app.py

import os
import streamlit as st
import pandas as pd
import requests

# API Key for fetching mental health articles
news_api_key = "fe1e6bcbbf384b3e9220a7a1138805e0"  # Replace with your News API key

@st.cache_data
def load_data(file):
    return pd.read_csv(file)

def provide_observed_advice(data):
    """Generate detailed advice based on the user's data."""
    advice = []

    # Mental Health Advice
    if data['depression'] > 7 or data['anxiety_level'] > 7:
        advice.append(
            "You are experiencing high levels of depression or anxiety. It’s critical to prioritize your mental health. "
            "Please consider scheduling an appointment with a mental health professional. Additionally, practice mindfulness or meditation daily, "
            "engage in hobbies you enjoy, and spend time in nature to help reduce negative emotions."
        )
    elif data['depression'] > 5 or data['anxiety_level'] > 5:
        advice.append(
            "You are showing moderate signs of depression or anxiety. Try incorporating regular physical activity into your routine, "
            "such as walking, yoga, or light exercise. Build a support system by reaching out to trusted friends or family members. "
            "Consider journaling your thoughts or keeping a gratitude diary to refocus your mind on positive aspects of your life."
        )

    if data['stress_level'] > 7:
        advice.append(
            "High stress levels detected. Stress can negatively affect your physical and mental health. To manage stress effectively, "
            "practice relaxation techniques such as deep breathing, progressive muscle relaxation, or guided imagery. "
            "Identify your stressors and try to address them one by one. Seek professional counseling if stress becomes overwhelming."
        )

    if data['mental_health_history'] > 5:
        advice.append(
            "Your mental health history indicates potential ongoing challenges. Consistent therapy or counseling might provide the support you need. "
            "Stay proactive in tracking your mood changes and avoid isolating yourself when you're feeling low."
        )

    # Physical Health Advice
    if data['headache'] > 5:
        advice.append(
            "Frequent headaches reported. Ensure you’re staying hydrated and maintaining a balanced diet. Avoid prolonged screen time "
            "and practice proper posture to reduce physical strain. If headaches persist, consult a doctor to rule out underlying conditions."
        )

    if data['blood_pressure'] > 5:
        advice.append(
            "Elevated blood pressure detected. Reduce your salt intake and focus on a heart-healthy diet rich in fruits, vegetables, and lean proteins. "
            "Engage in light exercises like walking or swimming, and monitor your blood pressure regularly. Consult a doctor for long-term management strategies."
        )

    if data['sleep_quality'] < 5:
        advice.append(
            "Poor sleep quality reported. Establish a consistent bedtime routine, avoid caffeine and heavy meals before sleeping, and create a dark, quiet sleeping environment. "
            "Try relaxation techniques like reading or listening to soothing music before bed. Seek medical advice if sleep problems persist."
        )

    if data['breathing_problem'] > 5:
        advice.append(
            "Breathing problems reported. If this is linked to allergies or asthma, ensure you’re avoiding triggers and using prescribed medications. "
            "Practice deep breathing exercises or try yoga to improve lung function. Consider consulting a pulmonologist for further evaluation."
        )

    # Environmental and Social Advice
    if data['noise_level'] > 7:
        advice.append(
            "High noise levels detected in your environment. Use noise-canceling headphones or soundproofing techniques to create a quieter space. "
            "Spend some time in peaceful locations, such as parks or libraries, to recharge mentally."
        )

    if data['living_conditions'] < 5 or data['safety'] < 5:
        advice.append(
            "Suboptimal living conditions or low safety levels detected. Seek resources or community support to improve your living environment. "
            "Consider reaching out to local authorities or organizations for assistance in addressing safety concerns."
        )

    # Academic and Social Support Advice
    if data['study_load'] > 7:
        advice.append(
            "High academic workload reported. Create a detailed study plan to prioritize tasks and allocate sufficient time for breaks. "
            "Avoid multitasking and focus on one task at a time to improve efficiency. Consider seeking help from teachers or peers if you feel overwhelmed."
        )

    if data['future_career_concerns'] > 7:
        advice.append(
            "High concerns about future career prospects detected. Break down your career goals into smaller, actionable steps. "
            "Research potential career paths, network with professionals, and consider attending career counseling for guidance."
        )

    if data['social_support'] < 5:
        advice.append(
            "Low social support detected. Building meaningful connections can significantly improve your well-being. "
            "Join social groups, clubs, or community activities that align with your interests. Don’t hesitate to reach out to friends or family for emotional support."
        )

    if data['peer_pressure'] > 7:
        advice.append(
            "High peer pressure detected. Stay true to your values and goals. Politely decline requests that make you uncomfortable, "
            "and remember that it's okay to say no. Surround yourself with individuals who respect your boundaries."
        )

    if data['extracurricular_activities'] < 5:
        advice.append(
            "Low engagement in extracurricular activities detected. Participating in activities such as sports, arts, or volunteering can help you develop new skills, "
            "reduce stress, and expand your social circle. Consider trying out an activity that interests you."
        )

    return advice

def main():
    st.set_page_config(page_title="Student Well-being Advisor", layout="wide")
    st.title("🔍 Analyze Your Well-being")

    # File uploader
    uploaded_file = st.file_uploader("Upload your dataset (CSV)", type=["csv"])
    if uploaded_file:
        df = load_data(uploaded_file)
        st.write("### Dataset Preview:")
        st.dataframe(df.head())

        # Validate dataset columns
        required_columns = [
            'anxiety_level', 'self_esteem', 'mental_health_history', 'depression',
            'headache', 'blood_pressure', 'sleep_quality', 'breathing_problem',
            'noise_level', 'living_conditions', 'safety', 'basic_needs',
            'academic_performance', 'study_load', 'teacher_student_relationship',
            'future_career_concerns', 'social_support', 'peer_pressure',
            'extracurricular_activities', 'bullying', 'stress_level'
        ]
        missing_columns = [col for col in required_columns if col not in df.columns]
        
        if missing_columns:
            st.error(f"The uploaded dataset is missing the following required columns: {', '.join(missing_columns)}")
        else:
            # Handle missing values in the dataset
            if df.isnull().values.any():
                st.warning("The dataset contains missing values. Rows with missing values will be skipped.")
                df = df.dropna()

            st.markdown("### Select a Row for Analysis")
            selected_row = st.selectbox(
                "Select a row (based on index) to analyze:",
                options=df.index,
                format_func=lambda x: f"Row {x} - Depression: {df.loc[x, 'depression']}, Anxiety: {df.loc[x, 'anxiety_level']}, Stress: {df.loc[x, 'stress_level']}",
            )

            # Extract data for the selected row
            row_data = df.loc[selected_row].to_dict()

            # Show extracted details
            st.write("### Selected User Details:")
            st.json(row_data)

            # Generate advice
            st.subheader("🔔 Personalized Advice")
            advice = provide_observed_advice(row_data)
            if advice:
                for i, tip in enumerate(advice, 1):
                    st.write(f"📌 **{i}.** {tip}")
            else:
                st.warning("No specific advice available based on this user's data.")

if __name__ == "__main__":
    main()