app.py

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

# Retrieve the GROC API Key from environment variable
GROC_API_KEY = "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"

# Check if the API key is missing
if not GROC_API_KEY:
    st.error("API key is missing. Please set the GROC_API_KEY environment variable.")
else:
    # 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):
        url = f"https://api.groc.com/search?q={query}"
        headers = {"Authorization": f"Bearer {GROC_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")

        # 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)
                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()