Spaces:
Runtime error
Runtime error
File size: 11,610 Bytes
4ba4a77 08a437b 4ba4a77 08a437b 4ba4a77 08a437b 4ba4a77 08a437b 4ba4a77 3c8872c 1ab0a91 08a437b 4ba4a77 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 |
import gradio as gr
import requests
import random
import time
import pandas as pd
from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
from game1 import read1, func1, interpre1, read1_written, func1_written, change_lang
from game2 import func2
from game3 import func3
def ret_en():
return 'en'
def ret_nl():
return 'nl'
def reset_scores():
data = pd.DataFrame(
{
"Role": ["AI 🤖", "HUMAN 👨👩"],
"Scores": [0, 0],
}
)
tot_scores = ''' ### <p style="text-align: center;"> Machine   ''' + str(int(0)) + '''   VS   ''' + str(int(0)) + '''   Human </p>'''
# scroe_human = ''' # Human: ''' + str(int(0))
# scroe_robot = ''' # Robot: ''' + str(int(0))
# tooltip=["Role", "Scores"],
return 0, 0, tot_scores, gr.BarPlot.update(
data,
x="Role",
y="Scores",
color="Role",
vertical=False,
y_lim=[0,10],
color_legend_position='none',
height=250,
width=500,
show_label=False,
container=False,
)
with gr.Blocks(theme=gr.themes.Default(text_size=gr.themes.sizes.text_md)) as demo:
pre_load_1 = pipeline("sentiment-analysis", model="nlptown/bert-base-multilingual-uncased-sentiment")
with gr.Row():
num1 = gr.Number(value=0, container=False, show_label=False, visible=False)
num2 = gr.Number(value=0, container=False, show_label=False, visible=False)
placeholder = gr.Markdown(
''' ## Welcome to the Language Model Explanation Challenge!
Language Models (LMs) are powerful AI tools to understand and generate human language.<br />
However, they sometimes make mistakes... and it's hard to know why!<br /><br />
Are *humans* or *machines* better at understanding language?<br />
→ Play a game against AI to find out!<br /><br />
Does AI think like you or not at all?<br />
→ Check out the color highlighting to see which parts of the sentence are more important for the machine.<br /><br />
Can you outsmart the AI?<br />
→ Try to write a text that will trick it into the wrong decision<br /><br />
Choose one of the three tasks below ... and start to play!
'''
#* **Like or Dislike** provides a movie/food/book review. You (and AI) are required to guess its score.
#The one with the correct or close answer win the score.
#* **Human or Machine** provides a paragraph. You (and AI) need to judge if it is written by humans or machines.
#The one with the correct or close answer win the score.
#* **Man or Woman** allows you to write a text.
#If you could successfully trick the AI into guessing the wrong gender, you get the score.
)
with gr.Column():
# plot = gr.BarPlot(height=120, width=300, container=False)
data = pd.DataFrame(
{
"Role": ["AI 🤖", "HUMAN 👨👩"],
"Scores": [0, 0],
}
)
plot = gr.BarPlot(
data,
x="Role",
y="Scores",
color="Role",
vertical=False,
y_lim=[0,10],
color_legend_position='none',
height=250,
width=500,
show_label=False,
container=False,
)
# tooltip=["Role", "Scores"],
# button_reset = gr.Button("Reset Scores")
gr.Markdown(
''' ## Today's Scores
'''
)
tot_scores = gr.Markdown(
''' ### <p style="text-align: center;"> Machine   ''' + str(int(0)) + '''   VS   ''' + str(int(0)) + '''   Human </p>'''
)
# score_robot = gr.Markdown(
# ''' ## Robot: ''' + str(int(num2.value))
# )
# score_human = gr.Markdown(
# ''' ## Human: ''' + str(int(num1.value))
# )
# button_reset.click(reset_scores, outputs=[num1, num2, tot_scores, plot])
with gr.Tab("Like or Dislike"):
text_en = gr.Textbox(label="", value="en", visible=False)
text_nl = gr.Textbox(label="", value="nl", visible=False)
lang_selected = gr.Textbox(label="", value="", visible=False)
num_selected = gr.Number(value=0, container=False, show_label=False, visible=False)
with gr.Row():
with gr.Column():
sample_button_en = gr.Button("Click to get a review in English.", size='sm')
gr.Markdown(''' <p style="text-align: center;"> or </p> ''')
# gr.Markdown(''' <h2 style="text-align: center;"> or </h2> ''')
sample_button_nl = gr.Button("Click to get a review in Dutch.", size='sm')
# h1 = gr.HighlightedText(label="Review/Recensie:", interactive=True, show_legend=True, combine_adjacent=False, color_map={"+": "red", "-": "green"})
input_text = gr.Textbox(label="Review/Recensie:", value="HELLO! Hallo!", visible=False, container=False)
interpretation1 = gr.components.Interpretation(input_text)
# image_1_1 = gr.Image('icon_user.png', height=80, width=80, min_width=80, show_label=False, show_share_button=False, interactive=False)
slider_1_1 = gr.Slider(label="Human: Dislike ——> Like", container=True, min_width=200, height=80, show_label=True, interactive=True)
# checkbox_1 = gr.CheckboxGroup(label="Which words are the guesses based on?", interactive=True)
user_important = gr.Textbox(label="Which words are the guesses based on?")
gr.Markdown(
''' ## Like or Dislike
You're given a short review of a movie, book or restaurant.
The goal of this game is to guess how *positive* the review is, from 0 (=extremely bad) to 100 (=fantastic).
* Step 1. Get an English or Dutch review and guess the corresponding score.
* Step 2. Check the score guessed by AI. Who gets the most correct answer wins.
* Step 3. Check the word highlighting to understand how AI made its decision.
'''
)
# gr.Markdown(
# ''' ## Like or Dislike
# In this game, you will fight against AI in guessing the scores of the reviews:
# * Step 1. Get an English/Dutch review and guess the corresponding score.
# * Step 2. Check the score guessed by AI. The one with the correct/close answer wins.
# * Step 3. (See how AI made the decision.)
# Simple enough? Let's have fun!
# '''
# )
with gr.Row():
with gr.Column():
chat_button_1 = gr.Button("Click to see AI's answer.", size='sm')
slider_1_2 = gr.Slider(label="AI: Dislike ——> Like", container=True, min_width=200, height=80, show_label=True, interactive=True)
interpre_button = gr.Button("See how AI gets the answer.", size='sm')
# h2 = gr.HighlightedText(label="Review/Recensie:", interactive=True, show_legend=True, combine_adjacent=False, color_map={"+": "red", "-": "green"})
placeholder_text = gr.Textbox(label="Review/Recensie:", value="HELLO! Hallo!", visible=False)
interpretation2 = gr.components.Interpretation(placeholder_text)
# image_1_2 = gr.Image('icon_robot.png', height=80, width=80, min_width=80, show_label=False, show_share_button=False, interactive=False)
chatbot1 = gr.Chatbot(height=200, min_width=50, container=False) # height=300
####################################################################################################
# gr.Markdown(''' --- ''')
gr.Markdown(''' *** ''')
gr.Markdown(
''' # Now try your own reviews!
'''
)
with gr.Row():
with gr.Column():
text_written = gr.Textbox(label="Review/Recensie: ", value="HELLO! Hallo!", visible=True)
# image_1_3 = gr.Image('icon_user.png', height=80, width=80, min_width=80, show_label=False, show_share_button=False, interactive=False)
slider_1_3 = gr.Slider(label="Human: Dislike ——> Like", container=True, min_width=200, height=80, show_label=True, interactive=True)
lang_written = gr.Radio(["English", "Dutch"], label="Language:", info="In which language is the review written?")
chat_button_2 = gr.Button("Click to see AI's answer.", size='sm')
placeholder_written_text = gr.Textbox(label="Review/Recensie: ", value="HELLO! Hallo!", visible=False)
interpretation4 = gr.components.Interpretation(placeholder_written_text)
slider_1_4 = gr.Slider(label="AI: Dislike ——> Like", container=True, min_width=200, height=80, show_label=True, interactive=True)
chatbot2 = gr.Chatbot(height=350, min_width=50, container=False) # height=300
# sample_button_en.click(read1, inputs=[text_en], outputs=[checkbox_1, interpretation1, lang_selected, num_selected, interpretation2, slider_1_1, slider_1_2, chatbot1])
# sample_button_nl.click(read1, inputs=[text_nl], outputs=[checkbox_1, interpretation1, lang_selected, num_selected, interpretation2, slider_1_1, slider_1_2, chatbot1])
# chat_button_1.click(func1, inputs=[lang_selected, num_selected, slider_1_1, num1, num2, checkbox_1], outputs=[slider_1_2, chatbot1, num1, num2, tot_scores, plot])
# interpre_button.click(interpre1, inputs=[lang_selected, num_selected], outputs=[interpretation2])
sample_button_en.click(read1, inputs=[text_en], outputs=[interpretation1, lang_selected, num_selected, interpretation2, slider_1_1, slider_1_2, chatbot1, user_important])
sample_button_nl.click(read1, inputs=[text_nl], outputs=[interpretation1, lang_selected, num_selected, interpretation2, slider_1_1, slider_1_2, chatbot1, user_important])
chat_button_1.click(func1, inputs=[lang_selected, num_selected, slider_1_1, num1, num2, user_important], outputs=[slider_1_2, chatbot1, num1, num2, tot_scores, plot])
interpre_button.click(interpre1, inputs=[lang_selected, num_selected], outputs=[interpretation2])
# sample_button_en_written.click(read1_written, inputs=[text_en], outputs=[text_written])
# sample_button_nl_written.click(read1_written, inputs=[text_nl], outputs=[text_written])
# lang_written.change(fn=change_lang, inputs=radio, outputs=lang_written_text)
chat_button_2.click(func1_written, inputs=[text_written, slider_1_3, lang_written], outputs=[interpretation4, slider_1_4, chatbot2])
with gr.Tab("Human or Machine"):
with gr.Row():
text_input_2 = gr.Textbox()
text_output_2 = gr.Label()
text_button_2 = gr.Button("Check")
with gr.Tab("Man or Woman"):
with gr.Row():
text_input_3 = gr.Textbox()
text_output_3 = gr.Label()
text_button_3 = gr.Button("Guess")
if __name__ == "__main__":
demo.launch()
|