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| import pandas as pd | |
| import streamlit as st | |
| # Title | |
| st.title("Q&A Evaluation Tool") | |
| # Upload the dataset | |
| def load_data(file_path): | |
| return pd.read_excel(file_path) | |
| # File upload section | |
| uploaded_file = st.file_uploader("Upload the Q&A Excel File", type=["xlsx"]) | |
| if uploaded_file: | |
| # Load data | |
| data = load_data(uploaded_file) | |
| # Add columns for evaluation if not present | |
| if "Rating" not in data.columns: | |
| data["Rating"] = "" | |
| if "Comments" not in data.columns: | |
| data["Comments"] = "" | |
| # Initialize session state for tracking progress | |
| if "current_index" not in st.session_state: | |
| st.session_state.current_index = 0 | |
| # Display current question-answer pair | |
| idx = st.session_state.current_index | |
| if idx < len(data): | |
| st.subheader(f"Question {idx + 1}:") | |
| st.write(data.loc[idx, "Question"]) | |
| st.subheader("Generated Answer:") | |
| st.write(data.loc[idx, "Generated Answer"]) | |
| # Rating input | |
| rating = st.slider("Rate the answer (1 = Poor, 5 = Excellent)", 1, 5, step=1) | |
| comment = st.text_area("Add any comments or suggestions") | |
| # Save feedback | |
| if st.button("Submit Feedback"): | |
| data.at[idx, "Rating"] = rating | |
| data.at[idx, "Comments"] = comment | |
| st.session_state.current_index += 1 | |
| # Save the updated dataset | |
| data.to_excel("evaluated_data.xlsx", index=False) | |
| # Confirmation and next question | |
| st.success("Feedback submitted!") | |
| st.experimental_rerun() | |
| else: | |
| st.write("You have completed the evaluation. Thank you!") | |
| # Download the evaluated file | |
| with open("evaluated_data.xlsx", "rb") as f: | |
| st.download_button( | |
| "Download Evaluated Data", | |
| f, | |
| file_name="evaluated_data.xlsx", | |
| mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet", | |
| ) | |
| else: | |
| st.info("Please upload an Excel file to get started.") | |