Create app.py

app.py

@@ -0,0 +1,38 @@
+import streamlit as st
+import pandas as pd
+import joblib
+from huggingface_hub import hf_hub_download
+
+st.set_page_config(page_title="Wellness Tourism Prediction", layout="centered")
+
+st.title("Wellness Tourism Purchase Prediction")
+st.write("Predict whether a customer will purchase the Wellness Tourism Package.")
+
+# Load model from Hugging Face Model Hub
+model_path = hf_hub_download(
+    repo_id="AngadSi/wellness-purchase-prediction-model",
+    filename="wellness_purchase_model.joblib",
+    repo_type="model"
+)
+
+model = joblib.load(model_path)
+
+# UI inputs
+age = st.number_input("Age", min_value=18, max_value=100, value=30)
+income = st.number_input("Monthly Income", min_value=0, value=6000)
+trips = st.number_input("Number of Trips", min_value=0, value=2)
+pitch_score = st.slider("Pitch Satisfaction Score", 1, 100, 80)
+
+if st.button("Predict"):
+    df = pd.DataFrame([{
+        "Age": age,
+        "MonthlyIncome": income,
+        "NumberOfTrips": trips,
+        "PitchSatisfactionScore": pitch_score
+    }])
+
+    pred = model.predict(df)[0]
+    prob = model.predict_proba(df)[0][1]
+
+    st.success(f"Prediction: {'Will Purchase' if pred == 1 else 'Will Not Purchase'}")
+    st.info(f"Purchase Probability: {round(prob, 2)}")