diff --git a/rhyme_generator.ipynb b/rhyme_generator.ipynb
new file mode 100644
index 0000000..c54e3dd
--- /dev/null
+++ b/rhyme_generator.ipynb
@@ -0,0 +1,395 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Using TensorFlow backend.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "corpus length: 203492\n"
+     ]
+    }
+   ],
+   "source": [
+    "from __future__ import print_function\n",
+    "from keras.callbacks import LambdaCallback\n",
+    "from keras.models import Sequential\n",
+    "from keras.layers import Dense\n",
+    "from keras.layers import LSTM\n",
+    "from keras.optimizers import RMSprop\n",
+    "from keras.utils.data_utils import get_file\n",
+    "import numpy as np\n",
+    "import random\n",
+    "import sys\n",
+    "import io"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "corpus length: 34517\n",
+      "total chars: 6960\n"
+     ]
+    }
+   ],
+   "source": [
+    "path = 'rhymes.txt'\n",
+    "with open(path, encoding='utf-8') as f:\n",
+    "    text = f.read().lower()\n",
+    "\n",
+    "text = text.split()\n",
+    "print('corpus length:', len(text))\n",
+    "\n",
+    "chars = sorted(list(set(text)))\n",
+    "print('total chars:', len(chars))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "nb sequences: 34477\n",
+      "Vectorization...\n",
+      "Build model...\n",
+      "Epoch 1/20\n",
+      "34477/34477 [==============================] - 221s 6ms/step - loss: 7.9745\n",
+      "\n",
+      "----- Generating text after Epoch: 0\n",
+      "----- diversity: 0.2\n",
+      "----- Generating with seed: \"['oystermouth', 'way', 'bay', 'alone', 'stone', 'tolled', 'when', 'cry', 'men', 'he', 'sea', 'said', 'head', 'roar', 'oar', 'sons', 'guns', 'love', 'above', 'bed', 'head', 'blew', 'crew', 'afloat', 'boat', 'high', 'caves', 'waves', 'storm', 'form', 'breath', 'death', 'lips', 'ships', 'and', 'lighthouse', 'shore', 'hand', 'land', 'save']\"\n",
+      "['be', ['oystermouth', 'way', 'bay', 'alone', 'stone', 'tolled', 'when', 'cry', 'men', 'he', 'sea', 'said', 'head', 'roar', 'oar', 'sons', 'guns', 'love', 'above', 'bed', 'head', 'blew', 'crew', 'afloat', 'boat', 'high', 'caves', 'waves', 'storm', 'form', 'breath', 'death', 'lips', 'ships', 'and', 'lighthouse', 'shore', 'hand', 'land', 'save']]['day']['day']['away']['away']['day']['away']['day']['day']['there']['day']['day']['away']['day']['away']['day']['away']['day']['day']['away']['day']['day']['day']['way']['day']['day']['away']['night']['away']['day']['away']['day']['away']['day']['away']['there']['day']['away']['light']['sky']['away']\n",
+      "----- diversity: 0.5\n",
+      "----- Generating with seed: \"['oystermouth', 'way', 'bay', 'alone', 'stone', 'tolled', 'when', 'cry', 'men', 'he', 'sea', 'said', 'head', 'roar', 'oar', 'sons', 'guns', 'love', 'above', 'bed', 'head', 'blew', 'crew', 'afloat', 'boat', 'high', 'caves', 'waves', 'storm', 'form', 'breath', 'death', 'lips', 'ships', 'and', 'lighthouse', 'shore', 'hand', 'land', 'save']\"\n",
+      "['be', ['oystermouth', 'way', 'bay', 'alone', 'stone', 'tolled', 'when', 'cry', 'men', 'he', 'sea', 'said', 'head', 'roar', 'oar', 'sons', 'guns', 'love', 'above', 'bed', 'head', 'blew', 'crew', 'afloat', 'boat', 'high', 'caves', 'waves', 'storm', 'form', 'breath', 'death', 'lips', 'ships', 'and', 'lighthouse', 'shore', 'hand', 'land', 'save']]['away']['made']['out']['light']['her']['fall']['there']['blow']['still']['hand']['morn']['way']['again']['be']['again']['heaven']['place']['strong']['ring']['world']['be']['it']['it']['it']['it']['it']['it']['it']['it']['it']['it']['it']['it']['it']['it']['it']['it']['it']['it']['it']\n",
+      "----- diversity: 1.0\n",
+      "----- Generating with seed: \"['oystermouth', 'way', 'bay', 'alone', 'stone', 'tolled', 'when', 'cry', 'men', 'he', 'sea', 'said', 'head', 'roar', 'oar', 'sons', 'guns', 'love', 'above', 'bed', 'head', 'blew', 'crew', 'afloat', 'boat', 'high', 'caves', 'waves', 'storm', 'form', 'breath', 'death', 'lips', 'ships', 'and', 'lighthouse', 'shore', 'hand', 'land', 'save']\"\n",
+      "['be', ['oystermouth', 'way', 'bay', 'alone', 'stone', 'tolled', 'when', 'cry', 'men', 'he', 'sea', 'said', 'head', 'roar', 'oar', 'sons', 'guns', 'love', 'above', 'bed', 'head', 'blew', 'crew', 'afloat', 'boat', 'high', 'caves', 'waves', 'storm', 'form', 'breath', 'death', 'lips', 'ships', 'and', 'lighthouse', 'shore', 'hand', 'land', 'save']]['meets']['tree']['made']['sorrow']['mine']['dwell']['amount']['morrow']['way']['shame']['children']['scorn']['play']['sinfulness']['eye']['wood']['intent']['wing']['prayer']['will']['light']['god']['struck']['close']['true']['road']['things']['flare']['sight']['war']['pain']['rough']['home']['out']['close']['green']['head']['curses']['spirit']['nerves']\n",
+      "----- diversity: 1.2\n",
+      "----- Generating with seed: \"['oystermouth', 'way', 'bay', 'alone', 'stone', 'tolled', 'when', 'cry', 'men', 'he', 'sea', 'said', 'head', 'roar', 'oar', 'sons', 'guns', 'love', 'above', 'bed', 'head', 'blew', 'crew', 'afloat', 'boat', 'high', 'caves', 'waves', 'storm', 'form', 'breath', 'death', 'lips', 'ships', 'and', 'lighthouse', 'shore', 'hand', 'land', 'save']\"\n",
+      "['be', ['oystermouth', 'way', 'bay', 'alone', 'stone', 'tolled', 'when', 'cry', 'men', 'he', 'sea', 'said', 'head', 'roar', 'oar', 'sons', 'guns', 'love', 'above', 'bed', 'head', 'blew', 'crew', 'afloat', 'boat', 'high', 'caves', 'waves', 'storm', 'form', 'breath', 'death', 'lips', 'ships', 'and', 'lighthouse', 'shore', 'hand', 'land', 'save']]['shore']['take']['strife']['boom']['hum']['starlight']['talk']['win']['washington']['you']['bound']['war']['bride']['will']['shook']['snarls']['threshold']['sweetness']['thee']['cured']['fail']['trundle-bed']['sheep']['afternoon']['sly']['pine-tree']['we']['reveal']['smirk']['miles']['france']['care']['so']['sweet']['rendezvous']['understood']['demurred—']['morn']['flower-like']['with']\n",
+      "Epoch 2/20\n",
+      "34477/34477 [==============================] - 218s 6ms/step - loss: 7.4730\n",
+      "Epoch 3/20\n",
+      "34477/34477 [==============================] - 219s 6ms/step - loss: 6.9996\n",
+      "Epoch 4/20\n",
+      "34477/34477 [==============================] - 218s 6ms/step - loss: 6.7760\n",
+      "Epoch 5/20\n",
+      "34477/34477 [==============================] - 219s 6ms/step - loss: 6.6035\n",
+      "Epoch 6/20\n",
+      "34477/34477 [==============================] - 221s 6ms/step - loss: 6.3921\n",
+      "\n",
+      "----- Generating text after Epoch: 5\n",
+      "----- diversity: 0.2\n",
+      "----- Generating with seed: \"['strife', 'life', 'urge', 'surge', 'stride', 'beside', 'passed', 'on', 'fawn', 'strained', 'trained', 'cost', 'lost', 'strength', 'length', 'mine--no', 'blow', 'gun', 'one', 'lump', 'rump', 'bolder', 'shoulder', 'steed', 'heed', 'calls', 'falls', 'storm', 'form', 'hand', 'stand', 'done', 'won', 'say', 'men', 'again', 'surf', 'turf', 'years', 'peers']\"\n",
+      "['be', ['strife', 'life', 'urge', 'surge', 'stride', 'beside', 'passed', 'on', 'fawn', 'strained', 'trained', 'cost', 'lost', 'strength', 'length', 'mine--no', 'blow', 'gun', 'one', 'lump', 'rump', 'bolder', 'shoulder', 'steed', 'heed', 'calls', 'falls', 'storm', 'form', 'hand', 'stand', 'done', 'won', 'say', 'men', 'again', 'surf', 'turf', 'years', 'peers']]['there']['care']['there']['care']['there']['air']['there']['care']['pain']['again']['rest']['breast']['breast']['rest']['rest']['breast']['breast']['rest']['cold']['gold']['cold']['gold']['cold']['gold']['old']['gold']['cold']['gold']['be']['me']['me']['me']['soul']['soul']['roll']['soul']['soul']['roll']['soul']['soul']\n",
+      "----- diversity: 0.5\n",
+      "----- Generating with seed: \"['strife', 'life', 'urge', 'surge', 'stride', 'beside', 'passed', 'on', 'fawn', 'strained', 'trained', 'cost', 'lost', 'strength', 'length', 'mine--no', 'blow', 'gun', 'one', 'lump', 'rump', 'bolder', 'shoulder', 'steed', 'heed', 'calls', 'falls', 'storm', 'form', 'hand', 'stand', 'done', 'won', 'say', 'men', 'again', 'surf', 'turf', 'years', 'peers']\"\n",
+      "['be', ['strife', 'life', 'urge', 'surge', 'stride', 'beside', 'passed', 'on', 'fawn', 'strained', 'trained', 'cost', 'lost', 'strength', 'length', 'mine--no', 'blow', 'gun', 'one', 'lump', 'rump', 'bolder', 'shoulder', 'steed', 'heed', 'calls', 'falls', 'storm', 'form', 'hand', 'stand', 'done', 'won', 'say', 'men', 'again', 'surf', 'turf', 'years', 'peers']]['place']['be']['me']['eye']['me']['be']['sea']['me']['me']['be']['me']['sea']['me']['be']['me']['be']['me']['sea']['me']['soul']['be']['me']['sea']['me']['me']['be']['me']['sea']['me']['sea']['be']['me']['sea']['be']['me']['sea']['be']['me']['thee']['sea']\n",
+      "----- diversity: 1.0\n",
+      "----- Generating with seed: \"['strife', 'life', 'urge', 'surge', 'stride', 'beside', 'passed', 'on', 'fawn', 'strained', 'trained', 'cost', 'lost', 'strength', 'length', 'mine--no', 'blow', 'gun', 'one', 'lump', 'rump', 'bolder', 'shoulder', 'steed', 'heed', 'calls', 'falls', 'storm', 'form', 'hand', 'stand', 'done', 'won', 'say', 'men', 'again', 'surf', 'turf', 'years', 'peers']\"\n",
+      "['be', ['strife', 'life', 'urge', 'surge', 'stride', 'beside', 'passed', 'on', 'fawn', 'strained', 'trained', 'cost', 'lost', 'strength', 'length', 'mine--no', 'blow', 'gun', 'one', 'lump', 'rump', 'bolder', 'shoulder', 'steed', 'heed', 'calls', 'falls', 'storm', 'form', 'hand', 'stand', 'done', 'won', 'say', 'men', 'again', 'surf', 'turf', 'years', 'peers']]['time']['roof']['sea']['high']['stone']['death']['shed']['winter']['word']['bread']['tell']['well']['fell']['fine']['arm']['corn']['be']['be']['child']['sea']['fright']['town']['walls']['ground']['milk']['divine']['tender']['shame']['years']['dawn']['dawn']['flow']['stands']['king']['sublime']['sun']['me']['keep']['plant']['die']\n",
+      "----- diversity: 1.2\n",
+      "----- Generating with seed: \"['strife', 'life', 'urge', 'surge', 'stride', 'beside', 'passed', 'on', 'fawn', 'strained', 'trained', 'cost', 'lost', 'strength', 'length', 'mine--no', 'blow', 'gun', 'one', 'lump', 'rump', 'bolder', 'shoulder', 'steed', 'heed', 'calls', 'falls', 'storm', 'form', 'hand', 'stand', 'done', 'won', 'say', 'men', 'again', 'surf', 'turf', 'years', 'peers']\"\n",
+      "['be', ['strife', 'life', 'urge', 'surge', 'stride', 'beside', 'passed', 'on', 'fawn', 'strained', 'trained', 'cost', 'lost', 'strength', 'length', 'mine--no', 'blow', 'gun', 'one', 'lump', 'rump', 'bolder', 'shoulder', 'steed', 'heed', 'calls', 'falls', 'storm', 'form', 'hand', 'stand', 'done', 'won', 'say', 'men', 'again', 'surf', 'turf', 'years', 'peers']]['rise']['glad']['revealed']['cheek']['each']['view']['state']['tried']['he']['now']['days']['hill']['gold']['go']['follow']['heaven']['night']['height']['light']['door']['more']['style']['heart']['her']['been']['slave']['do']['years']['end']['life']['been']['her']['she']['part']['me']['speak']['floor']['go']['alone']['away']\n",
+      "Epoch 7/20\n",
+      "34477/34477 [==============================] - 228s 7ms/step - loss: 6.1825\n",
+      "Epoch 8/20\n",
+      "34477/34477 [==============================] - 229s 7ms/step - loss: 5.9736\n",
+      "Epoch 9/20\n",
+      "34477/34477 [==============================] - 220s 6ms/step - loss: 5.7911\n",
+      "Epoch 10/20\n",
+      "34477/34477 [==============================] - 220s 6ms/step - loss: 5.6130\n",
+      "Epoch 11/20\n",
+      "34477/34477 [==============================] - 219s 6ms/step - loss: 5.4404\n",
+      "\n",
+      "----- Generating text after Epoch: 10\n",
+      "----- diversity: 0.2\n",
+      "----- Generating with seed: \"['place', 'undertone', 'drew', 'adieu', 'behest', 'stayed', 'land', 'hand', 'cloak', 'spoke', 'will', \"howe'er\", 'peer', 'alone', 'foundation-stone', 'own', 'grasp', 'clasp', 'fire', 'ire', 'said', 'spared', 'head', 'peer', 'here', 'pride', 'near', 'sword', 'defied', 'peer', 'here', 'near', 'lied', 'rage', 'age', 'then', 'den', 'hall', 'go', 'no']\"\n",
+      "['be', ['place', 'undertone', 'drew', 'adieu', 'behest', 'stayed', 'land', 'hand', 'cloak', 'spoke', 'will', \"howe'er\", 'peer', 'alone', 'foundation-stone', 'own', 'grasp', 'clasp', 'fire', 'ire', 'said', 'spared', 'head', 'peer', 'here', 'pride', 'near', 'sword', 'defied', 'peer', 'here', 'near', 'lied', 'rage', 'age', 'then', 'den', 'hall', 'go', 'no']]['died']['all']['eyes']['dead']['said']['head']['dead']['said']['head']['dead']['said']['head']['out']['about']['out']['about']['out']['about']['out']['about']['out']['about']['out']['about']['out']['about']['out']['about']['out']['about']['out']['about']['out']['about']['out']['about']['it']['again']['deep']['sleep']\n",
+      "----- diversity: 0.5\n",
+      "----- Generating with seed: \"['place', 'undertone', 'drew', 'adieu', 'behest', 'stayed', 'land', 'hand', 'cloak', 'spoke', 'will', \"howe'er\", 'peer', 'alone', 'foundation-stone', 'own', 'grasp', 'clasp', 'fire', 'ire', 'said', 'spared', 'head', 'peer', 'here', 'pride', 'near', 'sword', 'defied', 'peer', 'here', 'near', 'lied', 'rage', 'age', 'then', 'den', 'hall', 'go', 'no']\"\n",
+      "['be', ['place', 'undertone', 'drew', 'adieu', 'behest', 'stayed', 'land', 'hand', 'cloak', 'spoke', 'will', \"howe'er\", 'peer', 'alone', 'foundation-stone', 'own', 'grasp', 'clasp', 'fire', 'ire', 'said', 'spared', 'head', 'peer', 'here', 'pride', 'near', 'sword', 'defied', 'peer', 'here', 'near', 'lied', 'rage', 'age', 'then', 'den', 'hall', 'go', 'no']]['yet']['all']['dead']['hand']['stand']['hand']['land']['day']['lay']['eyes']['rise']['skies']['fled']['eyes']['shore']['name']['dead']['said']['shame']['came']['name']['shame']['name']['us']['me']['gay']['bright']['sky']['air']['there']['care']['prayer']['star']['me']['me']['be']['made']['shore']['more']['on']\n",
+      "----- diversity: 1.0\n",
+      "----- Generating with seed: \"['place', 'undertone', 'drew', 'adieu', 'behest', 'stayed', 'land', 'hand', 'cloak', 'spoke', 'will', \"howe'er\", 'peer', 'alone', 'foundation-stone', 'own', 'grasp', 'clasp', 'fire', 'ire', 'said', 'spared', 'head', 'peer', 'here', 'pride', 'near', 'sword', 'defied', 'peer', 'here', 'near', 'lied', 'rage', 'age', 'then', 'den', 'hall', 'go', 'no']\"\n",
+      "['be', ['place', 'undertone', 'drew', 'adieu', 'behest', 'stayed', 'land', 'hand', 'cloak', 'spoke', 'will', \"howe'er\", 'peer', 'alone', 'foundation-stone', 'own', 'grasp', 'clasp', 'fire', 'ire', 'said', 'spared', 'head', 'peer', 'here', 'pride', 'near', 'sword', 'defied', 'peer', 'here', 'near', 'lied', 'rage', 'age', 'then', 'den', 'hall', 'go', 'no']]['mother']['eyes']['way']['side']['beside']['king']['mind']['sight']['john']['sorrow']['with']['corn']['fame']['know']['relief']['gaze']['dress']['save']['went']['wall']['ended']['array']['dim']['success']['boy']['chin']['play']['see']['be']['faster']['breast']['rocked']['on']['true']['do']['trod']['me']['me']['earth']['arose']\n",
+      "----- diversity: 1.2\n",
+      "----- Generating with seed: \"['place', 'undertone', 'drew', 'adieu', 'behest', 'stayed', 'land', 'hand', 'cloak', 'spoke', 'will', \"howe'er\", 'peer', 'alone', 'foundation-stone', 'own', 'grasp', 'clasp', 'fire', 'ire', 'said', 'spared', 'head', 'peer', 'here', 'pride', 'near', 'sword', 'defied', 'peer', 'here', 'near', 'lied', 'rage', 'age', 'then', 'den', 'hall', 'go', 'no']\"\n",
+      "['be', ['place', 'undertone', 'drew', 'adieu', 'behest', 'stayed', 'land', 'hand', 'cloak', 'spoke', 'will', \"howe'er\", 'peer', 'alone', 'foundation-stone', 'own', 'grasp', 'clasp', 'fire', 'ire', 'said', 'spared', 'head', 'peer', 'here', 'pride', 'near', 'sword', 'defied', 'peer', 'here', 'near', 'lied', 'rage', 'age', 'then', 'den', 'hall', 'go', 'no']]['dream']['delight']['strong']['spell']['men']['eye']['slowly']['spot']['my']['find']['curls']['top']['enderby']['skies']['sea']['eyes']['lies']['play']['see']['smile']['must']['roam']['flee']['east']['mouse']['press']['sight']['ought']['school']['beast']['sextus']['mine']['power']['turn']['the']['of']['near']['ashore']['hands']['view']\n",
+      "Epoch 12/20\n",
+      "34477/34477 [==============================] - 220s 6ms/step - loss: 5.2854\n",
+      "Epoch 13/20\n",
+      "34477/34477 [==============================] - 221s 6ms/step - loss: 5.1560\n",
+      "Epoch 14/20\n",
+      "34477/34477 [==============================] - 224s 6ms/step - loss: 5.0554\n",
+      "Epoch 15/20\n",
+      "34477/34477 [==============================] - 231s 7ms/step - loss: 4.9645\n",
+      "Epoch 16/20\n",
+      "34477/34477 [==============================] - 235s 7ms/step - loss: 4.8694\n",
+      "\n",
+      "----- Generating text after Epoch: 15\n",
+      "----- diversity: 0.2\n",
+      "----- Generating with seed: \"['eyes', 'fell', 'own', 'blown', 'heart', 'in', 'part', 'sigh', 'why', 'tell', 'sell', 'away', 'day', 'fair', 'hair', 'white', 'to-night', 'cold', 'nigh', 'white', 'to-night', 'dart', 'hour', 'right', 'to-night', 'brow', 'vow', 'sigh', 'bright', 'to-night', 'door', 'before', 'aglow', 'fro', 'light', 'to-night', 'bell', 'hell', 'now', 'brow']\"\n",
+      "['be', ['eyes', 'fell', 'own', 'blown', 'heart', 'in', 'part', 'sigh', 'why', 'tell', 'sell', 'away', 'day', 'fair', 'hair', 'white', 'to-night', 'cold', 'nigh', 'white', 'to-night', 'dart', 'hour', 'right', 'to-night', 'brow', 'vow', 'sigh', 'bright', 'to-night', 'door', 'before', 'aglow', 'fro', 'light', 'to-night', 'bell', 'hell', 'now', 'brow']]['light']['to-night']['rest']['breast']['door']['floor']['more']['door']['shore']['more']['shore']['yore']['shore']['still']['shore']['more']['shore']['bay']['lay']['away']['bay']['town']['down']['town']['done']['down']['on']['all']['more']['shore']['bay']['it']['it']['to']['too']['you']['true']['too']['you']['blue']\n",
+      "----- diversity: 0.5\n",
+      "----- Generating with seed: \"['eyes', 'fell', 'own', 'blown', 'heart', 'in', 'part', 'sigh', 'why', 'tell', 'sell', 'away', 'day', 'fair', 'hair', 'white', 'to-night', 'cold', 'nigh', 'white', 'to-night', 'dart', 'hour', 'right', 'to-night', 'brow', 'vow', 'sigh', 'bright', 'to-night', 'door', 'before', 'aglow', 'fro', 'light', 'to-night', 'bell', 'hell', 'now', 'brow']\"\n",
+      "['be', ['eyes', 'fell', 'own', 'blown', 'heart', 'in', 'part', 'sigh', 'why', 'tell', 'sell', 'away', 'day', 'fair', 'hair', 'white', 'to-night', 'cold', 'nigh', 'white', 'to-night', 'dart', 'hour', 'right', 'to-night', 'brow', 'vow', 'sigh', 'bright', 'to-night', 'door', 'before', 'aglow', 'fro', 'light', 'to-night', 'bell', 'hell', 'now', 'brow']]['light']['to-night']['need']['more']['shore']['yore']['shore']['before']['shore']['yore']['child']['smiled']['too']['he']['door']['sea']['thing']['word']['day']['he']['be']['sea']['snow']['eyes']['free']['be']['along']['grace']['face']['me']['too']['sped']['me']['too']['do']['hand']['day']['sun']['gray']['white']\n",
+      "----- diversity: 1.0\n",
+      "----- Generating with seed: \"['eyes', 'fell', 'own', 'blown', 'heart', 'in', 'part', 'sigh', 'why', 'tell', 'sell', 'away', 'day', 'fair', 'hair', 'white', 'to-night', 'cold', 'nigh', 'white', 'to-night', 'dart', 'hour', 'right', 'to-night', 'brow', 'vow', 'sigh', 'bright', 'to-night', 'door', 'before', 'aglow', 'fro', 'light', 'to-night', 'bell', 'hell', 'now', 'brow']\"\n",
+      "['be', ['eyes', 'fell', 'own', 'blown', 'heart', 'in', 'part', 'sigh', 'why', 'tell', 'sell', 'away', 'day', 'fair', 'hair', 'white', 'to-night', 'cold', 'nigh', 'white', 'to-night', 'dart', 'hour', 'right', 'to-night', 'brow', 'vow', 'sigh', 'bright', 'to-night', 'door', 'before', 'aglow', 'fro', 'light', 'to-night', 'bell', 'hell', 'now', 'brow']]['light']['to-night']['speak']['red']['head']['of']['bad']['within']['sin']['springs']['low']['sat']['cat']['everywhere']['clear']['pride']['success']['waiting']['bend']['two']['men']['dead']['low']['it']['it']['wide']['place']['bare']['thee']['name']['mead']['sight']['sail']['hand']['band']['fro']['wood']['while']['eye']['fight']\n",
+      "----- diversity: 1.2\n",
+      "----- Generating with seed: \"['eyes', 'fell', 'own', 'blown', 'heart', 'in', 'part', 'sigh', 'why', 'tell', 'sell', 'away', 'day', 'fair', 'hair', 'white', 'to-night', 'cold', 'nigh', 'white', 'to-night', 'dart', 'hour', 'right', 'to-night', 'brow', 'vow', 'sigh', 'bright', 'to-night', 'door', 'before', 'aglow', 'fro', 'light', 'to-night', 'bell', 'hell', 'now', 'brow']\"\n",
+      "['be', ['eyes', 'fell', 'own', 'blown', 'heart', 'in', 'part', 'sigh', 'why', 'tell', 'sell', 'away', 'day', 'fair', 'hair', 'white', 'to-night', 'cold', 'nigh', 'white', 'to-night', 'dart', 'hour', 'right', 'to-night', 'brow', 'vow', 'sigh', 'bright', 'to-night', 'door', 'before', 'aglow', 'fro', 'light', 'to-night', 'bell', 'hell', 'now', 'brow']]['still']['stir']['pace']['face']['more']['done']['desire']['tongue']['kind']['future']['creed']['stay']['burning']['own']['me']['more']['delight']['queen']['thought']['glow']['grow']['high']['youth']['falling']['jaw']['clay']['last']['grasp']['harm']['roar']['knee']['takes']['quee']['flow']['there']['day']['lay']['court']['off']['eyes']\n",
+      "Epoch 17/20\n",
+      "34477/34477 [==============================] - 223s 6ms/step - loss: 4.7961\n",
+      "Epoch 18/20\n",
+      "34477/34477 [==============================] - 222s 6ms/step - loss: 4.7257\n",
+      "Epoch 19/20\n",
+      "34477/34477 [==============================] - 223s 6ms/step - loss: 4.6614\n",
+      "Epoch 20/20\n",
+      "34477/34477 [==============================] - 222s 6ms/step - loss: 4.6155\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<keras.callbacks.History at 0x7f420c0a1400>"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "\n",
+    "char_indices = dict((c, i) for i, c in enumerate(chars))\n",
+    "indices_char = dict((i, c) for i, c in enumerate(chars))\n",
+    "\n",
+    "# cut the text in semi-redundant sequences of maxlen characters\n",
+    "maxlen = 40\n",
+    "step = 1\n",
+    "sentences = []\n",
+    "next_chars = []\n",
+    "\n",
+    "\n",
+    "for i in range(0, len(text) - maxlen, step):\n",
+    "    sentences.append(text[i: i + maxlen])\n",
+    "    next_chars.append(text[i + maxlen])\n",
+    "print('nb sequences:', len(sentences))\n",
+    "\n",
+    "print('Vectorization...')\n",
+    "x = np.zeros((len(sentences), maxlen, len(chars)), dtype=np.bool)\n",
+    "y = np.zeros((len(sentences), len(chars)), dtype=np.bool)\n",
+    "for i, sentence in enumerate(sentences):\n",
+    "    for t, char in enumerate(sentence):\n",
+    "        x[i, t, char_indices[char]] = 1\n",
+    "    y[i, char_indices[next_chars[i]]] = 1\n",
+    "\n",
+    "\n",
+    "# build the model: a single LSTM\n",
+    "print('Build model...')\n",
+    "model = Sequential()\n",
+    "model.add(LSTM(128, input_shape=(maxlen, len(chars))))\n",
+    "model.add(Dense(len(chars), activation='softmax'))\n",
+    "\n",
+    "optimizer = RMSprop(lr=0.01)\n",
+    "model.compile(loss='categorical_crossentropy', optimizer=optimizer)\n",
+    "\n",
+    "\n",
+    "def sample(preds, temperature=1.0):\n",
+    "    # helper function to sample an index from a probability array\n",
+    "    preds = np.asarray(preds).astype('float64')\n",
+    "    preds = np.log(preds) / temperature\n",
+    "    exp_preds = np.exp(preds)\n",
+    "    preds = exp_preds / np.sum(exp_preds)\n",
+    "    probas = np.random.multinomial(1, preds, 1)\n",
+    "    return np.argmax(probas)\n",
+    "\n",
+    "\n",
+    "char_indices = dict((c, i) for i, c in enumerate(chars))\n",
+    "indices_char = dict((i, c) for i, c in enumerate(chars))\n",
+    "\n",
+    "# cut the text in semi-redundant sequences of maxlen characters\n",
+    "maxlen = 40\n",
+    "step = 1\n",
+    "sentences = []\n",
+    "next_chars = []\n",
+    "\n",
+    "\n",
+    "for i in range(0, len(text) - maxlen, step):\n",
+    "    sentences.append(text[i: i + maxlen])\n",
+    "    next_chars.append(text[i + maxlen])\n",
+    "print('nb sequences:', len(sentences))\n",
+    "\n",
+    "print('Vectorization...')\n",
+    "x = np.zeros((len(sentences), maxlen, len(chars)), dtype=np.bool)\n",
+    "y = np.zeros((len(sentences), len(chars)), dtype=np.bool)\n",
+    "for i, sentence in enumerate(sentences):\n",
+    "    for t, char in enumerate(sentence):\n",
+    "        x[i, t, char_indices[char]] = 1\n",
+    "    y[i, char_indices[next_chars[i]]] = 1\n",
+    "\n",
+    "\n",
+    "# build the model: a single LSTM\n",
+    "print('Build model...')\n",
+    "model = Sequential()\n",
+    "model.add(LSTM(128, input_shape=(maxlen, len(chars))))\n",
+    "model.add(Dense(len(chars), activation='softmax'))\n",
+    "\n",
+    "optimizer = RMSprop(lr=0.01)\n",
+    "model.compile(loss='categorical_crossentropy', optimizer=optimizer)\n",
+    "\n",
+    "\n",
+    "def sample(preds, temperature=1.0):\n",
+    "    # helper function to sample an index from a probability array\n",
+    "    preds = np.asarray(preds).astype('float64')\n",
+    "    preds = np.log(preds) / temperature\n",
+    "    exp_preds = np.exp(preds)\n",
+    "    preds = exp_preds / np.sum(exp_preds)\n",
+    "    probas = np.random.multinomial(1, preds, 1)\n",
+    "    return np.argmax(probas)\n",
+    "\n",
+    "\n",
+    "def on_epoch_end(epoch, _):\n",
+    "    # Function invoked at end of each epoch. Prints generated text.\n",
+    "    if epoch % 5 == 0:\n",
+    "        print()\n",
+    "        print('----- Generating text after Epoch: {}'.format(epoch + 1))\n",
+    "\n",
+    "        start_index = random.randint(0, len(text) - maxlen - 1)\n",
+    "        for diversity in [0.2, 0.5, 1.0, 1.2]:\n",
+    "            print('----- diversity:', diversity)\n",
+    "\n",
+    "            generated = []\n",
+    "            sentence = text[start_index: start_index + maxlen]\n",
+    "            generated += sentence\n",
+    "            print('----- Generating with seed: \"{}\"'.format(sentence))\n",
+    "            sys.stdout.write(\"{}\".format(generated))\n",
+    "\n",
+    "            for i in range(40):\n",
+    "                x_pred = np.zeros((1, maxlen, len(chars)))\n",
+    "                for t, char in enumerate(sentence):\n",
+    "                    x_pred[0, t, char_indices[char]] = 1.\n",
+    "\n",
+    "                preds = model.predict(x_pred, verbose=0)[0]\n",
+    "                next_index = sample(preds, diversity)\n",
+    "                next_char = indices_char[next_index]\n",
+    "\n",
+    "                generated += [next_char]\n",
+    "                sentence = sentence[1:] + [next_char]\n",
+    "\n",
+    "                sys.stdout.write('{}'.format([next_char]))\n",
+    "                sys.stdout.flush()\n",
+    "            print()\n",
+    "\n",
+    "print_callback = LambdaCallback(on_epoch_end=on_epoch_end)\n",
+    "\n",
+    "model.fit(x, y,\n",
+    "          batch_size=128,\n",
+    "          epochs=20,\n",
+    "callbacks=[print_callback])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "----- diversity: 0.2\n",
+      "----- Generating with seed: \"['because', 'pause', 'gray', 'play', 'say', 'day', 'sheridan', 'man', 'high', 'sky', 'fame', 'name', 'bright', 'fight', 'away', 'bethlehem', 'lie', 'sleep', 'by', 'shineth', 'light', 'years', 'to-night', 'mary', 'above', 'keep', 'love', 'together', 'birth', 'king', 'earth', 'silently', 'given', 'hearts', 'heaven', 'coming', 'sin', 'still', 'in', 'bethlehem']\"\n",
+      "['be', ['because', 'pause', 'gray', 'play', 'say', 'day', 'sheridan', 'man', 'high', 'sky', 'fame', 'name', 'bright', 'fight', 'away', 'bethlehem', 'lie', 'sleep', 'by', 'shineth', 'light', 'years', 'to-night', 'mary', 'above', 'keep', 'love', 'together', 'birth', 'king', 'earth', 'silently', 'given', 'hearts', 'heaven', 'coming', 'sin', 'still', 'in', 'bethlehem']]['pray']['in']['to-day']['all']['fall']['fall']['again']['all']['came']['strong']['wrong']['song']['rest']['too']['you']['strong']['song']['now']['now']['now']['now']['light']['sight']['flight']['air']['there']['air']['lay']['hand']['land']['air']['lay']['hand']['white']['go']['snow']['below']['blow']['go']['blow']\n",
+      "----- diversity: 0.5\n",
+      "----- Generating with seed: \"['because', 'pause', 'gray', 'play', 'say', 'day', 'sheridan', 'man', 'high', 'sky', 'fame', 'name', 'bright', 'fight', 'away', 'bethlehem', 'lie', 'sleep', 'by', 'shineth', 'light', 'years', 'to-night', 'mary', 'above', 'keep', 'love', 'together', 'birth', 'king', 'earth', 'silently', 'given', 'hearts', 'heaven', 'coming', 'sin', 'still', 'in', 'bethlehem']\"\n",
+      "['be', ['because', 'pause', 'gray', 'play', 'say', 'day', 'sheridan', 'man', 'high', 'sky', 'fame', 'name', 'bright', 'fight', 'away', 'bethlehem', 'lie', 'sleep', 'by', 'shineth', 'light', 'years', 'to-night', 'mary', 'above', 'keep', 'love', 'together', 'birth', 'king', 'earth', 'silently', 'given', 'hearts', 'heaven', 'coming', 'sin', 'still', 'in', 'bethlehem']]['pray']['in']['all']['earth']['birth']['heard']['day']['man']['can']['mind']['yet']['sight']['all']['flight']['fall']['end']['friend']['day']['lay']['all']['day']['way']['soul']['goal']['soul']['bear']['out']['about']['eyes']['skies']['eyes']['rise']['skies']['eyes']['rise']['eyes']['lies']['eyes']['men']['dead']\n",
+      "----- diversity: 1.0\n",
+      "----- Generating with seed: \"['because', 'pause', 'gray', 'play', 'say', 'day', 'sheridan', 'man', 'high', 'sky', 'fame', 'name', 'bright', 'fight', 'away', 'bethlehem', 'lie', 'sleep', 'by', 'shineth', 'light', 'years', 'to-night', 'mary', 'above', 'keep', 'love', 'together', 'birth', 'king', 'earth', 'silently', 'given', 'hearts', 'heaven', 'coming', 'sin', 'still', 'in', 'bethlehem']\"\n",
+      "['be', ['because', 'pause', 'gray', 'play', 'say', 'day', 'sheridan', 'man', 'high', 'sky', 'fame', 'name', 'bright', 'fight', 'away', 'bethlehem', 'lie', 'sleep', 'by', 'shineth', 'light', 'years', 'to-night', 'mary', 'above', 'keep', 'love', 'together', 'birth', 'king', 'earth', 'silently', 'given', 'hearts', 'heaven', 'coming', 'sin', 'still', 'in', 'bethlehem']]['sighed']['go']['home']['man']['measure']['fears']['pain']['roof']['swell']['pinion']['south']['smile']['wind']['calls']['grass']['walls']['rise']['round']['do']['sound']['world']['he']['thee']['flowers']['mill']['liberty']['between']['nose']['day']['clear']['sword']['word']['line']['fly']['high']['folks']['too']['knows']['hell']['ahead']\n",
+      "----- diversity: 1.2\n",
+      "----- Generating with seed: \"['because', 'pause', 'gray', 'play', 'say', 'day', 'sheridan', 'man', 'high', 'sky', 'fame', 'name', 'bright', 'fight', 'away', 'bethlehem', 'lie', 'sleep', 'by', 'shineth', 'light', 'years', 'to-night', 'mary', 'above', 'keep', 'love', 'together', 'birth', 'king', 'earth', 'silently', 'given', 'hearts', 'heaven', 'coming', 'sin', 'still', 'in', 'bethlehem']\"\n",
+      "['be', ['because', 'pause', 'gray', 'play', 'say', 'day', 'sheridan', 'man', 'high', 'sky', 'fame', 'name', 'bright', 'fight', 'away', 'bethlehem', 'lie', 'sleep', 'by', 'shineth', 'light', 'years', 'to-night', 'mary', 'above', 'keep', 'love', 'together', 'birth', 'king', 'earth', 'silently', 'given', 'hearts', 'heaven', 'coming', 'sin', 'still', 'in', 'bethlehem']]['apace']['remain']['night']['light']['meet']['klingle']['enough']['scorn']['prayer']['helpless']['bonnet']['late']['gate']['one']['deep'][\"'em\"]['song']['strong']['wrong']['universe']['give']['tears']['slow']['wait']['morning']['flame']['give']['upon']['dead.’']['so']['wave']['mind']['din']['game']['lace']['bread']['hope']['that']['top']['bed']\n"
+     ]
+    }
+   ],
+   "source": [
+    "start_index = random.randint(0, len(text) - maxlen - 1)\n",
+    "for diversity in [0.2, 0.5, 1.0, 1.2]:\n",
+    "    print('----- diversity:', diversity)\n",
+    "\n",
+    "    generated = ['be']\n",
+    "    sentence = text[start_index: start_index + maxlen]\n",
+    "    generated += [sentence]\n",
+    "    print('----- Generating with seed: \"{}\"'.format(sentence))\n",
+    "    sys.stdout.write(\"{}\".format(generated))\n",
+    "\n",
+    "    for i in range(40):\n",
+    "        x_pred = np.zeros((1, maxlen, len(chars)))\n",
+    "        for t, char in enumerate(sentence):\n",
+    "            x_pred[0, t, char_indices[char]] = 1.\n",
+    "\n",
+    "        preds = model.predict(x_pred, verbose=0)[0]\n",
+    "        next_index = sample(preds, diversity)\n",
+    "        next_char = indices_char[next_index]\n",
+    "\n",
+    "        generated += [next_char]\n",
+    "        sentence = sentence[1:] + [next_char]\n",
+    "\n",
+    "        sys.stdout.write('{}'.format([next_char]))\n",
+    "        sys.stdout.flush()\n",
+    "    print()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/rhyme_generator.py b/rhyme_generator.py
new file mode 100644
index 0000000..511f11f
--- /dev/null
+++ b/rhyme_generator.py
@@ -0,0 +1,105 @@
+from __future__ import print_function
+from keras.callbacks import LambdaCallback
+from keras.models import Sequential
+from keras.layers import Dense
+from keras.layers import LSTM
+from keras.optimizers import RMSprop
+from keras.utils.data_utils import get_file
+import numpy as np
+import random
+import sys
+import io
+
+
+path = 'rhymes.txt'
+with open(path, encoding='utf-8') as f:
+    text = f.read().lower()
+
+text = text.split()
+chars = sorted(list(set(text)))  # vocabulary of rhymes in the corpus
+
+
+# transform words into integer
+char_indices = dict((c, i) for i, c in enumerate(chars))
+indices_char = dict((i, c) for i, c in enumerate(chars))
+
+maxlen = 40
+step = 1
+sentences = []
+next_chars = []
+
+
+# creating input and output
+for i in range(0, len(text) - maxlen, step):
+    sentences.append(text[i: i + maxlen])
+    next_chars.append(text[i + maxlen])
+
+
+print('Vectorization...')
+x = np.zeros((len(sentences), maxlen, len(chars)), dtype=np.bool)
+y = np.zeros((len(sentences), len(chars)), dtype=np.bool)
+for i, sentence in enumerate(sentences):
+    for t, char in enumerate(sentence):
+        x[i, t, char_indices[char]] = 1
+    y[i, char_indices[next_chars[i]]] = 1
+
+
+# build the LSTM model
+print('Build model...')
+model = Sequential()
+model.add(LSTM(128, input_shape=(maxlen, len(chars))))
+model.add(Dense(len(chars), activation='softmax'))
+
+optimizer = RMSprop(lr=0.01)
+model.compile(loss='categorical_crossentropy', optimizer=optimizer)
+
+
+def sample(preds, temperature=1.0):
+    # Generates the next word
+    preds = np.asarray(preds).astype('float64')
+    preds = np.log(preds) / temperature
+    exp_preds = np.exp(preds)
+    preds = exp_preds / np.sum(exp_preds)
+    probas = np.random.multinomial(1, preds, 1)
+    return np.argmax(probas)
+
+
+def on_epoch_end(epoch, _):
+    # Function invoked at end of each epoch. Prints generated text.
+    if epoch % 5 == 0:
+        print()
+        print('----- Generating text after Epoch: {}'.format(epoch + 1))
+
+        start_index = random.randint(0, len(text) - maxlen - 1)
+        for diversity in [0.2, 0.5, 1.0, 1.2]:
+            print('----- diversity:', diversity)
+
+            generated = [rhyme]
+            sentence = text[start_index: start_index + maxlen]
+            generated += [sentence]
+            print('----- Generating from: "{}"'.format(sentence))
+            sys.stdout.write("{}".format(generated))
+
+            for i in range(40):
+                x_pred = np.zeros((1, maxlen, len(chars)))
+                for t, char in enumerate(sentence):
+                    x_pred[0, t, char_indices[char]] = 1.
+
+                preds = model.predict(x_pred, verbose=0)[0]
+                next_index = sample(preds, diversity)
+                next_char = indices_char[next_index]
+
+                generated += [next_char]
+                sentence = sentence[1:] + [next_char]
+
+                sys.stdout.write('{}'.format([next_char]))
+                sys.stdout.flush()
+            print()
+
+print_callback = LambdaCallback(on_epoch_end=on_epoch_end)
+
+model.fit(x, y,
+          batch_size=128,
+          epochs=20,
+callbacks=[print_callback])
+