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