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import pandas as pd |
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import streamlit as st |
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from util.evaluator import evaluator,write_evaluation_commentary |
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import os |
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examples = { |
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'good': { |
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'question': "What causes rainbows to appear in the sky?", |
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'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." |
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}, |
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'bad': { |
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'question': "What causes rainbows to appear in the sky?", |
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'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." |
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} |
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} |
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def check_password(): |
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def password_entered(): |
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if password_input == os.getenv('PASSWORD'): |
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st.session_state['password_correct'] = True |
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else: |
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st.error("Incorrect Password, please try again.") |
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password_input = st.text_input("Enter Password:", type="password") |
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submit_button = st.button("Submit", on_click=password_entered) |
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if submit_button and not st.session_state.get('password_correct', False): |
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st.error("Please enter a valid password to access the demo.") |
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st.title('Natural Language Explanation Demo') |
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if not st.session_state.get('password_correct', False): |
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check_password() |
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else: |
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model_name = st.selectbox('Select a model:', ['gpt4-1106', 'gpt35-1106']) |
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input_type = st.radio("Choose input type:", ('Use predefined example', 'Enter your own')) |
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if input_type == 'Use predefined example': |
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example_type = st.radio("Select an example type:", ('good', 'bad')) |
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question = examples[example_type]['question'] |
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explanation = examples[example_type]['explanation'] |
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else: |
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question = st.text_input('Enter your question:', '') |
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explanation = st.text_input('Enter your explanation:', '') |
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st.write('### Question') |
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st.write(question if question else 'No question entered yet.') |
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st.write('### Explanation') |
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st.write(explanation if explanation else 'No explanation entered yet.') |
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if st.button('Evaluate Explanation'): |
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if question and explanation: |
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eval = evaluator(model_name) |
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scores = eval(question, explanation) |
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st.write('### Scores') |
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details = write_evaluation_commentary(scores) |
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df = pd.DataFrame(details) |
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st.write(df) |
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csv = df.to_csv(index=False) |
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st.download_button( |
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label="Download evaluation as CSV", |
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data=csv, |
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file_name='evaluation.csv', |
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mime='text/csv', |
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) |
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else: |
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st.error('Please enter both a question and an explanation to evaluate.') |