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"""Streamlit entry point for the Sentinel expert feedback UI."""

import streamlit as st

# --- Page Configuration ---
st.set_page_config(
    page_title="Sentinel | AI Cancer Risk Assessment", page_icon="βš•οΈ", layout="wide"
)

# --- Header Section ---
st.title("Sentinel: AI-Powered Cancer Risk Assessment")
st.markdown("""
Welcome to **Sentinel**, an advanced demonstration of an AI-powered assistant for evidence-based cancer risk assessment.
This tool analyzes user-provided health data to generate a preliminary risk profile and personalized diagnostic recommendations based on a configurable knowledge base.
""")

st.divider()

# --- Key Features Section ---
st.header("How It Works", anchor=False)
col1, col2, col3 = st.columns(3, gap="large")

with col1:
    st.subheader("πŸ‘€ 1. Build Your Profile")
    st.write(
        "Navigate to the **Profile** page to input your health information. "
        "You can either upload a pre-filled YAML file or create a new profile from scratch using our guided form."
    )

with col2:
    st.subheader("βš™οΈ 2. Configure the AI")
    st.write(
        "On the **Configuration** page, you can select the AI model and the specific cancer modules and diagnostic protocols "
        "from our knowledge base that will be used for your assessment."
    )

with col3:
    st.subheader("πŸ”¬ 3. Run the Assessment")
    st.write(
        "Finally, visit the **Assessment** page to run the analysis. You'll receive a full dashboard of your results, "
        "and you can interact with the AI assistant via a chat interface."
    )

# --- Call to Action / How to Get Started ---
st.header("Get Started", anchor=False)
st.page_link(
    "pages/1_Profile.py", label="**Go to the Profile Page to begin β†’**", icon="πŸ‘€"
)

st.divider()

st.warning(
    "**Disclaimer:** This is a demo application - please report any bugs or issues to Tom!"
)


# --- Footer / About Section ---
with st.sidebar:
    st.info("Created by **Tom Barrett**")
    with st.expander("About Sentinel"):
        st.markdown("""
        This application uses a Large Language Model (LLM) to synthesize user data with an evidence-based knowledge base,
        providing a nuanced, preliminary cancer risk assessment.

        **Powered by:**
        - Streamlit
        - FastAPI
        - LangChain
        - ChatGPT, Google Gemini, Llama, etc.
        - β˜• Coffee
        """)