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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_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 str(df), path
except Exception as e:
return {'Error': e}, None
instructions = 'Please upload a file or paste the text below. '
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'
)
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, file_output],
description=description
)
app.launch()
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