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import base64
from pathlib import Path
from datetime import datetime
import uuid
import streamlit as st
from utilities.localization import tr, language_selector
def show_welcome_page():
# Renders the welcome page with a user info form.
# Language selection dropdown.
#language_selector()
st.markdown("---")
# Header and introduction.
logo_path = Path(__file__).resolve().parent.parent / "LOGO" / "Logo.png"
logo_html = ""
if logo_path.exists():
with open(logo_path, "rb") as logo_file:
logo_base64 = base64.b64encode(logo_file.read()).decode("utf-8")
logo_html = (
f"<img src='data:image/png;base64,{logo_base64}' alt='{tr('llm_analysis_suite')}' "
"style='max-width: 280px; width: 55%; min-width: 180px; margin-bottom: 1.5rem;'/>"
)
st.markdown(
f"""
<div style="background: radial-gradient(circle at top, #1c2947, #0b1321); color: #f9fafb; padding: 2.75rem; border-radius: 14px; text-align: center; border: 1px solid rgba(220,174,54,0.25); box-shadow: 0 24px 45px rgba(8, 13, 24, 0.55);">
{logo_html}
<h1 style="color: #f9fafb; font-size: 2.2rem; margin-bottom: 0.75rem;">{tr('welcome_to_llm_analysis_suite')}</h1>
<p style="font-size: 1.15rem; margin: 0 auto; max-width: 640px; color: #dce3f2;">{tr('research_tool_intro')}</p>
</div>
""",
unsafe_allow_html=True
)
# st.markdown(f"""
# ### {tr('about_this_tool')}
# {tr('research_study_info')}
# **{tr('your_role')}**
# - {tr('role_1')}
# - {tr('role_2')}
# - {tr('role_3')}
# **{tr('data_privacy')}**
# - {tr('privacy_1')}
# - {tr('privacy_2')}
# - {tr('privacy_3')}
# ---
# """, unsafe_allow_html=True)
# Don't show the form if it has already been submitted.
if 'user_info' in st.session_state and st.session_state.user_info.get("form_submitted"):
st.success(tr('thank_you_proceed'))
return
# st.header(tr('tell_us_about_yourself'))
with st.form("user_data_form"):
# age_options = ["under_18", "18_24", "25_34", "35_44", "45_54", "55_64", "65_or_over", "prefer_not_to_say"]
# age_group = st.selectbox(
# tr('what_is_your_age_group'),
# options=age_options,
# format_func=lambda x: tr(x),
# index=2
# )
# expertise_options = ["novice", "intermediate", "expert"]
# expertise = st.selectbox(
# tr('rate_your_expertise'),
# options=expertise_options,
# format_func=lambda x: tr(x),
# index=1
# )
# Set default values
age_group = "25_34"
expertise = "intermediate"
submitted = st.form_submit_button(tr('start_analysis_button'), use_container_width=True)
if submitted:
# Generate a unique session ID.
session_id = str(uuid.uuid4())
# Store user data in the session.
st.session_state.user_info = {
"id": session_id,
"age": age_group,
"llm_experience": expertise,
"form_submitted": True,
"timestamp": datetime.now().strftime("%Y-%m-%d %H:%M:%S")
}
st.success(tr('thank_you_main_suite'))
st.rerun()
if __name__ == "__main__":
show_welcome_page() |