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"""
The Streamlit app for the project demo.
In the demo, the user can write a prompt
 and the model will generate a response using the grouped sampling algorithm.
"""

import streamlit as st

from hanlde_form_submit import on_form_submit
from on_server_start import main as on_server_start_main


on_server_start_main()


st.title("Grouped Sampling Demo")


with st.form("request_form"):
    selected_model_name: str = st.text_input(
        label="Model name",
        value="gpt2",
        help=f"The name of the model to use."
             f"Supported models are all the models in:"
             f" https://huggingface.co/models?pipeline_tag=text-generation&library=pytorch",
    )

    output_length: int = st.number_input(
        label="Number of word pieces in the generated text, 1-4096 (default: 100)",
        min_value=1,
        max_value=4096,
        value=100,
        help="The length of the output text in tokens (word pieces)."
    )

    submitted_prompt: str = st.text_area(
        label="Input for the model, It is highly recommended to write an English prompt.",
        help="Enter the prompt for the model. The model will generate a response based on this prompt.",
        max_chars=16384,
    )

    submitted: bool = st.form_submit_button(
        label="Generate",
        help="Generate the output text.",
        disabled=False,
    )

    if submitted:
        try:
            output = on_form_submit(selected_model_name, output_length, submitted_prompt)
            st.write(f"Generated text: {output}")
        except ValueError as e:
            st.error(e)