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import pandas as pd
import streamlit as st
from transformers import pipeline
import os
# Load models
model1 = pipeline("text-classification", model="vectara/hallucination_evaluation_model")
model2 = pipeline("text-classification", model="sileod/deberta-v3-base-tasksource-nli")
# Predefined examples
examples = {
'good': {
'question': "What causes rainbows to appear in the sky?",
'explanation': "Rainbows appear when sunlight is refracted, dispersed, and reflected inside water droplets in the atmosphere, resulting in a spectrum of light appearing in the sky.",
'ground_truth': "Correct"
},
'bad': {
'question': "What causes rainbows to appear in the sky?",
'explanation': "Rainbows happen because light in the sky gets mixed up and sometimes shows colors when it's raining or when there is water around.",
'ground_truth': "Incorrect"
}
}
# Function to evaluate explanations using the two models
def evaluate_explanation(question, explanation):
results1 = model1(explanation)
results2 = model2(explanation)
return results1, results2
# Function to compare vectors (simple difference in scores as example)
def compare_vectors(v1, v2):
diff = abs(v1[0]['score'] - v2[0]['score'])
return diff
# Title of the application
st.title('Dual Model Evaluation of Explanations')
# Check for password before allowing access
def check_password():
def password_entered():
if password_input == os.getenv('PASSWORD'):
st.session_state['password_correct'] = True
else:
st.error("Incorrect Password, please try again.")
password_input = st.text_input("Enter Password:", type="password")
submit_button = st.button("Submit", on_click=password_entered)
if submit_button and not st.session_state.get('password_correct', False):
st.error("Please enter a valid password to access the demo.")
# Password check
if not st.session_state.get('password_correct', False):
check_password()
else:
st.sidebar.success("Password Verified. Proceed with the demo.")
input_type = st.radio("Choose input type:", ('Use predefined example', 'Enter your own'))
if input_type == 'Use predefined example':
example_type = st.radio("Select an example type:", ('good', 'bad'))
selected_example = examples[example_type]
question = selected_example['question']
explanation = selected_example['explanation']
ground_truth = selected_example['ground_truth']
else:
question = st.text_input('Enter your question:', '')
explanation = st.text_input('Enter your explanation:', '')
ground_truth = st.text_input('Enter ground truth:', '')
if st.button('Evaluate Explanation'):
if question and explanation and ground_truth:
results1, results2 = evaluate_explanation(question, explanation)
diff = compare_vectors(results1, results2)
st.write('### Model 1 Results')
st.write(results1)
st.write('### Model 2 Results')
st.write(results2)
st.write(f'### Score Difference: {diff}')
else:
st.error('Please enter a question, explanation, and ground truth to evaluate.') |