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import streamlit as st
import nltk
import pandas as pd
from py_thesaurus import Thesaurus
import random
# Cache the NLTK corpora and functions for better performance
@st.cache
def load_nltk_data():
nltk.download('book')
from nltk.book import text1
return text1
# Function to generate random text from NLTK corpora
def generate_text():
text = load_nltk_data()
words = [word.lower() for word in text if word.isalpha()]
random_text = ' '.join(nltk.choice(words) for _ in range(10))
return random_text
# Function to replace a random word with its synonym
def replace_with_synonym(sentence):
words = sentence.split()
index = random.randint(0, len(words) - 1)
word = words[index]
synonyms = Thesaurus(word).get_synonym()
if synonyms:
replacement = random.choice(synonyms)
words[index] = replacement
return ' '.join(words)
st.title('Joke Parts Voting Game')
st.write('Upvote or downvote the funny joke parts generated below!')
# Create thumbs up and thumbs down buttons
thumbs_up = st.button('👍')
thumbs_down = st.button('👎')
# Initialize upvote and downvote counts
upvotes = 0
downvotes = 0
# Increment upvote or downvote count when corresponding button is clicked
if thumbs_up:
upvotes += 1
elif thumbs_down:
downvotes += 1
# Display upvote and downvote count
st.write(f'👍 {upvotes} | 👎 {downvotes}')
# Create scoreboard using pandas and display it
scoreboard = pd.DataFrame({'Upvotes': [upvotes], 'Downvotes': [downvotes]})
st.write(scoreboard)
# Save scoreboard to output CSV file
scoreboard.to_csv('output.csv', index=False)
# Generate a random text and replace a word with a synonym
original_text = generate_text()
modified_text = replace_with_synonym(original_text)
# Display the modified text
st.write(f'🤣 {modified_text}')
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