app.py

import streamlit as st
import pandas as pd
from groq import Groq
import os

# Initialize Groq client
client = Groq(api_key="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")

# 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):
    # [Your existing logic]
    pass

# Function to fetch health articles from Groq's API
def get_health_articles(query):
    response = client.chat.completions.create(
        messages=[
            {"role": "system", "content": "You are a helpful assistant."},
            {"role": "user", "content": f"Provide a list of recent health articles about {query} with titles and URLs."}
        ],
        model="llama-3.3-70b-versatile",
    )
    articles = response.choices[0].message.content
    return articles

# Streamlit app layout
def main():
    st.title("Student Health Advisory Assistant")
    st.subheader("Analyze your well-being and get personalized 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 based on user inputs
        if st.button("Get Observed Advice"):
            st.subheader("Health Advice Based on Observations")
            advice = provide_observed_advice(user_data)
            for i, tip in enumerate(advice, 1):
                st.write(f"{i}. {tip}")

            # Fetch related health articles based on user input
            st.subheader("Related Health Articles")
            query = "mental health anxiety depression isolation stress relief"
            articles = get_health_articles(query)
            st.write(articles)

if __name__ == "__main__":
    main()