app.py

import streamlit as st
import time
import plotly.graph_objects as go
import random

# Set page layout to wide mode
st.set_page_config(layout="wide")

# Treatment outcomes and possibilities
outcomes = [
    ("Doctor prescribes Treatment 1 (Personalized Drug A)", "info"),
    ("Nurse monitors Patient - Slight improvement", "success"),
    ("Clinician evaluates lab results - Treatment seems effective", "info"),
    ("Doctor prescribes Treatment 2 (Personalized Drug B)", "warning"),
    ("Nurse monitors Patient - Side effects observed", "error"),
    ("Clinician suggests modifying dosage", "warning"),
    ("Doctor prescribes modified Treatment 2", "info"),
    ("Patient shows significant improvement", "success")
]

# Different possible outcomes of each treatment
possibilities = {
    1: [
        ("Possibility 1: Patient responds well to Treatment 1", "success"),
        ("Possibility 2: Slight improvement, but inconclusive results", "info"),
        ("Possibility 3: No response, reevaluation needed", "error")
    ],
    2: [
        ("Possibility 1: Significant improvement", "success"),
        ("Possibility 2: Mild side effects", "warning")
    ],
    3: [
        ("Possibility 1: Treatment is effective", "success"),
        ("Possibility 2: Inconclusive lab results", "info")
    ],
    4: [
        ("Possibility 1: Improvement with Drug B", "success"),
        ("Possibility 2: Significant side effects", "error")
    ],
    5: [
        ("Possibility 1: Side effects worsen, modify dosage", "warning"),
        ("Possibility 2: Manageable side effects", "info")
    ],
    6: [
        ("Possibility 1: Dosage adjustment successful", "success"),
        ("Possibility 2: Further modification needed", "warning")
    ],
    7: [
        ("Possibility 1: Patient responds well to modified treatment", "success"),
        ("Possibility 2: Limited response, consider alternatives", "warning")
    ],
    8: [
        ("Possibility 1: Complete recovery", "success"),
        ("Possibility 2: Partial improvement, continue monitoring", "info")
    ]
}

# Initialize a dictionary to keep track of patient counts for each possibility
patient_counts = {i: [0] * len(possibilities[i]) for i in possibilities}

# Create a tree diagram using Plotly
def create_tree_diagram(stage, selected_box=None):
    labels = [f"Stage {stage}: {outcomes[stage - 1][0]}"]
    parents = [""]
    values = [1]  # Root node value
    colors = ['lightgrey']  # Root node color
    
    stage_possibilities = possibilities.get(stage, [("No specific possibilities defined", "info")])
    
    for idx, (possibility, outcome_type) in enumerate(stage_possibilities):
        labels.append(f"{possibility} - Patients: {patient_counts[stage][idx]}")
        parents.append(f"Stage {stage}: {outcomes[stage - 1][0]}")
        values.append(1)  # Equal weight for all possibilities
        if outcome_type == "success":
            colors.append('#d4edda' if idx != selected_box else '#28a745')
        elif outcome_type == "info":
            colors.append('#cce5ff' if idx != selected_box else '#007bff')
        elif outcome_type == "warning":
            colors.append('#fff3cd' if idx != selected_box else '#ffc107')
        elif outcome_type == "error":
            colors.append('#f8d7da' if idx != selected_box else '#dc3545')
        else:
            colors.append('lightgrey')
    
    fig = go.Figure(go.Treemap(
        labels=labels,
        parents=parents,
        values=values,
        marker=dict(colors=colors),
        textinfo="label",
        textfont=dict(size=14),
    ))

    fig.update_layout(
        margin=dict(t=10, l=10, r=10, b=10),
        width=600, height=400,
        uniformtext=dict(minsize=12, mode='show')
    )
    
    return fig

# Function to increment patient counts in random boxes for each stage
def run_simulation():
    for stage in possibilities:
        selected_box = random.randint(0, len(possibilities[stage]) - 1)
        patient_counts[stage][selected_box] += 1
        st.session_state[f'selected_box_{stage}'] = selected_box

# Initialize the selected box in session state if it doesn't exist
for stage in possibilities:
    if f'selected_box_{stage}' not in st.session_state:
        st.session_state[f'selected_box_{stage}'] = None

# Streamlit app layout
st.title("Precision Medicine AI Agents - Treatment Decision Tree")

# Add a "Run Simulation" button
run_button = st.button("Run Simulation")

# If the button is pressed, run the simulation
if run_button:
    run_simulation()

# Render the animation with the updated patient counts
for i, (outcome, outcome_type) in enumerate(outcomes, 1):
    with st.container():
        col1, col2 = st.columns([1, 2])

        with col1:
            if outcome_type == "success":
                st.markdown(f"<div style='padding:10px; border-radius:5px; background-color:#d4edda; color:#155724;'><strong>Stage {i}:</strong> {outcome}</div>", unsafe_allow_html=True)
            elif outcome_type == "info":
                st.markdown(f"<div style='padding:10px; border-radius:5px; background-color:#cce5ff; color:#004085;'><strong>Stage {i}:</strong> {outcome}</div>", unsafe_allow_html=True)
            elif outcome_type == "warning":
                st.markdown(f"<div style='padding:10px; border-radius:5px; background-color:#fff3cd; color:#856404;'><strong>Stage {i}:</strong> {outcome}</div>", unsafe_allow_html=True)
            elif outcome_type == "error":
                st.markdown(f"<div style='padding:10px; border-radius:5px; background-color:#f8d7da; color:#721c24;'><strong>Stage {i}:</strong> {outcome}</div>", unsafe_allow_html=True)

            st.markdown("### Possibilities:")
            stage_possibilities = possibilities.get(i, [("No specific possibilities defined", "info")])
            for idx, (possibility, possibility_type) in enumerate(stage_possibilities):
                color = 'lightgrey'
                if possibility_type == "success":
                    color = '#d4edda'
                elif possibility_type == "info":
                    color = '#cce5ff'
                elif possibility_type == "warning":
                    color = '#fff3cd'
                elif possibility_type == "error":
                    color = '#f8d7da'

                # Display the possibility and its patient count
                st.markdown(f"<div style='padding:5px; background-color:{color};'><strong>{possibility} - Patients: {patient_counts[i][idx]}</strong></div>", unsafe_allow_html=True)

        with col2:
            selected_box = st.session_state[f'selected_box_{i}']
            fig = create_tree_diagram(i, selected_box)
            st.plotly_chart(fig, use_container_width=True)