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import os
import streamlit as st
import pandas as pd
import requests
import urllib.parse
# Fetch the News API key from the environment variable
news_api_key = "fe1e6bcbbf384b3e9220a7a1138805e0" # Replace with your News API key
# Check if the API key is available, if not show an error and stop
if not news_api_key:
st.error("NEWS_API_KEY is not set. Please provide a valid API key.")
st.stop()
# 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 based on user data
def provide_observed_advice(data):
advice = []
if data['depression'] > 7 and data['anxiety'] > 7:
advice.append(
"You seem to be experiencing high levels of both depression and anxiety. Consider professional mental health support and calming activities like deep breathing, mindfulness, or yoga."
)
if data['depression'] > 5 or data['anxiety'] > 5:
advice.append(
"Moderate levels of depression or anxiety detected. Maintain a regular sleep schedule, engage in physical activity, and reach out for support."
)
if data['isolation'] > 7 and data['stress_relief_activities'] < 5:
advice.append(
"Feeling isolated with low stress-relief activities. Connect with friends or community groups and try journaling or meditation."
)
if data['future_insecurity'] > 7:
advice.append(
"Significant insecurity about the future detected. Break down goals into smaller tasks, and consider career counseling or mentorship."
)
if data['stress_relief_activities'] < 5:
advice.append(
"Low engagement in stress-relief activities. Try hobbies, physical exercise, or relaxation techniques like yoga."
)
return advice
# Function to fetch health articles from News API based on the query
def get_health_articles(query):
url = f"https://newsapi.org/v2/everything?q={query}&apiKey={news_api_key}"
try:
response = requests.get(url)
response.raise_for_status()
data = response.json()
articles = [{"title": item["title"], "url": item["url"]} for item in data.get("articles", [])]
return articles
except requests.exceptions.RequestException as err:
st.error(f"Error fetching articles: {err}. Please check your internet connection.")
return []
# Streamlit app layout
def main():
st.set_page_config(page_title="Student Health Advisory Assistant", layout="wide")
# Sidebar for navigation
with st.sidebar:
st.header("Navigation")
option = st.radio("Go to", ["Home", "Analyze Your Well-being", "Health Articles"])
# Home page
if option == "Home":
st.title("π Welcome to the Student Health Advisory Assistant π")
st.image("https://via.placeholder.com/800x300?text=Student+Health+Advisory", use_column_width=True)
st.markdown("### Helping you analyze your well-being and provide personalized advice for a healthier mind.")
st.markdown(
"""
- Upload your dataset for in-depth analysis.
- Input your details to receive personalized advice.
- Browse the latest health-related articles.
"""
)
# Well-being analysis
elif option == "Analyze Your Well-being":
st.title("π Analyze Your Well-being")
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())
with st.expander("Enter Your Details"):
gender = st.selectbox("πΉ Gender", ["Male", "Female"])
age = st.slider("πΉ Age", 18, 35, step=1)
depression = st.slider("πΉ Depression Level (1-10)", 1, 10)
anxiety = st.slider("πΉ Anxiety Level (1-10)", 1, 10)
isolation = st.slider("πΉ Isolation Level (1-10)", 1, 10)
future_insecurity = st.slider("πΉ Future Insecurity Level (1-10)", 1, 10)
stress_relief_activities = st.slider("πΉ Stress Relief Activities Level (1-10)", 1, 10)
user_data = {
"gender": gender,
"age": age,
"depression": depression,
"anxiety": anxiety,
"isolation": isolation,
"future_insecurity": future_insecurity,
"stress_relief_activities": stress_relief_activities,
}
if st.button("Get Observed Advice"):
st.subheader("π Health Advice Based on Observations")
advice = provide_observed_advice(user_data)
for i, tip in enumerate(advice, 1):
st.write(f"π {i}. {tip}")
# Health articles
elif option == "Health Articles":
st.title("π° Browse Health Articles")
query = st.text_input("Search for health topics (e.g., anxiety, stress relief)")
if query and st.button("Search Articles"):
articles = get_health_articles(query)
for article in articles:
st.write(f"π [{article['title']}]({article['url']})")
if __name__ == "__main__":
main()
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