Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,40 +1,57 @@
-import altair as alt
-import numpy as np
-import pandas as pd
 import streamlit as st
-
-"""
-# Welcome to Streamlit!
-
-Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:.
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
-
-In the meantime, below is an example of what you can do with just a few lines of code:
-"""
-
-num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
-num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
-
-indices = np.linspace(0, 1, num_points)
-theta = 2 * np.pi * num_turns * indices
-radius = indices
-
-x = radius * np.cos(theta)
-y = radius * np.sin(theta)
-
-df = pd.DataFrame({
-    "x": x,
-    "y": y,
-    "idx": indices,
-    "rand": np.random.randn(num_points),
-})
-
-st.altair_chart(alt.Chart(df, height=700, width=700)
-    .mark_point(filled=True)
-    .encode(
-        x=alt.X("x", axis=None),
-        y=alt.Y("y", axis=None),
-        color=alt.Color("idx", legend=None, scale=alt.Scale()),
-        size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
-    ))
+import pandas as pd
+import numpy as np
+import joblib
+
+# Load the Model
+try:
+    model = joblib.load('src/introvert_model.joblib')
+except FileNotFoundError:
+    st.error("Model file not found.")
+    st.stop()
+
+# Page 
+st.set_page_config(page_title="Personality Predictor", page_icon="🧠")
+
+st.title("🧠 Introvert vs. Extrovert Predictor")
+st.write("This application predicts whether you are an **Introvert** or an **Extrovert** based on your social habits and preferences.")
+
+# User Inputs 
+with st.sidebar:
+    st.header("Please Enter Your Details")
+    time_spent_alone = st.slider("Time Spent Alone (Hours/Day)", 0.0, 10.0, 3.5)
+    social_event_attendance = st.slider("Social Event Attendance (Frequency 0-10)", 0, 10, 5)
+    going_outside = st.slider("Frequency of Going Out (0-10)", 0, 10, 5)
+    friends_circle_size = st.number_input("Friends Circle Size", min_value=0, max_value=20, value=5)
+    post_frequency = st.slider("Social Media Post Frequency (0-10)", 0, 10, 2)
+    stage_fear_input = st.radio("Do you have Stage Fear?", ["Yes", "No"])
+    drained_input = st.radio("Do you feel drained after socializing?", ["Yes", "No"])
+
+# Feature Engineering
+stage_fear = 1 if stage_fear_input == "Yes" else 0
+drained = 1 if drained_input == "Yes" else 0
+social_to_alone_ratio = social_event_attendance / (time_spent_alone + 1)
+social_volume = friends_circle_size * going_outside
+
+# Create DataFrame
+input_data = pd.DataFrame({
+    'Time_spent_Alone': [time_spent_alone],
+    'Stage_fear': [stage_fear],
+    'Social_event_attendance': [social_event_attendance],
+    'Going_outside': [going_outside],
+    'Drained_after_socializing': [drained],
+    'Friends_circle_size': [friends_circle_size],
+    'Post_frequency': [post_frequency],
+    'Social_to_Alone_Ratio': [social_to_alone_ratio],
+    'Social_Volume': [social_volume]})
+
+# Prediction
+st.subheader("Prediction Result")
+if st.button("Analyze Personality"):
+    prediction = model.predict(input_data)[0]
+    if prediction == 1:
+        st.success("Result: **INTROVERT**")
+        st.info("You likely prefer staying in your own space and recharging your energy through solitude.")
+    else:
+        st.info("Result: **EXTROVERT**")
+        st.success("You likely gain energy from social environments and enjoy engaging with the outside world.")