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ugik
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chat-bot cleanup
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3 files changed

+57
-80
lines changed

‎Tensorflow chat-bot model.ipynb‎

Lines changed: 12 additions & 21 deletions
Original file line numberDiff line numberDiff line change
@@ -119,17 +119,8 @@
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" output_row = list(output_empty)\n",
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" output_row[classes.index(doc[1])] = 1\n",
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"\n",
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" training.append([bag, output_row])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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" training.append([bag, output_row])\n",
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"\n",
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"# shuffle our features and turn into np.array\n",
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"random.shuffle(training)\n",
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"training = np.array(training)\n",
@@ -141,7 +132,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"execution_count": 5,
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"metadata": {
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"collapsed": false,
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"scrolled": true
@@ -151,10 +142,10 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Training Step: 3999 | total loss: \u001b[1m\u001b[32m0.18876\u001b[0m\u001b[0m | time: 0.008s\n",
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"| Adam | epoch: 1000 | loss: 0.18876 - acc: 0.9896 -- iter: 24/27\n",
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"Training Step: 4000 | total loss: \u001b[1m\u001b[32m0.17795\u001b[0m\u001b[0m | time: 0.010s\n",
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"| Adam | epoch: 1000 | loss: 0.17795 - acc: 0.9907 -- iter: 27/27\n",
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"Training Step: 3999 | total loss: \u001b[1m\u001b[32m0.79875\u001b[0m\u001b[0m | time: 0.009s\n",
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"| Adam | epoch: 1000 | loss: 0.79875 - acc: 0.9100 -- iter: 24/27\n",
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"Training Step: 4000 | total loss: \u001b[1m\u001b[32m0.72213\u001b[0m\u001b[0m | time: 0.012s\n",
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"| Adam | epoch: 1000 | loss: 0.72213 - acc: 0.9190 -- iter: 27/27\n",
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"--\n",
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"INFO:tensorflow:/home/gk/gensim/notebooks/model.tflearn is not in all_model_checkpoint_paths. Manually adding it.\n"
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]
@@ -179,7 +170,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"execution_count": 6,
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"metadata": {
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"collapsed": true
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},
@@ -210,7 +201,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {
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"collapsed": false
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},
@@ -233,7 +224,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"execution_count": 8,
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"metadata": {
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"collapsed": false
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},
@@ -242,7 +233,7 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[[0.00010235147055936977, 7.91284620049737e-08, 0.04525074362754822, 3.261959591327468e-07, 0.9264171123504639, 1.7087060655285313e-08, 0.00015298598736990243, 0.00015127936785575002, 0.02792503498494625]]\n"
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"[[0.0006383281433954835, 1.1489937890019064e-08, 0.005845240317285061, 2.1674446543329395e-05, 0.9596946239471436, 1.4315231666728323e-08, 0.0018385507864877582, 1.7271321439693565e-06, 0.031959764659404755]]\n"
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]
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}
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],
@@ -252,7 +243,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"execution_count": 9,
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"metadata": {
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"collapsed": false
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},

‎Tensorflow chat-bot response.ipynb‎

Lines changed: 45 additions & 59 deletions
Original file line numberDiff line numberDiff line change
@@ -42,17 +42,8 @@
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"words = data['words']\n",
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"classes = data['classes']\n",
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"train_x = data['train_x']\n",
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"train_y = data['train_y']"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"train_y = data['train_y']\n",
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"\n",
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"# import our chat-bot intents file\n",
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"import json\n",
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"with open('intents.json') as json_data:\n",
@@ -61,7 +52,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"execution_count": 3,
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"metadata": {
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"collapsed": false,
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"scrolled": true
@@ -81,7 +72,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"execution_count": 4,
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"metadata": {
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"collapsed": true
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},
@@ -112,7 +103,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"execution_count": 5,
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"metadata": {
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"collapsed": false
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},
@@ -135,7 +126,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {
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"collapsed": false
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},
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"# create a data structure to hold user context\n",
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"context = {}"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"execution_count": 7,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"# create a data structure to hold user context\n",
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"context = {}\n",
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"\n",
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"ERROR_THRESHOLD = 0.25\n",
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"def classify(sentence):\n",
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" # generate probabilities from the model\n",
@@ -205,18 +187,18 @@
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"execution_count": 8,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[('opentoday', 0.9264171123504639)]"
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"[('opentoday', 0.9596946239471436)]"
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]
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},
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"execution_count": 10,
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"execution_count": 8,
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"metadata": {},
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"output_type": "execute_result"
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}
@@ -227,7 +209,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"metadata": {
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},
@@ -236,7 +218,7 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Our hours are 9am-9pm every day\n"
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"We're open every day from 9am-9pm\n"
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]
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}
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],
@@ -246,7 +228,7 @@
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},
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{
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"cell_type": "code",
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},
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"We accept most major credit cards\n"
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"We accept VISA, Mastercard and AMEX\n"
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]
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}
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],
@@ -265,7 +247,7 @@
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},
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{
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"cell_type": "code",
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},
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"cell_type": "code",
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"execution_count": 12,
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"metadata": {
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"collapsed": false
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},
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"{}"
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]
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},
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"execution_count": 12,
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"metadata": {},
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"output_type": "execute_result"
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}
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},
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{
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"cell_type": "code",
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"metadata": {
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},
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},
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{
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"cell_type": "code",
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"execution_count": 21,
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"metadata": {
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"collapsed": false
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},
@@ -336,7 +318,7 @@
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"{'123': 'rentalday'}"
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]
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},
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"execution_count": 16,
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"execution_count": 21,
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"metadata": {},
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"output_type": "execute_result"
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}
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},
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{
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"cell_type": "code",
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"execution_count": 22,
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"metadata": {
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},
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"tag: today\n",
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"For rentals today please call 1-800-MYMOPED\n"
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]
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}
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],
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"source": [
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"response('today', show_details=True)"
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"response('today')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[('today', 0.5322513580322266), ('opentoday', 0.2611265480518341)]"
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"[('today', 0.5943121910095215)]"
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]
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},
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"execution_count": 18,
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"execution_count": 16,
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"metadata": {},
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"output_type": "execute_result"
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}
@@ -390,7 +371,7 @@
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},
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{
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"cell_type": "code",
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},
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Hello, thanks for visiting\n"
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"context: \n",
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"tag: greeting\n",
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"Hi there, how can I help?\n"
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]
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}
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],
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"source": [
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"# clear context\n",
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"response(\"Hi there!\")"
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"response(\"Hi there!\", show_details=True)"
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]
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},
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"cell_type": "code",
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"tag: opentoday\n",
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"Our hours are 9am-9pm every day\n"
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]
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"data": {
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"text/plain": [
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"[('today', 0.5943121910095215)]"
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]
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},
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"execution_count": 24,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"response('today', show_details=True)"
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"response('today')\n",
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"classify('today')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 21,
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"execution_count": 25,
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"metadata": {
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"collapsed": false
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},

‎training_data‎

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