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import streamlit as st
from datasets import load_dataset
import streamlit.components.v1 as components
# Load the dataset
dataset = load_dataset("awacke1/DatasetOfDatasetsUSA")
# Initialize session state for record navigation
if 'index' not in st.session_state:
st.session_state.index = 0
# Define the maximum index as the length of the dataset - 1
max_index = len(dataset['train']) - 1
# Navigation buttons
col1, col2, col3, col4, col5 = st.columns(5)
with col1:
if st.button('⏮️'):
st.session_state.index = 0
with col2:
if st.button('◀️') and st.session_state.index > 0:
st.session_state.index -= 1
with col3:
st.write(f"Record {st.session_state.index + 1} of {max_index + 1}")
with col4:
if st.button('▶️') and st.session_state.index < max_index:
st.session_state.index += 1
with col5:
if st.button('⏭️'):
st.session_state.index = max_index
# Generate the A-Frame scene HTML with links from the dataset
aframe_html = """
<a-scene embedded style="width: 800px; height: 600px;">
<a-sky color="#ECECEC"></a-sky>
"""
# Loop through the dataset and create a-link entities for each record
for index, item in enumerate(dataset['train']):
cityOrState = item['cityOrState']
link = item['link']
linkType = item['linkType']
position = f"{index * 1.5} 1.25 -3" # Simple positioning logic
aframe_html += f"""
<a-link href="{link}" position="{position}" title="{cityOrState} - {linkType}" image="#homeThumbnail"></a-link>
"""
# Close the A-Scene tag
aframe_html += "</a-scene>"
# Use Streamlit components to render the A-Frame HTML
components.html(aframe_html, height=600)
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