42 lines
1.6 KiB
Python
42 lines
1.6 KiB
Python
import streamlit as st
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# Set the page configuration
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# This should be the first Streamlit command in your script
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st.set_page_config(
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page_title="PYGREX: Pyhton Explainable Group Recommendation",
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page_icon="👥",
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layout="wide",
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initial_sidebar_state="expanded",
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)
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# --- Welcome Page Content ---
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st.title("Welcome to PY-GREX! 👋")
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st.header("A Novel Library for Supporting Explanations in Group Recommendation")
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st.markdown("""
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Welcome to the interactive application for the **GREX** library. This tool allows you to step through the entire process of generating and explaining group recommendations.
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**GREX** is designed with a modular architecture, allowing you to flexibly combine different components like data handling, recommendation models, group aggregation strategies, and explanation methods.
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### How to Use This App:
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1. **📄 Data Preparation**: Use the sidebar to navigate to the Data Preparation page to upload your datasets.
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2. **🧠 Model Training**: Select and train a recommender model.
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3. **🎯 Group Recommendation**: Choose a group and an aggregation strategy to generate recommendations.
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4. **💬 Explanation & Evaluation**: View the generated explanations and analyze their quality.
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Use the navigation on the left to begin!
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# """)
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# st.sidebar.header("⚙️ App Controls")
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# st.sidebar.write("If results seem inconsistent, clear the app's memory.")
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# if st.sidebar.button("⚠️ Clear Cache & Rerun"):
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# # Clears all items from the session state (like data, models, etc.)
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# st.session_state.clear()
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# # Reruns the script from the top
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# st.rerun()
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st.sidebar.success("Select a page above to start.")
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