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import streamlit as st
from transformers import pipeline
from ModelDriver import *
import numpy as np
# Add a title
st.title('GPT Detection Demo')
# Add 4 options for 4 models
ModelOption = st.sidebar.selectbox(
'Which Model do you want to use?',
('RobertaSentinel', 'RobertaClassifier'),
)
DatasetOption = st.sidebar.selectbox(
'Which Dataset do you want to use?',
('OpenGPT', 'CSAbstract'),
)
text = st.text_area('Enter text here', '')
if st.button('Generate'):
if ModelOption == 'RobertaSentinel':
if DatasetOption == 'OpenGPT':
result = RobertaSentinelOpenGPTInference(text)
elif DatasetOption == 'CSAbstract':
result = RobertaSentinelCSAbstractInference(text)
elif ModelOption == 'RobertaClassifier':
if DatasetOption == 'OpenGPT':
result = RobertaClassifierOpenGPTInference(text)
elif DatasetOption == 'CSAbstract':
result = RobertaClassifierCSAbstractInference(text)
Prediction = "Human Written" if not np.argmax(result) else "Machine Generated"
print(f"Prediction: {Prediction} ")
print(f"Probabilty:", max(result))
st.write(result)
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