Update app.py

app.py

@@ -1,112 +1,114 @@
 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):
-    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()
+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()