import streamlit as st
import pandas as pd
from py_thesaurus import Thesaurus
import random
from transformers import GPT2LMHeadModel, GPT2Tokenizer

# Load GPT-2 model and tokenizer
model = GPT2LMHeadModel.from_pretrained("gpt2")
tokenizer = GPT2Tokenizer.from_pretrained("gpt2")

# Function to generate random text using GPT-2
def generate_text(prompt):
    inputs = tokenizer.encode(prompt, return_tensors="pt")
    outputs = model.generate(inputs, max_length=50, num_return_sequences=1)
    return tokenizer.decode(outputs[0])

# 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 using GPT-2
prompt = "Tell me a joke:"
original_text = generate_text(prompt)
modified_text = replace_with_synonym(original_text)

# Display the modified text
st.write(f'🤣 {modified_text}')