chatbot_app.py

import streamlit as st
from datetime import date

st.set_page_config(page_title="Male Intake Chatbot", layout="centered")

st.title("🤖 Male Intake Chatbot")
st.markdown("Welcome! I will guide you through the Male Intake Questionnaire step by step.")

# Initialize session state
if "step" not in st.session_state:
    st.session_state.step = 0
    st.session_state.answers = {}

questions = [
    # Section: General Info
    ("general", "🧑 What is your full name?", "name", "text"),
    ("general", "🎂 How old are you?", "age", "number"),
    ("general", "📅 What is your date of birth?", "dob", "date"),
    ("general", "📧 What is your email address?", "email", "text"),
    ("general", "🏠 What is your home address?", "address", "text"),
    ("general", "🏙️ City?", "city", "text"),
    ("general", "🌍 State/Province?", "state", "text"),
    ("general", "📮 Zip code?", "zip", "text"),

    # Section: Contact Info
    ("contact", "📞 Home phone number?", "phone_home", "text"),
    ("contact", "📱 Cell phone number?", "phone_cell", "text"),
    ("contact", "☎️ Work phone number?", "phone_work", "text"),

    # Section: Emergency
    ("emergency", "👤 Emergency contact name?", "emergency_name", "text"),
    ("emergency", "📖 Relationship to you?", "emergency_relationship", "text"),
    ("emergency", "🏠 Emergency contact home phone?", "emergency_phone_home", "text"),
    ("emergency", "📱 Emergency contact cell phone?", "emergency_phone_cell", "text"),
    ("emergency", "☎️ Emergency contact work phone?", "emergency_phone_work", "text"),

    # Section: Genetic Background
    ("genetic", "🌐 What is your genetic background? (Separate multiple with commas)", "genetic_background", "text"),

    # Section: Nutrition
    ("nutrition", "🥦 Do you follow any special diets? (e.g., Vegan, Low Carb, etc.)", "special_diets", "text"),
    ("nutrition", "⚠️ Do you have sensitivities to certain foods?", "food_sensitivities", "radio"),
    ("nutrition", "🤢 If yes, list the foods and symptoms", "sensitivity_details", "text"),
    ("nutrition", "😖 Do you have an aversion to certain foods?", "food_aversion", "radio"),
    ("nutrition", "📄 If yes, explain the aversion", "aversion_details", "text"),
    ("nutrition", "❤️ Do you crave or binge on any food?", "food_cravings", "radio"),
    ("nutrition", "🍫 If yes, what foods?", "craved_foods", "text"),

    # Section: Meals
    ("meals", "🍽️ Do you eat 3 meals per day?", "eat_3_meals", "radio"),
    ("meals", "📊 If no, how many meals?", "meals_count", "text"),
    ("meals", "😵 Does skipping a meal affect you?", "skip_meal_effect", "radio"),
    ("meals", "🍔 How many meals do you eat out per week? (0-1, 1-3, etc.)", "meals_out_per_week", "text"),

    # Section: Caffeine
    ("caffeine", "☕ Do you drink caffeinated beverages?", "drink_caffeine", "radio"),
    ("caffeine", "☕ Coffee (cups per day)?", "coffee_intake", "text"),
    ("caffeine", "🍵 Tea (cups per day)?", "tea_intake", "text"),
    ("caffeine", "🥤 Soda (cans per day)?", "soda_intake", "text"),
    ("caffeine", "😟 Any adverse reactions to caffeine?", "caffeine_reaction", "radio"),
    ("caffeine", "📄 If yes, explain:", "caffeine_reaction_detail", "text"),

    # Section: Smoking
    ("smoking", "🚬 Do you currently smoke?", "smoke_now", "radio"),
    ("smoking", "📦 Packs per day?", "packs_per_day", "text"),
    ("smoking", "📅 Number of years?", "smoke_years", "text"),
    ("smoking", "📦 What type? (Cigarette, Pipe, etc.)", "smoke_type", "text"),
    ("smoking", "🔁 Have you tried quitting?", "tried_quit", "radio"),
    ("smoking", "📋 If yes, using what methods?", "quit_methods", "text"),

    # Section: Stress
    ("stress", "😰 Do you feel you have too much stress?", "high_stress", "radio"),
    ("stress", "🧘 Can you handle stress easily?", "stress_handling", "radio"),
    ("stress", "💼 Rate work stress (1–10)", "stress_work", "number"),
    ("stress", "👨‍👩‍👧‍👦 Rate family stress (1–10)", "stress_family", "number"),
    ("stress", "💸 Rate financial stress (1–10)", "stress_finance", "number"),

    # More sections like: History, Dental, Men's Health, Family, etc. can be added here similarly...
]

# Step through questions
if st.session_state.step < len(questions):
    section, question_text, field_name, field_type = questions[st.session_state.step]

    st.markdown(f"### Section: {section.capitalize()}")
    if field_type == "text":
        response = st.text_input(question_text)
    elif field_type == "number":
        response = st.number_input(question_text, step=1)
    elif field_type == "date":
        response = st.date_input(question_text, value=date(2000, 1, 1))
    elif field_type == "radio":
        response = st.radio(question_text, ["Yes", "No"])
    else:
        response = st.text_input(question_text)

    if response:
        st.session_state.answers[field_name] = response
        st.session_state.step += 1
        st.experimental_rerun()
else:
    st.success("🎉 You've completed the intake chatbot!")
    st.json(st.session_state.answers)


from reportlab.lib.pagesizes import letter
from reportlab.pdfgen import canvas

# Create a function to save intake form answers to PDF
def save_intake_to_pdf(answers: dict, output_path: str):
    c = canvas.Canvas(output_path, pagesize=letter)
    width, height = letter
    line_height = 14
    x_margin = 50
    y = height - 50

    c.setFont("Helvetica", 12)
    c.drawString(x_margin, y, "Male Intake Questionnaire - Summary")
    y -= line_height * 2

    for key, value in answers.items():
        # Wrap long values
        text = f"{key.replace('_', ' ').capitalize()}: {value}"
        lines = []
        while len(text) > 90:
            split_pos = text.rfind(" ", 0, 90)
            lines.append(text[:split_pos])
            text = text[split_pos+1:]
        lines.append(text)

        for line in lines:
            if y <= 50:
                c.showPage()
                y = height - 50
                c.setFont("Helvetica", 12)
            c.drawString(x_margin, y, line)
            y -= line_height

        y -= 5  # extra spacing between entries

    c.save()
    return output_path

# Example usage
example_answers = {
    "name": "John Doe",
    "age": "35",
    "dob": "1989-03-15",
    "email": "[email protected]",
    "stress_work": 7,
    "smoke_now": "No",
    "food_sensitivities": "Yes",
    "sensitivity_details": "Dairy - causes bloating",
}
pdf_path = "intake_summary_example.pdf"
save_intake_to_pdf(example_answers, pdf_path)