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import gradio as gr
def respond(system_message, max_length, min_length, max_new_tokens, num_beams, temperature, top_p):
# Your response generation logic here
#response = correct_text(message, max_length, max_new_tokens, min_length, num_beams, temperature, top_p)
#yield response
#return f"System message: {system_message}, Max Length: {max_length}, Min Length: {min_length}, Max new tokens: {max_new_tokens}, Num Beams: {num_beams}, Temperature: {temperature}, Top-p: {top_p}"
return message
# Create the Gradio interface
with gr.Blocks() as demo:
gr.Markdown(
"""
# Grammar Correction App
""")
prompt_box = gr.Textbox(lines=2, placeholder="Enter your prompt here...")
output_box = gr.Textbox()
submitBtn = gr.Button("Submit")
with gr.Accordion("Generation Parameters:", open=False):
max_length = gr.Slider(minimum=1, maximum=256, value=80, step=1, label="Max Length")
min_length = gr.Slider(minimum=1, maximum=256, value=0, step=1, label="Min Length")
max_tokens = gr.Slider(minimum=0, maximum=256, value=0, step=1, label="Max new tokens")
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)")
#show_top_p = gr.Checkbox(value=True, label="Show Top-p Slider")
#top_p_slider = gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)", visible=True)
#show_top_p.change(lambda show: gr.update(visible=show), show_top_p, top_p_slider)
submitBtn.click(respond, [prompt_box, max_length, min_length, max_tokens, num_beams, temperature, top_p], output_box)
demo.launch()
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