File size: 5,781 Bytes
aeb7752
868289f
3da247b
2745b9c
5733740
b382f24
 
 
868289f
 
 
 
 
0bb182a
868289f
 
dac5058
0bb182a
dac5058
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
43471b3
dac5058
b382f24
 
dac5058
b382f24
41c6728
b382f24
 
 
 
 
 
 
 
 
 
 
 
 
e1e605f
868289f
 
9ea96c4
240a1f8
 
 
 
 
 
9ea96c4
 
 
 
 
 
 
 
 
 
 
240a1f8
 
 
 
 
 
 
 
0bb182a
868289f
 
 
 
240a1f8
868289f
0bb182a
868289f
240a1f8
 
 
 
 
 
 
 
0bb182a
868289f
 
 
 
 
 
 
 
 
 
 
 
240a1f8
 
868289f
240a1f8
 
 
 
 
5117e78
b382f24
 
 
 
e1e605f
0bb182a
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
import streamlit as st
import pandas as pd
import os
from groq import Groq

# Set the GROQ API key from environment variable
groq_api_key = os.getenv("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")  # Make sure the GROQ API key is set in your environment

# 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 = []

    # High depression and anxiety with low stress-relief activities
    if data['depression'] > 7 and data['anxiety'] > 7:
        advice.append("You seem to be experiencing high levels of both depression and anxiety. It's important to consider professional mental health support. You might also benefit from engaging in calming activities like deep breathing, mindfulness, or yoga.")

    # Moderate depression or anxiety
    elif data['depression'] > 5 or data['anxiety'] > 5:
        advice.append("You are showing moderate levels of depression or anxiety. It would be helpful to develop healthy coping strategies like maintaining a regular sleep schedule, engaging in physical activity, and reaching out to friends or family for support.")

    # High isolation and low stress-relief activities
    if data['isolation'] > 7 and data['stress_relief_activities'] < 5:
        advice.append("It seems you are feeling isolated, and your engagement in stress-relief activities is low. It's important to connect with friends or join community groups. Incorporate activities that help alleviate stress, such as walking, journaling, or meditation.")

    # High future insecurity
    if data['future_insecurity'] > 7:
        advice.append("You are feeling a significant amount of insecurity about the future. It can be helpful to break down your larger goals into smaller, manageable tasks. Seeking career counseling or mentorship could provide valuable guidance and reduce anxiety about the future.")

    # Overall low engagement in stress-relief activities
    if data['stress_relief_activities'] < 5:
        advice.append("Your engagement in stress-relief activities is quite low. It's essential to engage in activities that reduce stress and promote mental wellness, such as hobbies, physical exercise, and relaxation techniques like deep breathing or yoga.")

    return advice

# Function to use the GROQ API for health queries (e.g., for symptoms or wellness queries)
def get_health_advice_from_groq(query):
    try:
        # Sending request to GROQ API
        chat_completion = groq_api_key.chat.completions.create(
            messages=[{
                "role": "user",
                "content": query
            }],
            model="llama-3.3-70b-versatile",
        )

        # Extracting and returning the response from GROQ API
        response_content = chat_completion.choices[0].message.content
        return response_content
    except Exception as e:
        st.error(f"Error with GROQ API: {str(e)}")
        return "Could not fetch advice from GROQ API."

# Streamlit app layout
def main():
    # Set a background color and style
    st.markdown(
        """
        <style>
        .stApp {
            background-color: #F4F4F9;
        }
        .stButton>button {
            background-color: #6200EE;
            color: white;
            font-size: 18px;
        }
        .stSlider>div>div>span {
            color: #6200EE;
        }
        .stTextInput>div>div>input {
            background-color: #E0E0E0;
        }
        </style>
        """,
        unsafe_allow_html=True
    )

    # Title and header
    st.title("🌟 **Student Health Advisory Assistant** 🌟")
    st.markdown("### **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.markdown("### **Input Your Details**")
        gender = st.selectbox("πŸ”Ή Gender", ["Male", "Female"], help="Select your gender.")
        age = st.slider("πŸ”Ή Age", 18, 35, step=1)
        depression = st.slider("πŸ”Ή Depression Level (1-10)", 1, 10)
        anxiety = st.slider("πŸ”Ή Anxiety Level (1-10)", 1, 10)
        isolation = st.slider("πŸ”Ή Isolation Level (1-10)", 1, 10)
        future_insecurity = st.slider("πŸ”Ή Future Insecurity Level (1-10)", 1, 10)
        stress_relief_activities = st.slider("πŸ”Ή 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("πŸ” Get Observed Advice", key="advice_btn"):
            st.subheader("πŸ”” **Health Advice Based on Observations** πŸ””")
            advice = provide_observed_advice(user_data)
            if advice:
                for i, tip in enumerate(advice, 1):
                    st.write(f"πŸ“Œ {i}. {tip}")
            else:
                st.warning("No advice available based on your inputs.")

            # Fetch additional health advice from GROQ API
            st.subheader("πŸ’¬ **Additional Health Advice from GROQ** πŸ’¬")
            groq_advice = get_health_advice_from_groq("Provide wellness tips for managing anxiety and stress.")
            st.write(f"πŸ’‘ {groq_advice}")

if __name__ == "__main__":
    main()