hommes sont pass? S en conteurs d'histoires  \\nLaissant derri? Re eux amour, espoirs  \\nComme lumi? Re pour? Clairer le noir  \\n  \\nO? Sont ces hommes? Je voudrais le savoir.  \\nOn en aurait besoin chez nous  \\n  \\nParlez-nous, parlez-nous de vous  \\nParlez-nous parlez-nous parlez-nous de vous, de vous  \\n  \\n(bis)  \\n  \\nJe veux savoir  \\nQui sont ces hommes, o? Sont-ils pass? S?  \\nOn a besoin de ces hommes chez nous  \\n  \\nParlez-nous, parlez-nous de vous, de vous  \\nParlez-nous parlez-nous parlez-nous de vous  \\nParlez-nous, parlez-nous de vous  \\n  \\nL'univers a besoin d'amour  \\nL'univers a besoin d'amour  \\nL'univers a besoin d'amour  \\nL'univers a besoin d'amour  \\n  \\nL'univers...\\n\\n\"}]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "description = \"\"\"\n",
    "Combattons pour notre liberté et la défense de nos droits.\n",
    "\n",
    "\n",
    "\"\"\"\n",
    "\n",
    "results = find_songs(description)\n",
    "results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "def print_results(results:list[dict]):\n",
    "    for result in results:\n",
    "        print(f\"{result['artist']}: {result['song']}\")\n",
    "        #print(result[\"text\"])\n",
    "        #print(\"\\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Celine Dion: Je Ne Vous Oublie Pas\n",
      "Marianne Faithfull: Coquillage\n",
      "Celine Dion: La Religieuse\n",
      "Michael Bolton: Une Femme Comme Toi\n",
      "Gloria Estefan: Amour Infini\n",
      "David Bowie: Chant Of The Ever Circling Skeletal\n",
      "Celine Dion: Carmen\n",
      "Celine Dion: Glory Alleluia\n",
      "Marianne Faithfull: Plaisir D'amour\n",
      "Celine Dion: Je Ne Veux Pas\n"
     ]
    }
   ],
   "source": [
    "for result in results:\n",
    "    print(f\"{result['artist']}: {result['song']}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "headlines_description = \"\"\"\n",
    "J'ai réussi dans ma carrière je suis libre, j'en ai plus rien à foutre de ce que les gens pensent de moi.\n",
    "\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gucci Mane: Grown Man\n",
      "Warren Zevon: Laissez-Moi Tranquille\n",
      "Celine Dion: Lolita\n",
      "Ween: Ode To Rene\n",
      "Drake: Money 2 Blow\n",
      "Celine Dion: Cherche Encore\n",
      "Celine Dion: Je Ne Vous Oublie Pas\n",
      "David Bowie: Almost Grown\n",
      "Chris Brown: 4 Years Old\n",
      "David Bowie: Anyway, Anyhow, Anywhere\n"
     ]
    }
   ],
   "source": [
    "#results = find_songs(headlines_description)\n",
    "print_results(results)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "started_from_the_bottom_description = \"\"\"\n",
    "Grinding and going up the ladder\n",
    "\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lauryn Hill: I Had To Walk\n",
      "David Bowie: Chant Of The Ever Circling Skeletal\n",
      "Gucci Mane: Hustle\n",
      "Bob Marley: Iron, Lion, Zion\n",
      "Drake: Stunt Hard\n",
      "Gucci Mane: I'm Up\n",
      "David Bowie: Jump They Say\n",
      "David Bowie: It Ain't Easy\n",
      "Drake: Say What's Real\n",
      "Lauryn Hill: Do You Like The Way\n"
     ]
    }
   ],
   "source": [
    "results = find_songs(started_from_the_bottom_description)\n",
    "print_results(results)"
   ]
  }
 ],
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