app.py

from io import StringIO
from typing import Optional

import gradio as gr
import pandas as pd

from utils import pipeline
from utils.models import list_models


def read_data(filepath: str) -> Optional[pd.DataFrame]:
    if filepath.endswith('.xlsx'):
        df = pd.read_csv(filepath)
    elif filepath.endswith('.csv'):
        df = pd.read_csv(filepath)
    else:
        raise Exception('File type not supported')
    return df


def process(task_name: str,
            model_name: str,
            text: str,
            file=None,
            ):
    try:
        # load file
        if file:
            df = read_data(file.name)
        elif text:
            string_io = StringIO(text)
            df = pd.read_csv(string_io)
            assert len(df) >= 1, 'No input data'
        else:
            raise Exception('No input data')

        # process
        if task_name == 'Originality':
            df = pipeline.p0_originality(df, model_name)
        elif task_name == 'Flexibility':
            df = pipeline.p1_flexibility(df, model_name)
        else:
            raise Exception('Task not supported')

        # save
        path = 'output.csv'
        df.to_csv(path, index=False, encoding='utf-8-sig')
        return None, df.iloc[:10], path
    except Exception as e:
        return {'Error': e}, None, None


task_name_dropdown = gr.components.Dropdown(
    label='Task Name',
    value='Originality',
    choices=['Originality', 'Flexibility']
)

model_name_input = gr.components.Textbox(
    value='paraphrase-multilingual-MiniLM-L12-v2',
    lines=1,
    type='text'
)

model_name_dropdown = gr.components.Dropdown(
    label='Model Name',
    value=list_models[0],
    choices=list_models
)

text_input = gr.components.Textbox(
    value='id,prompt,response\n',
    lines=10,
    type='text'
)

text_output = gr.components.Textbox(
    label='Output',
    type='text'
)

dataframe_output = gr.components.Dataframe(
    label='DataFrame'
)

description = open('description.txt', 'r').read()

file_output = gr.components.File(label='Output File',
                                 file_count='single',
                                 file_types=['', '.', '.csv', '.xls', '.xlsx'])

app = gr.Interface(
    fn=process,
    inputs=[task_name_dropdown, model_name_dropdown, text_input, 'file'],
    outputs=[text_output, dataframe_output, file_output],
    description=description
)
app.launch()