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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_excel(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,
pooling: str,
text: str,
file=None,
) -> (None, pd.DataFrame, str):
# 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, pooling)
elif task_name == 'Flexibility':
df = pipeline.p1_flexibility(df, model_name, pooling)
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
# input
task_name_dropdown = gr.components.Dropdown(
label='Task Name',
value='Originality',
choices=['Originality', 'Flexibility']
)
model_name_dropdown = gr.components.Dropdown(
label='Model Name',
value=list_models[0],
choices=list_models
)
pooling_dropdown = gr.components.Dropdown(
label='Pooling',
value='mean',
choices=['mean', 'cls']
)
text_input = gr.components.Textbox(
value=open('data/example_xlm.csv', 'r').read(),
lines=10,
)
file_input = gr.components.File(label='Input File', file_types=['.csv', '.xlsx'])
# output
text_output = gr.components.Textbox(label='Output')
dataframe_output = gr.components.Dataframe(label='DataFrame')
file_output = gr.components.File(label='Output File', file_types=['.csv', '.xlsx'])
app = gr.Interface(
fn=process,
inputs=[task_name_dropdown, model_name_dropdown, pooling_dropdown, text_input, file_input],
outputs=[text_output, dataframe_output, file_output],
description=open('data/description.txt', 'r').read(),
title='TransDis-CreativityAutoAssessment',
)
app.launch()
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