app.py

import streamlit as st
import pandas as pd
import requests

# Function to load and preprocess data
@st.cache_data
def load_data(file):
    df = pd.read_csv(file)
    return df

# Function to provide detailed health advice
def provide_detailed_advice(data):
    advice = []

    if data['depression'] > 7:
        advice.append("You have high levels of depression. Consider consulting a mental health professional. Practice self-care activities like mindfulness, journaling, and physical exercise.")
    elif data['depression'] > 5:
        advice.append("Your depression levels are moderate. Engage in uplifting activities, maintain a healthy routine, and seek social support.")

    if data['anxiety'] > 7:
        advice.append("High levels of anxiety detected. Use breathing exercises, yoga, and reduce caffeine intake. Consulting a therapist is highly recommended.")
    elif data['anxiety'] > 5:
        advice.append("Moderate anxiety levels observed. Focus on managing stress, maintaining proper sleep, and practicing relaxation techniques.")

    if data['isolation'] > 7:
        advice.append("You might be feeling isolated. Try joining community groups, reaching out to friends, or participating in social activities.")
    elif data['isolation'] > 5:
        advice.append("Moderate isolation detected. Schedule regular social interactions to maintain mental wellness.")

    if data['future_insecurity'] > 7:
        advice.append("You have significant concerns about the future. Break large goals into smaller tasks, and consider career counseling or mentorship.")
    elif data['future_insecurity'] > 5:
        advice.append("Moderate future insecurity observed. Building a concrete plan and seeking guidance from trusted professionals can help.")

    if data['stress_relief_activities'] < 5:
        advice.append("Low engagement in stress-relief activities. Incorporate activities like walking, meditation, or pursuing hobbies into your routine.")

    return advice

# Function to fetch health articles using the GROC API
def get_health_articles(query, api_key):
    api_key = "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"
    url = f"https://api.groc.com/search?q={query}"
    headers = {"Authorization": f"Bearer {api_key}"}

    try:
        response = requests.get(url, headers=headers)
        response.raise_for_status()
        data = response.json()  # Assuming the API returns JSON
        articles = [{"title": item["title"], "url": item["url"]} for item in data.get("results", [])]
        return articles
    except requests.exceptions.RequestException as e:
        st.error(f"Error fetching articles: {e}")
        return []

# Streamlit app layout
def main():
    st.title("Student Health Advisory Assistant")
    st.subheader("Analyze your well-being and get advice")

    # GROC API key input
    api_key = st.text_input("Enter your GROC API Key", type="password")
    if not api_key:
        st.warning("Please enter your GROC API Key to fetch related articles.")
        return

    # File upload
    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())

        # User input for analysis
        st.header("Input Your Details")
        gender = st.selectbox("Gender", ["Male", "Female"])
        age = st.slider("Age", 18, 35, step=1)
        depression = st.slider("Depression Level (1-10)", 1, 10)
        anxiety = st.slider("Anxiety Level (1-10)", 1, 10)
        isolation = st.slider("Isolation Level (1-10)", 1, 10)
        future_insecurity = st.slider("Future Insecurity Level (1-10)", 1, 10)
        stress_relief_activities = st.slider("Stress Relief Activities Level (1-10)", 1, 10)

        # Data dictionary for advice
        user_data = {
            "gender": gender,
            "age": age,
            "depression": depression,
            "anxiety": anxiety,
            "isolation": isolation,
            "future_insecurity": future_insecurity,
            "stress_relief_activities": stress_relief_activities,
        }

        # Provide advice
        if st.button("Get Detailed Advice"):
            st.subheader("Health Advice")
            advice = provide_detailed_advice(user_data)
            for i, tip in enumerate(advice, 1):
                st.write(f"{i}. {tip}")

            # Fetch articles from GROC API
            st.subheader("Related Health Articles")
            query = "mental health, stress relief, social well-being"
            articles = get_health_articles(query, api_key)
            if articles:
                for article in articles:
                    st.write(f"- [{article['title']}]({article['url']})")
            else:
                st.write("No articles found. Please check your API key or internet connection.")

if __name__ == "__main__":
    main()