Spaces:
Runtime error
Runtime error
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 π€", "HUMAN π¨π©"], | |
"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 π€", "HUMAN π¨π©"], | |
"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 ββ> 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 ββ> 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 ββ> 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 ββ> 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() | |