464 lines
11 KiB
Plaintext
464 lines
11 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# User Interface Configuration and Information\n",
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"We want to create a small user interface for our prototype in emoji prediction"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Needed\n",
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"We want to define needed components for this UI"
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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": 1,
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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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"import random\n",
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"import ipywidgets as widgets\n",
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"from IPython.display import display, clear_output"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Trigger refresh of prediction\n",
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"each action of typing and sending should yield a new updated prediction for best fitting emojis"
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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": 2,
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"Using TensorFlow backend.\n"
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]
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},
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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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"[nltk_data] Downloading package punkt to /Users/Carsten/nltk_data...\n",
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"[nltk_data] Package punkt is already up-to-date!\n",
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"[nltk_data] Downloading package averaged_perceptron_tagger to\n",
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"[nltk_data] /Users/Carsten/nltk_data...\n",
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"[nltk_data] Package averaged_perceptron_tagger is already up-to-\n",
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"[nltk_data] date!\n",
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"[nltk_data] Downloading package wordnet to /Users/Carsten/nltk_data...\n",
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"[nltk_data] Package wordnet is already up-to-date!\n"
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]
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}
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],
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"source": [
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"import sys\n",
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"sys.path.append(\"..\")\n",
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"\n",
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"import simple_approach.simple_twitter_learning as stl\n",
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"clf = stl.pipeline_manager.load_pipeline_from_files( '../simple_approach/custom_classifier', ['keras_model'], ['vectorizer', 'keras_model'])\n",
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"\n",
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"import Tools.Emoji_Distance as ed"
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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": null,
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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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},
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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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"outputs": [],
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"source": [
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"top_emojis = ['😂',\n",
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" '😭',\n",
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" '😍',\n",
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" '😩',\n",
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" '😊',\n",
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" '😘',\n",
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" '🙏',\n",
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" '🙌',\n",
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" '😉',\n",
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" '😁',\n",
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" '😅',\n",
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" '😎',\n",
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" '😢',\n",
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" '😒',\n",
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" '😏',\n",
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" '😌',\n",
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" '😔',\n",
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" '😋',\n",
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" '😀',\n",
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" '😤']\n",
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"predictions = [\"🤐\",\"🤑\",\"🤒\",\"🤓\",\"🤔\",\"🤕\",\"🤗\",\"🤘\"]\n",
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"\n",
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"def trigger_new_prediction(all_chat, current_message):\n",
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" global predictions\n",
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" #random.shuffle(predictions)\n",
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" sent = clf.predict([current_message])\n",
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" p = ed.sentiment_vector_to_emoji(sent,n_results = 8, custom_target_emojis=top_emojis)\n",
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" predictions = p\n",
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" update_descriptions()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### User Output\n",
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"the wiritten text as an overview or list of text"
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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": 4,
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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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"all_text = \"no text yet \\n\"\n",
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"\n",
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"out = widgets.Output(layout = widgets.Layout(max_height = \"500px\"))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### User Input\n",
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"the user has to interact with our UI so hee needs:"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### Text Input field\n",
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"a simple line for text input on the bottom of UI"
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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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"text_input = widgets.Text()\n",
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"\n",
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"def submit_new_message(p):\n",
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" global all_text\n",
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" bar = \"----------- \\n\"\n",
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" time = \"12:00 \\n\"\n",
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" msg = text_input.value +\"\\n\"\n",
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" new_message = bar + time + msg\n",
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" all_text += new_message \n",
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" \n",
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" with out:\n",
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" clear_output()\n",
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" print(all_text)\n",
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" \n",
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" trigger_new_prediction(all_text, text_input.value)\n",
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" update_descriptions()\n",
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" text_input.description = \"\"\n",
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" \n",
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"text_input.on_submit(submit_new_message)\n",
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"\n",
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"\n",
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"#TODO\n",
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"text_input.observe(lambda b: trigger_new_prediction(None, text_input.value))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### A sent button to enter yout typed in message\n",
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"alternatively it should be also possible to simply type enter"
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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": 6,
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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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"sent_button = widgets.Button(description = \"Sent\")\n",
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"\n",
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"sent_button.on_click(submit_new_message)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### A list of buttons for selecting predicted emojis\n",
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"a set of fixed size of buttons with a dynamic changeable labeling replaced by the unicode emoji"
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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": 7,
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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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"p0_button = widgets.Button(description = \"p0\")\n",
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"\n",
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"def on_p0_button_click(p):\n",
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" update_descriptions() \n",
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" #with out:\n",
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" text_input.value += \" \"+predictions[0]\n",
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"\n",
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"p0_button.on_click(on_p0_button_click)"
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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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"p1_button = widgets.Button(description = \"p1\")\n",
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"\n",
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"def on_p1_button_click(p):\n",
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" update_descriptions()\n",
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" with out:\n",
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" text_input.value += \" \"+predictions[1]\n",
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"\n",
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"p1_button.on_click(on_p1_button_click)"
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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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"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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"p2_button = widgets.Button(description = \"p2\")\n",
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"\n",
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"def on_p2_button_click(p):\n",
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" update_descriptions()\n",
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" with out:\n",
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" text_input.value += \" \"+predictions[2]\n",
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"\n",
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"p2_button.on_click(on_p2_button_click)"
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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": 10,
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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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"p3_button = widgets.Button(description = \"p3\")\n",
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"\n",
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"def on_p3_button_click(p):\n",
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" update_descriptions()\n",
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" with out:\n",
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" text_input.value += \" \"+predictions[3]\n",
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"\n",
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"p3_button.on_click(on_p3_button_click)"
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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": 11,
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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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"p4_button = widgets.Button(description = \"p4\")\n",
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"\n",
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"def on_p4_button_click(p):\n",
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" update_descriptions()\n",
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" with out:\n",
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" text_input.value += \" \"+predictions[4]\n",
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"\n",
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"p4_button.on_click(on_p4_button_click)"
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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": 12,
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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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"p5_button = widgets.Button(description = \"p5\")\n",
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"\n",
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"def on_p5_button_click(p):\n",
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" update_descriptions()\n",
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" with out:\n",
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" text_input.value += \" \"+predictions[5]\n",
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"\n",
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"p5_button.on_click(on_p5_button_click)"
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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": 13,
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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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"p6_button = widgets.Button(description = \"p6\")\n",
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"\n",
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"def on_p6_button_click(p):\n",
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" update_descriptions()\n",
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" with out:\n",
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" text_input.value += \" \"+predictions[6]\n",
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"\n",
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"p6_button.on_click(on_p6_button_click)"
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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": 14,
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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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"p7_button = widgets.Button(description = \"p7\")\n",
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"\n",
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"def on_p7_button_click(p):\n",
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" update_descriptions()\n",
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" with out:\n",
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" text_input.value += \" \"+predictions[7]\n",
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"\n",
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"p7_button.on_click(on_p7_button_click)"
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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": 15,
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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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"def update_descriptions():\n",
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" global predictions\n",
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" p0_button.description = predictions[0]\n",
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" p1_button.description = predictions[1]\n",
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" p2_button.description = predictions[2]\n",
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" p3_button.description = predictions[3]\n",
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" p4_button.description = predictions[4]\n",
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" p5_button.description = predictions[5]\n",
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" p6_button.description = predictions[6]\n",
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" p7_button.description = predictions[7]"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Additional\n",
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"Developer Information\n",
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"#### Output of in and out commands\n",
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"#### Prob distribution or whole list of sorted emojis\n",
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"#### configuration information"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Prototype UI"
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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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"outputs": [
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "29e1cbab23c841a8b201b95c3d75da01",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
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"A Jupyter Widget"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"text_output = widgets.VBox([out])\n",
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"all_prediction_buttons = widgets.HBox([p0_button,p1_button,p2_button,p3_button,p4_button,p5_button,p6_button,p7_button])\n",
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"user_input = widgets.HBox([text_input,sent_button])\n",
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"total_layout = widgets.VBox([text_output,all_prediction_buttons,user_input],layout = widgets.Layout(max_width = \"450px\"))\n",
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"display(total_layout)"
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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": null,
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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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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
|
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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