app.py

import gradio as gr
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer

model = AutoModelForSeq2SeqLM.from_pretrained("vennify/t5-base-grammar-correction")
tokenizer = AutoTokenizer.from_pretrained("vennify/t5-base-grammar-correction")

def correct_text(text, max_length, max_new_tokens, min_length, num_beams, temperature, top_p):
    inputs = tokenizer.encode("grammar: " + text, return_tensors="pt")
    generate_kwargs = {
        "inputs": inputs,
        "max_length": max_length,
        "min_length": min_length,
        "num_beams": num_beams,
        "temperature": temperature,
        "top_p": top_p,
        "early_stopping": True
    }

    if max_new_tokens > 0:
        generate_kwargs["max_new_tokens"] = max_new_tokens

    outputs = model.generate(**generate_kwargs)
    corrected_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return corrected_text

def respond(message, history, max_length, min_length, max_new_tokens, num_beams, temperature, top_p):
    response = correct_text(message, max_length, max_new_tokens, min_length, num_beams, temperature, top_p)
    yield response

css = """
#interface-container {  
    padding: 20px; 
    border-radius: 10px; 
    box-shadow: 0 4px 15px rgba(0, 0, 0, 0.1); 
    max-width: 800px;
    margin: auto;
    font-family: 'Arial', sans-serif;
}
#input-container { 
    margin-bottom: 20px; 
}
#output-container { 
    margin-top: 20px; 
    font-family: Arial, sans-serif; 
    font-size: 16px; 
    color: #333; 
    padding: 10px; 
    border-radius: 5px; 
    border: 1px solid #ddd;
}
.gr-button { 
    background-color: #007bff; 
    color: white; 
    border: none; 
    padding: 10px 20px; 
    border-radius: 5px; 
    cursor: pointer; 
    font-size: 16px; 
}
.gr-button:hover { 
    background-color: #0056b3; 
}
.gr-slider .gr-slider-track { 
    background-color: #007bff; 
}
.gr-slider .gr-slider-thumb { 
    background-color: #0056b3; 
}
.gr-textbox input { 
    border: 1px solid #ddd; 
    border-radius: 5px; 
    padding: 10px; 
}
.gr-textbox textarea { 
    border: 1px solid #ddd; 
    border-radius: 5px; 
    padding: 10px; 
}
"""

with gr.Blocks(css=css) as demo:
    gr.HTML("<h1 style='text-align: center; color: #007bff;'>Grammar Correction Tool</h1>")
    
    with gr.Row(elem_id="interface-container"):
        with gr.Column():
            user_input = gr.Textbox(lines=2, placeholder="Enter a sentence with grammatical errors...", label="Input Text", elem_id="input-container")
            max_length = gr.Slider(minimum=1, maximum=256, value=100, step=1, label="Max Length")
            min_length = gr.Slider(minimum=1, maximum=256, value=0, step=1, label="Min Length")
            max_new_tokens = gr.Slider(minimum=0, maximum=256, value=0, step=1, label="Max New Tokens (optional)")
            num_beams = gr.Slider(minimum=1, maximum=10, value=5, step=1, label="Num Beams")
            temperature = gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature")
            top_p = gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)")
            
            btn = gr.Button("Correct Grammar")
        
        with gr.Column():
            corrected_output = gr.Textbox(lines=2, placeholder="The corrected sentence will appear here...", label="Corrected Text", elem_id="output-container")

    btn.click(
        fn=correct_text, 
        inputs=[user_input, max_length, max_new_tokens, min_length, num_beams, temperature, top_p],
        outputs=corrected_output
    )

if __name__ == "__main__":
    demo.launch()