import streamlit as st
import pandas as pd

# Load materials data
@st.cache
def load_data():
    # This data should be preprocessed and saved as a CSV for properties and materials
    data = pd.read_csv('materials_properties.csv')
    return data

# Title
st.title("Material Selector App")
st.sidebar.title("Material Filters")

# Load data
data = load_data()

# Filters
st.sidebar.header("Filter by Class")
material_class = st.sidebar.selectbox("Select Material Class", data['Class'].unique())

st.sidebar.header("Filter by Properties")
property_filter = st.sidebar.multiselect("Select Properties to Filter", data.columns[2:], default=[])

# Filter data based on selection
filtered_data = data[data['Class'] == material_class]
if property_filter:
    filtered_data = filtered_data[property_filter + ['Material', 'Class']]

# Show filtered data
st.subheader("Filtered Materials")
st.write(filtered_data)

# Download filtered data
st.sidebar.download_button(
    label="Download Filtered Data as CSV",
    data=filtered_data.to_csv(index=False),
    file_name='filtered_materials.csv',
    mime='text/csv',
)

# Footer
st.markdown("Powered by Streamlit and designed for Hugging Face deployment.")