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import streamlit as st
def CreatePage():
st.markdown("""
<h1 style="text-align:center; color:#4CAF50; font-size: 40px;">🚀 Welcome to DataScribe</h1>
<p style="text-align:center; font-size: 18px; color:#333;">An AI-powered information extraction tool to streamline data retrieval and analysis.</p>
""", unsafe_allow_html=True)
st.markdown("""---""")
def feature_card(title, description, icon, page):
col1, col2 = st.columns([1, 4])
with col1:
st.markdown(f"<div style='font-size: 40px; text-align:center;'>{icon}</div>", unsafe_allow_html=True)
with col2:
if st.button(f"{title}", key=title, help=description):
st.session_state.selected_page = page
st.markdown(f"<p style='font-size: 14px; color:#555;'>{description}</p>", unsafe_allow_html=True)
col1, col2 = st.columns([1, 1])
with col1:
feature_card(
title="Upload Data",
description="Upload data from CSV or Google Sheets to get started with your extraction.",
icon="📄",
page="Upload Data"
)
with col2:
feature_card(
title="Define Custom Queries",
description="Set custom search queries for each entity in your dataset for specific information retrieval.",
icon="🔍",
page="Define Query"
)
col1, col2 = st.columns([1, 1])
with col1:
feature_card(
title="Run Automated Searches",
description="Execute automated web searches and extract relevant information using an AI-powered agent.",
icon="🤖",
page="Extract Information"
)
with col2:
feature_card(
title="View & Download Results",
description="View extracted data in a structured format and download as a CSV or update Google Sheets.",
icon="📊",
page="View & Download"
)
return True
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