app.py

import streamlit as st
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from io import BytesIO
from reportlab.lib.pagesizes import letter
from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer, Image, ListFlowable, ListItem
from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
from datetime import date
from openai import OpenAI
import os
from datetime import datetime, timedelta
from dotenv import load_dotenv
from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer, Image, ListFlowable, ListItem


# Load environment variables
load_dotenv()

# Set up OpenAI client
client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))

# Constants
MEAL_FREQUENCY = ["Breakfast", "Morning Snack", "Lunch", "Afternoon Snack", "Dinner", "Evening Snack"]
FOOD_GROUPS = ["Fruits", "Vegetables", "Grains", "Proteins", "Dairy"]
EXERCISE = ["Cardio", "Strength", "Flexibility", "Balance"]
LIFESTYLE = ["Sleep", "Stress", "Work-Life Balance", "Social Connections"]
MEDICAL_HISTORY = ["Chronic Conditions", "Family History", "Medications", "Allergies"]

# Helper functions
def get_gpt_analysis(prompt, data):
    try:
        response = client.chat.completions.create(
            model="gpt-3.5-turbo",
            messages=[
                {"role": "system", "content": "You are a senior nutritionist and health advisor. Provide concise, personalized advice in bullet points."},
                {"role": "user", "content": f"{prompt}\n\nUser Data: {data}"}
            ],
            temperature=0.2,
            max_tokens=1024
        )
        return response.choices[0].message.content
    except Exception as e:
        print(f"Error in GPT API call: {e}")
        return "I apologize, but I encountered an error while processing your request."

# Update the create_chart function
def create_chart(data, labels, title, chart_type='bar'):
    fig, ax = plt.subplots(figsize=(8, 6))
    if chart_type == 'bar':
        ax.bar(labels, data)
    elif chart_type == 'pie':
        # Filter out zero values to avoid plotting empty slices
        non_zero = [(label, value) for label, value in zip(labels, data) if value > 0]
        if non_zero:
            labels, data = zip(*non_zero)
            ax.pie(data, labels=labels, autopct='%1.1f%%', startangle=90)
            ax.axis('equal')
        else:
            ax.text(0.5, 0.5, "No data to display", ha='center', va='center')
    ax.set_title(title)
    plt.close(fig)
    
    buf = BytesIO()
    fig.savefig(buf, format='png')
    buf.seek(0)
    return buf

# Add this new function to generate a personalized weekly plan
def generate_personalized_weekly_plan(user_data):
    prefs = user_data['detailed_preferences']
    plan = {}
    
    for i in range(7):
        day = (datetime.now() + timedelta(days=i)).strftime("%A")
        plan[day] = {
            "Meals": [],
            "Exercise": [],
            "Lifestyle": []
        }
        
        # Generate meal suggestions based on preferences and nutrition data
        if "Vegetarian" in prefs['meal_preferences']:
            plan[day]["Meals"].append(f"Breakfast: Vegetarian omelette with spinach and mushrooms")
        elif "Vegan" in prefs['meal_preferences']:
            plan[day]["Meals"].append(f"Breakfast: Vegan smoothie bowl with berries and nuts")
        else:
            plan[day]["Meals"].append(f"Breakfast: Whole grain toast with avocado and eggs")
        
        plan[day]["Meals"].append(f"Lunch: Mixed green salad with {', '.join(prefs['meal_preferences'][:2])} protein")
        plan[day]["Meals"].append(f"Dinner: Grilled {prefs['meal_preferences'][0] if prefs['meal_preferences'] else 'chicken'} with roasted vegetables")
        
        # Generate exercise suggestions based on preferences and schedule
        if prefs['exercise_time'] == "Morning":
            plan[day]["Exercise"].append(f"Morning: 30-minute {prefs['exercise_preferences'][0] if prefs['exercise_preferences'] else 'walk'}")
        elif prefs['exercise_time'] == "Evening":
            plan[day]["Exercise"].append(f"Evening: 45-minute {prefs['exercise_preferences'][0] if prefs['exercise_preferences'] else 'jog'}")
        else:
            plan[day]["Exercise"].append(f"Afternoon: 1-hour {prefs['exercise_preferences'][0] if prefs['exercise_preferences'] else 'gym session'}")
        
        # Add lifestyle recommendations
        plan[day]["Lifestyle"].append(f"Practice {prefs['stress_relief'][0] if prefs['stress_relief'] else 'meditation'} for 15 minutes")
        plan[day]["Lifestyle"].append(f"Get {user_data.get('sleep_hours', 8)} hours of sleep, from {prefs['sleep_time'].strftime('%I:%M %p')} to {prefs['wake_time'].strftime('%I:%M %p')}")
    
    return plan


def generate_pdf_report(user_data, analysis):
    buffer = BytesIO()
    doc = SimpleDocTemplate(buffer, pagesize=letter, rightMargin=72, leftMargin=72, topMargin=72, bottomMargin=18)
    
    styles = getSampleStyleSheet()
    if 'Bullet' not in styles:
        styles.add(ParagraphStyle(name='Bullet', parent=styles['BodyText'], bulletIndent=20, leftIndent=35))
    
    story = []
    
    # Cover Page
    story.append(Paragraph(f"{user_data['name']}'s Health and Wellness Report", styles['Title']))
    story.append(Paragraph(f"Date: {date.today().strftime('%Y-%m-%d')}", styles['Normal']))
    story.append(Spacer(1, 12))
    
    # Personal Information
    story.append(Paragraph("Personal Information", styles['Heading1']))
    for key, value in user_data.items():
        if key not in ['nutrition', 'exercise', 'lifestyle', 'medical_history', 'detailed_preferences']:
            story.append(Paragraph(f"{key.capitalize()}: {value}", styles['Normal']))
    
    # Nutrition Analysis
    story.append(Paragraph("Nutrition Analysis", styles['Heading1']))
    nutrition_data = [user_data['nutrition'].get(group, 0) for group in FOOD_GROUPS]
    nutrition_chart = create_chart(nutrition_data, FOOD_GROUPS, "Food Group Intake")
    story.append(Image(nutrition_chart, width=400, height=300))
    
    bullet_points = [Paragraph(point.strip(), styles['Bullet']) for point in analysis['nutrition'].split('\n') if point.strip()]
    story.append(ListFlowable(bullet_points, bulletType='bullet', start=''))
    
    # Exercise Analysis
    story.append(Paragraph("Exercise Analysis", styles['Heading1']))
    exercise_data = [user_data['exercise'].get(exercise, 0) for exercise in EXERCISE]
    exercise_chart = create_chart(exercise_data, EXERCISE, "Exercise Habits")
    story.append(Image(exercise_chart, width=400, height=300))
    
    bullet_points = [Paragraph(point.strip(), styles['Bullet']) for point in analysis['exercise'].split('\n') if point.strip()]
    story.append(ListFlowable(bullet_points, bulletType='bullet', start=''))
    
    # Lifestyle Analysis
    story.append(Paragraph("Lifestyle Analysis", styles['Heading1']))
    lifestyle_data = [user_data['lifestyle'].get(factor, 0) for factor in LIFESTYLE]
    lifestyle_chart = create_chart(lifestyle_data, LIFESTYLE, "Lifestyle Factors", chart_type='pie')
    story.append(Image(lifestyle_chart, width=400, height=300))
    
    bullet_points = [Paragraph(point.strip(), styles['Bullet']) for point in analysis['lifestyle'].split('\n') if point.strip()]
    story.append(ListFlowable(bullet_points, bulletType='bullet', start=''))
    
    # Personalized Recommendations
    story.append(Paragraph("Personalized Recommendations", styles['Heading1']))
    bullet_points = [Paragraph(point.strip(), styles['Bullet']) for point in analysis['recommendations'].split('\n') if point.strip()]
    story.append(ListFlowable(bullet_points, bulletType='bullet', start=''))
    
    # Weekly Plan
    story.append(Paragraph("Your Personalized Weekly Plan", styles['Heading1']))
    
    # Generate a personalized weekly plan
    weekly_plan = generate_personalized_weekly_plan(user_data)
    
    # Add the weekly plan to the PDF
    for day, plan in weekly_plan.items():
        story.append(Paragraph(day, styles['Heading2']))
        for category, items in plan.items():
            story.append(Paragraph(category, styles['Heading3']))
            bullet_points = [Paragraph(item, styles['Bullet']) for item in items]
            story.append(ListFlowable(bullet_points, bulletType='bullet', start=''))
    
    doc.build(story)
    buffer.seek(0)
    return buffer



# Streamlit UI
st.set_page_config(page_title="Health and Wellness Assessment", page_icon="🍏", layout="wide")


def introduction_page():
    st.header("Welcome to Your Health and Wellness Journey")
    st.markdown("""

    This comprehensive assessment will help you understand your current health status and provide personalized recommendations for improvement.

    

    Please answer all questions honestly for the most accurate results. Your data is confidential and will only be used to generate your personalized report.

    

    Let's begin your journey to better health!

    """)

def personal_info_page():
    st.header("Personal Information")
    
    st.session_state.user_data['name'] = st.text_input("Name", st.session_state.user_data.get('name', ''))
    st.session_state.user_data['age'] = st.number_input("Age", min_value=18, max_value=100, value=st.session_state.user_data.get('age', 30))
    st.session_state.user_data['gender'] = st.selectbox("Gender", ["Male", "Female", "Other"], index=["Male", "Female", "Other"].index(st.session_state.user_data.get('gender', 'Male')))
    st.session_state.user_data['height'] = st.number_input("Height (cm)", min_value=100, max_value=250, value=st.session_state.user_data.get('height', 170))
    st.session_state.user_data['weight'] = st.number_input("Weight (kg)", min_value=30, max_value=200, value=st.session_state.user_data.get('weight', 70))

def nutrition_page():
    st.header("Nutrition Assessment")
    
    if 'nutrition' not in st.session_state.user_data:
        st.session_state.user_data['nutrition'] = {}
    
    st.subheader("How often do you include the following food groups in your meals?")
    for group in FOOD_GROUPS:
        st.session_state.user_data['nutrition'][group] = st.select_slider(
            f"{group}",
            options=["Never", "Rarely", "Sometimes", "Often", "Always"],
            value=st.session_state.user_data['nutrition'].get(group, "Sometimes")
        )
    
    st.subheader("Meal Frequency")
    for meal in MEAL_FREQUENCY:
        st.session_state.user_data['nutrition'][f"{meal}_frequency"] = st.select_slider(
            f"How often do you have {meal}?",
            options=["Never", "1-2 times/week", "3-4 times/week", "5-6 times/week", "Daily"],
            value=st.session_state.user_data['nutrition'].get(f"{meal}_frequency", "Daily")
        )
    
    st.session_state.user_data['water_intake'] = st.number_input(
        "How many glasses of water do you drink per day?",
        min_value=0,
        max_value=20,
        value=st.session_state.user_data.get('water_intake', 8)
    )

def exercise_page():
    st.header("Exercise Habits")
    
    if 'exercise' not in st.session_state.user_data:
        st.session_state.user_data['exercise'] = {}
    
    st.subheader("How often do you engage in the following types of exercise?")
    for exercise_type in EXERCISE:
        st.session_state.user_data['exercise'][exercise_type] = st.select_slider(
            f"{exercise_type}",
            options=["Never", "1-2 times/month", "1-2 times/week", "3-4 times/week", "5+ times/week"],
            value=st.session_state.user_data['exercise'].get(exercise_type, "1-2 times/week")
        )
    
    st.session_state.user_data['exercise_duration'] = st.number_input(
        "On average, how long are your exercise sessions? (minutes)",
        min_value=0,
        max_value=180,
        value=st.session_state.user_data.get('exercise_duration', 30)
    )

# Add this function to convert lifestyle ratings to numeric values
def lifestyle_to_numeric(rating):
    conversion = {
        "Poor": 1,
        "Fair": 2,
        "Good": 3,
        "Very Good": 4,
        "Excellent": 5,
        "Very Low": 1,
        "Low": 2,
        "Moderate": 3,
        "High": 4,
        "Very High": 5
    }
    return conversion.get(rating, 3)  # Default to 3 if rating not found

# Update the lifestyle_page function
def lifestyle_page():
    st.header("Lifestyle Factors")
    
    if 'lifestyle' not in st.session_state.user_data:
        st.session_state.user_data['lifestyle'] = {}
    
    st.subheader("Rate the following aspects of your lifestyle:")
    options = ["Poor", "Fair", "Good", "Very Good", "Excellent"]
    for factor in LIFESTYLE:
        # Get the current value, defaulting to "Good" if not set or not in options
        current_value = st.session_state.user_data['lifestyle'].get(factor, "Good")
        if current_value not in options:
            current_value = "Good"
        
        rating = st.select_slider(
            f"{factor}",
            options=options,
            value=current_value
        )
        st.session_state.user_data['lifestyle'][factor] = lifestyle_to_numeric(rating)
    
    st.session_state.user_data['sleep_hours'] = st.number_input(
        "How many hours of sleep do you get on average?",
        min_value=4,
        max_value=12,
        value=st.session_state.user_data.get('sleep_hours', 7)
    )
    
    stress_options = ["Very Low", "Low", "Moderate", "High", "Very High"]
    current_stress = st.session_state.user_data.get('stress_level', "Moderate")
    if current_stress not in stress_options:
        current_stress = "Moderate"
    
    stress_level = st.select_slider(
        "Rate your overall stress level",
        options=stress_options,
        value=current_stress
    )
    st.session_state.user_data['stress_level'] = lifestyle_to_numeric(stress_level)

def medical_history_page():
    st.header("Medical History")
    
    if 'medical_history' not in st.session_state.user_data:
        st.session_state.user_data['medical_history'] = {}
    
    for category in MEDICAL_HISTORY:
        st.session_state.user_data['medical_history'][category] = st.text_area(
            f"{category}",
            value=st.session_state.user_data['medical_history'].get(category, ''),
            help="Enter relevant information or 'None' if not applicable"
        )
    
    st.session_state.user_data['smoker'] = st.selectbox(
        "Do you smoke?",
        ["No", "Occasionally", "Regularly"],
        index=["No", "Occasionally", "Regularly"].index(st.session_state.user_data.get('smoker', 'No'))
    )
    
    st.session_state.user_data['alcohol'] = st.selectbox(
        "How often do you consume alcohol?",
        ["Never", "Occasionally", "Weekly", "Daily"],
        index=["Never", "Occasionally", "Weekly", "Daily"].index(st.session_state.user_data.get('alcohol', 'Occasionally'))
    )

def detailed_preferences_page():
    st.header("Detailed Preferences")
    
    if 'detailed_preferences' not in st.session_state.user_data:
        st.session_state.user_data['detailed_preferences'] = {}
    
    prefs = st.session_state.user_data['detailed_preferences']
    
    prefs['wake_time'] = st.time_input("What time do you usually wake up?", value=prefs.get('wake_time', datetime.strptime("07:00", "%H:%M").time()))
    prefs['sleep_time'] = st.time_input("What time do you usually go to sleep?", value=prefs.get('sleep_time', datetime.strptime("22:00", "%H:%M").time()))
    
    prefs['meal_preferences'] = st.multiselect(
        "Do you have any specific meal preferences?",
        ["Vegetarian", "Vegan", "Low-carb", "High-protein", "Gluten-free", "Dairy-free"],
        default=prefs.get('meal_preferences', [])
    )
    
    prefs['food_allergies'] = st.text_input("Do you have any food allergies? (Separate with commas)", value=prefs.get('food_allergies', ''))
    
    prefs['exercise_preferences'] = st.multiselect(
        "What types of exercise do you enjoy?",
        ["Walking", "Running", "Cycling", "Swimming", "Yoga", "Weight Training", "HIIT", "Dance", "Team Sports"],
        default=prefs.get('exercise_preferences', [])
    )
    
    prefs['exercise_time'] = st.selectbox(
        "When do you prefer to exercise?",
        ["Morning", "Afternoon", "Evening"],
        index=["Morning", "Afternoon", "Evening"].index(prefs.get('exercise_time', "Morning"))
    )
    
    prefs['work_hours'] = st.text_input("What are your typical work hours? (e.g., 9am-5pm)", value=prefs.get('work_hours', ''))
    
    prefs['stress_relief'] = st.multiselect(
        "What activities help you relieve stress?",
        ["Meditation", "Reading", "Listening to Music", "Taking a Bath", "Gardening", "Painting/Art", "Cooking"],
        default=prefs.get('stress_relief', [])
    )

def generate_report_page():
    st.header("Generate Your Health and Wellness Report")
    
    if st.button("Generate Report", key="generate_report_button"):  # Added unique key here
        if not all(key in st.session_state.user_data for key in ['name', 'age', 'gender', 'height', 'weight', 'nutrition', 'exercise', 'lifestyle', 'medical_history']):
            st.error("Please complete all sections before generating the report.")
        else:
            with st.spinner("Analyzing your data and generating report..."):
                analysis = {
                    'nutrition': get_gpt_analysis("Analyze the user's nutritional habits and provide 3-5 key insights or recommendations in bullet points.", st.session_state.user_data['nutrition']),
                    'exercise': get_gpt_analysis("Analyze the user's exercise habits and provide 3-5 key insights or recommendations in bullet points.", st.session_state.user_data['exercise']),
                    'lifestyle': get_gpt_analysis("Analyze the user's lifestyle factors and provide 3-5 key insights or recommendations in bullet points.", st.session_state.user_data['lifestyle']),
                    'recommendations': get_gpt_analysis("Provide 5 personalized health and wellness recommendations based on the user's overall profile. Present these as bullet points.", st.session_state.user_data),
                    'weekly_plan': get_gpt_analysis("Create a brief, bullet-point weekly plan for the user, including suggested meals, exercises, and lifestyle adjustments. Keep it concise and actionable.", st.session_state.user_data)
                }
                
                pdf_buffer = generate_pdf_report(st.session_state.user_data, analysis)
                
                st.success("Your Health and Wellness Report has been generated!")
                st.download_button(
                    label="Download Your Report",
                    data=pdf_buffer,
                    file_name="health_wellness_report.pdf",
                    mime="application/pdf"
                )
                
                st.subheader("Summary of Recommendations")
                st.write(analysis['recommendations'])
                
                st.subheader("Your Personalized Weekly Plan")
                st.write(analysis['weekly_plan'])

# Make sure to add unique keys to the navigation buttons in the main() function as well
def main():
    if 'user_data' not in st.session_state:
        st.session_state.user_data = {}
    if 'page' not in st.session_state:
        st.session_state.page = 0
    
    st.title("Health and Wellness Assessment")
    
    pages = [
        introduction_page,
        personal_info_page,
        nutrition_page,
        exercise_page,
        lifestyle_page,
        medical_history_page,
        detailed_preferences_page,
        generate_report_page
    ]
    

    # Convert existing lifestyle data to numeric if it's not already
    if 'lifestyle' in st.session_state.user_data:
        for factor in LIFESTYLE:
            if factor in st.session_state.user_data['lifestyle']:
                st.session_state.user_data['lifestyle'][factor] = lifestyle_to_numeric(st.session_state.user_data['lifestyle'][factor])


    st.sidebar.title("Navigation")
    page_names = ["Introduction", "Personal Information", "Nutrition Assessment", "Exercise Habits", "Lifestyle Factors", "Medical History", "Generate Report"]
    
    for i, page_name in enumerate(page_names):
        if st.sidebar.button(page_name, key=f"nav_{i}"):  # Added unique keys here
            st.session_state.page = i
    
    pages[st.session_state.page]()
    
    col1, col2 = st.columns(2)
    with col1:
        if st.button("Previous", key="prev_button") and st.session_state.page > 0:  # Added unique key
            st.session_state.page -= 1
            st.rerun()
    with col2:
        if st.button("Next", key="next_button") and st.session_state.page < len(pages) - 1:  # Added unique key
            st.session_state.page += 1
            st.rerun()

if __name__ == "__main__":
    main()