Code Editor for app.py

import streamlit as st
import pandas as pd
import numpy as np
import plotly.graph_objects as go
from PIL import Image
import io

# Configure page
st.set_page_config(page_title="SkinGenius AI", page_icon="🧴", layout="wide")

# Initialize session state
if 'current_step' not in st.session_state:
    st.session_state.current_step = 1
if 'user_data' not in st.session_state:
    st.session_state.user_data = {}

def reset_form():
    st.session_state.current_step = 1
    st.session_state.user_data = {}

def next_step():
    if st.session_state.current_step < 5:
        st.session_state.current_step += 1

def prev_step():
    if st.session_state.current_step > 1:
        st.session_state.current_step -= 1

# Header
st.title("🧴 SkinGenius AI")
st.markdown("*Build your personalized skin report in 4 simple steps*")

# Progress bar
progress = (st.session_state.current_step - 1) / 4
st.progress(progress)

# Step indicators
steps = ["Basic Info", "Symptoms", "Photos", "Lifestyle", "Report"]
cols = st.columns(5)
for i, step in enumerate(steps):
    with cols[i]:
        if i + 1 == st.session_state.current_step:
            st.markdown(f"**{i+1}. {step}** ✅")
        elif i + 1 < st.session_state.current_step:
            st.markdown(f"{i+1}. {step} ✅")
        else:
            st.markdown(f"{i+1}. {step}")

st.markdown("---")

# Step 1: Basic Info
if st.session_state.current_step == 1:
    st.header("1. Basic Information")
    
    col1, col2 = st.columns(2)
    
    with col1:
        age = st.number_input("Age", min_value=13, max_value=100, value=25)
        gender = st.selectbox("Gender (Optional)", ["Prefer not to say", "Female", "Male", "Non-binary"])
        
        skin_concerns = st.multiselect(
            "Primary Skin Concerns",
            ["Acne", "Dryness", "Oily Skin", "Sensitivity", "Aging", "Dark Spots", "Redness", "Large Pores", "Uneven Texture"]
        )
    
    with col2:
        current_routine = st.text_area(
            "Current Skincare Routine",
            placeholder="Describe your current morning and evening routine...",
            height=150
        )
    
    if st.button("Next: Symptoms Analysis", type="primary"):
        st.session_state.user_data.update({
            'age': age,
            'gender': gender,
            'skin_concerns': skin_concerns,
            'current_routine': current_routine
        })
        next_step()
        st.rerun()

# Step 2: Symptoms
elif st.session_state.current_step == 2:
    st.header("2. Symptoms Analysis")
    
    col1, col2 = st.columns([2, 1])
    
    with col1:
        st.subheader("Facial Mapping")
        st.markdown("Select areas where you experience skin issues:")
        
        # Create a simple facial map using checkboxes
        face_areas = {
            "Forehead": st.checkbox("Forehead"),
            "T-Zone": st.checkbox("T-Zone (Nose & Center)"),
            "Cheeks": st.checkbox("Cheeks"),
            "Under Eyes": st.checkbox("Under Eyes"),
            "Jawline": st.checkbox("Jawline"),
            "Chin": st.checkbox("Chin"),
            "Neck": st.checkbox("Neck")
        }
    
    with col2:
        st.subheader("Additional Symptoms")
        
        symptoms = {
            "stinging": st.checkbox("Stinging/Burning sensation"),
            "itching": st.checkbox("Itching"),
            "tightness": st.checkbox("Skin feels tight"),
            "flaking": st.checkbox("Flaking/Peeling"),
            "redness": st.checkbox("Persistent redness"),
            "allergic_reactions": st.checkbox("Allergic reactions to products")
        }
    
    col1, col2 = st.columns(2)
    with col1:
        if st.button("← Previous"):
            prev_step()
            st.rerun()
    
    with col2:
        if st.button("Next: Photo Analysis", type="primary"):
            st.session_state.user_data.update({
                'face_areas': face_areas,
                'symptoms': symptoms
            })
            next_step()
            st.rerun()

# Step 3: Photos
elif st.session_state.current_step == 3:
    st.header("3. Photo Analysis")
    
    col1, col2 = st.columns(2)
    
    with col1:
        st.subheader("Front View")
        front_photo = st.file_uploader("Upload front-facing photo", type=['png', 'jpg', 'jpeg'], key="front")
        
        if front_photo:
            image = Image.open(front_photo)
            st.image(image, caption="Front view", use_column_width=True)
            
            # Simulate AI feedback
            feedback_messages = [
                "✅ Good lighting detected",
                "⚠️ Image slightly blurry - try holding phone steadier",
                "✅ Face clearly visible",
                "💡 Tip: Remove makeup for better analysis"
            ]
            
            st.markdown("**AI Feedback:**")
            for msg in feedback_messages:
                st.markdown(f"- {msg}")
    
    with col2:
        st.subheader("Side View")
        side_photo = st.file_uploader("Upload side profile photo", type=['png', 'jpg', 'jpeg'], key="side")
        
        if side_photo:
            image = Image.open(side_photo)
            st.image(image, caption="Side view", use_column_width=True)
            
            # Simulate AI feedback
            feedback_messages = [
                "✅ Good angle captured",
                "⚠️ Too dark - try better lighting",
                "✅ Skin texture visible",
                "💡 Natural lighting works best"
            ]
            
            st.markdown("**AI Feedback:**")
            for msg in feedback_messages:
                st.markdown(f"- {msg}")
    
    st.info("📸 For best results: Use natural lighting, clean face, and hold camera steady")
    
    col1, col2 = st.columns(2)
    with col1:
        if st.button("← Previous"):
            prev_step()
            st.rerun()
    
    with col2:
        if st.button("Next: Lifestyle", type="primary"):
            st.session_state.user_data.update({
                'front_photo': front_photo is not None,
                'side_photo': side_photo is not None
            })
            next_step()
            st.rerun()

# Step 4: Lifestyle
elif st.session_state.current_step == 4:
    st.header("4. Lifestyle Factors")
    
    col1, col2 = st.columns(2)
    
    with col1:
        st.subheader("Hydration & Health")
        water_intake = st.slider("Daily water intake (glasses)", 1, 15, 6)
        sleep_hours = st.slider("Average sleep hours", 4, 12, 7)
        stress_level = st.select_slider("Stress level", options=["Low", "Moderate", "High"], value="Moderate")
    
    with col2:
        st.subheader("Environmental Factors")
        sun_exposure = st.select_slider("Daily sun exposure", options=["Minimal", "Moderate", "High"], value="Moderate")
        sunscreen_use = st.radio("Sunscreen usage", ["Never", "Sometimes", "Daily"])
        environment = st.selectbox("Living environment", ["Urban", "Suburban", "Rural", "Coastal"])
    
    st.subheader("Additional Factors")
    col1, col2, col3 = st.columns(3)
    
    with col1:
        exercise_freq = st.selectbox("Exercise frequency", ["Rarely", "1-2x/week", "3-4x/week", "Daily"])
    
    with col2:
        diet_type = st.selectbox("Diet type", ["Standard", "Vegetarian", "Vegan", "Keto", "Mediterranean"])
    
    with col3:
        hormonal_changes = st.checkbox("Experiencing hormonal changes")
    
    col1, col2 = st.columns(2)
    with col1:
        if st.button("← Previous"):
            prev_step()
            st.rerun()
    
    with col2:
        if st.button("Generate Report", type="primary"):
            st.session_state.user_data.update({
                'water_intake': water_intake,
                'sleep_hours': sleep_hours,
                'stress_level': stress_level,
                'sun_exposure': sun_exposure,
                'sunscreen_use': sunscreen_use,
                'environment': environment,
                'exercise_freq': exercise_freq,
                'diet_type': diet_type,
                'hormonal_changes': hormonal_changes
            })
            next_step()
            st.rerun()

# Step 5: Report
elif st.session_state.current_step == 5:
    st.header("📊 Your Personalized Skin Report")
    
    # Generate dummy skin score based on inputs
    base_score = 75
    
    # Adjust score based on inputs
    if st.session_state.user_data.get('water_intake', 6) < 4:
        base_score -= 10
    if st.session_state.user_data.get('sunscreen_use') == 'Never':
        base_score -= 15
    if st.session_state.user_data.get('stress_level') == 'High':
        base_score -= 8
    if st.session_state.user_data.get('sleep_hours', 7) < 6:
        base_score -= 5
    
    skin_score = max(40, min(95, base_score))
    
    # Report tabs
    tab1, tab2, tab3 = st.tabs(["Skin Analysis", "Product Recommendations", "Medical Insights"])
    
    with tab1:
        st.subheader("Your Skin Score")
        
        # Create gauge chart
        fig = go.Figure(go.Indicator(
            mode = "gauge+number+delta",
            value = skin_score,
            domain = {'x': [0, 1], 'y': [0, 1]},
            title = {'text': "Skin Health Score"},
            delta = {'reference': 80},
            gauge = {
                'axis': {'range': [None, 100]},
                'bar': {'color': "darkblue"},
                'steps': [
                    {'range': [0, 50], 'color': "lightgray"},
                    {'range': [50, 80], 'color': "yellow"},
                    {'range': [80, 100], 'color': "green"}
                ],
                'threshold': {
                    'line': {'color': "red", 'width': 4},
                    'thickness': 0.75,
                    'value': 90
                }
            }
        ))
        
        fig.update_layout(height=300)
        st.plotly_chart(fig, use_container_width=True)
        
        # Insights
        st.subheader("Key Insights")
        
        insights = []
        if st.session_state.user_data.get('water_intake', 6) < 6:
            insights.append("🔹 **Moderate dehydration detected** - Consider increasing water intake")
        
        if 'Dryness' in st.session_state.user_data.get('skin_concerns', []):
            insights.append("🔹 **Dry skin concerns** - Focus on hydrating ingredients")
        
        if 'Acne' in st.session_state.user_data.get('skin_concerns', []):
            insights.append("🔹 **Acne-prone skin** - Gentle, non-comedogenic products recommended")
        
        if st.session_state.user_data.get('sunscreen_use') != 'Daily':
            insights.append("🔹 **Sun protection gap** - Daily SPF is crucial for skin health")
        
        if not insights:
            insights.append("🔹 **Good overall skin health** - Maintain current routine with minor optimizations")
        
        for insight in insights:
            st.markdown(insight)
    
    with tab2:
        st.subheader("Personalized Product Recommendations")
        
        # Morning routine
        st.markdown("### 🌅 Morning Routine")
        morning_products = [
            {"step": "1. Cleanser", "product": "CeraVe Foaming Facial Cleanser", "price": "$12.99"},
            {"step": "2. Serum", "product": "The Ordinary Niacinamide 10% + Zinc 1%", "price": "$7.90"},
            {"step": "3. Moisturizer", "product": "CeraVe Daily Moisturizing Lotion", "price": "$16.99"},
            {"step": "4. Sunscreen", "product": "EltaMD UV Clear Broad-Spectrum SPF 46", "price": "$37.00"}
        ]
        
        for product in morning_products:
            col1, col2, col3 = st.columns([2, 3, 1])
            with col1:
                st.markdown(f"**{product['step']}**")
            with col2:
                st.markdown(product['product'])
            with col3:
                st.markdown(product['price'])
        
        # Evening routine
        st.markdown("### 🌙 Evening Routine")
        evening_products = [
            {"step": "1. Cleanser", "product": "CeraVe Hydrating Facial Cleanser", "price": "$12.99"},
            {"step": "2. Treatment", "product": "The Ordinary Retinol 0.2% in Squalane", "price": "$9.90"},
            {"step": "3. Moisturizer", "product": "CeraVe PM Facial Moisturizing Lotion", "price": "$16.99"}
        ]
        
        for product in evening_products:
            col1, col2, col3 = st.columns([2, 3, 1])
            with col1:
                st.markdown(f"**{product['step']}**")
            with col2:
                st.markdown(product['product'])
            with col3:
                st.markdown(product['price'])
        
        # Weekly treatments
        st.markdown("### 📅 Weekly Treatments")
        st.markdown("- **2x per week**: The Ordinary AHA 30% + BHA 2% Peeling Solution")
        st.markdown("- **1x per week**: Hydrating sheet mask")
        
        total_cost = 139.66
        st.markdown(f"### 💰 Total Monthly Cost: ${total_cost:.2f}")
    
    with tab3:
        st.subheader("Medical Insights & Recommendations")
        
        # Medical alerts
        st.markdown("### ⚠️ Medical Alerts")
        
        alerts = []
        if st.session_state.user_data.get('symptoms', {}).get('allergic_reactions'):
            alerts.append("🚨 **Allergic reactions reported** - Patch test all new products before use")
        
        if st.session_state.user_data.get('symptoms', {}).get('stinging'):
            alerts.append("⚠️ **Stinging/burning sensations** - Avoid products with high acid concentrations")
        
        if 'Redness' in st.session_state.user_data.get('skin_concerns', []):
            alerts.append("🩺 **Persistent redness** - See dermatologist if redness lasts >2 weeks")
        
        if st.session_state.user_data.get('age', 0) > 50:
            alerts.append("📋 **Age consideration** - Annual skin cancer screening recommended")
        
        if not alerts:
            alerts.append("✅ **No immediate medical concerns** - Continue monitoring skin health")
        
        for alert in alerts:
            st.markdown(alert)
        
        # General recommendations
        st.markdown("### 📋 General Health Recommendations")
        
        recommendations = [
            "🔹 Perform monthly self-skin examinations",
            "🔹 Use broad-spectrum SPF 30+ daily",
            "🔹 Maintain adequate hydration (8+ glasses water daily)",
            "🔹 Get 7-9 hours of quality sleep",
            "🔹 Manage stress through exercise or meditation",
            "🔹 Eat a balanced diet rich in antioxidants"
        ]
        
        for rec in recommendations:
            st.markdown(rec)
        
        # When to see a dermatologist
        st.markdown("### 🩺 When to Consult a Dermatologist")
        st.markdown("- New or changing moles")
        st.markdown("- Persistent acne not responding to treatment")
        st.markdown("- Severe skin reactions or allergies")
        st.markdown("- Skin concerns affecting quality of life")
    
    # Action buttons
    st.markdown("---")
    col1, col2, col3 = st.columns(3)
    
    with col1:
        if st.button("📧 Email Report"):
            st.success("Report sent to your email!")
    
    with col2:
        if st.button("📱 Save to Phone"):
            st.success("Report saved to downloads!")
    
    with col3:
        if st.button("🔄 Start New Analysis", on_click=reset_form):
            st.rerun()

# Footer
st.markdown("---")
st.markdown("*SkinGenius AI - Your personalized skincare companion*")
st.markdown("⚠️ This tool provides general guidance only. Always consult healthcare professionals for medical concerns.")