app.py

import gradio as gr
from transformers import GPT2LMHeadModel, GPT2Tokenizer

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

def generate_opposing_article(input_text, max_length=100):
    # Encode input text
    input_ids = tokenizer.encode(input_text, return_tensors="pt")
    
    # Generate text with an opposing viewpoint
    output = model.generate(
        input_ids=input_ids,
        max_length=max_length,
        num_return_sequences=1,
        pad_token_id=tokenizer.eos_token_id,
        temperature=0.7,
        top_k=50,
        top_p=0.92,
        repetition_penalty=1.0,
        do_sample=True
    )
    
    # Decode generated text
    generated_text = tokenizer.decode(output[0], skip_special_tokens=True)
    
    return generated_text

# Create Gradio interface
inputs = gr.inputs.Textbox(lines=5, label="Enter your statement:")
outputs = gr.outputs.Textbox(label="Opposing Article:")

gr.Interface(
    fn=generate_opposing_article,
    inputs=inputs,
    outputs=outputs,
    title="Opposing Article Generator",
    description="Enter a statement, and this tool will generate an article with an opposing viewpoint.",
).launch()