Update app.py

app.py

@@ -1,23 +1,41 @@
 import gradio as gr
-import requests
+import pickle
+import numpy as np
 
-# URL of your FastAPI endpoint
-API_URL = "http://4.186.39.227/predict"
+# Load the preprocessor and model
+with open("processor.pkl", "rb") as f:
+    processor = pickle.load(f)
 
-# Function to call the FastAPI endpoint with customer data
+with open("model.pkl", "rb") as f:
+    model = pickle.load(f)
+
+# The original FastAPI endpoint URL (not active now)
+# API_URL = "http://4.186.39.227/predict"
+
+# Function to preprocess input data and predict customer segment
 def predict_customer_segment(data):
-    response = requests.post(API_URL, json=data)
-    if response.status_code == 200:
-        cluster_label = response.json()["cluster_label"]
-        cluster_descriptions = {
-            0: "Low Value Customer",
-            1: "Medium Value Customer",
-            2: "High Value Customer",
-            3: "Premium Customer"
-        }
-        return cluster_descriptions.get(cluster_label, "Unknown Cluster")
-    else:
-        return f"Error: {response.json()['detail']}"
+    # Preprocess the data
+    processed_data = processor.transform(np.array([[
+        data["CUST_ID"], data["BALANCE"], data["BALANCE_FREQUENCY"], data["PURCHASES"],
+        data["ONEOFF_PURCHASES"], data["INSTALLMENTS_PURCHASES"], data["CASH_ADVANCE"],
+        data["PURCHASES_FREQUENCY"], data["ONEOFF_PURCHASES_FREQUENCY"], data["PURCHASES_INSTALLMENTS_FREQUENCY"],
+        data["CASH_ADVANCE_FREQUENCY"], data["CASH_ADVANCE_TRX"], data["PURCHASES_TRX"],
+        data["CREDIT_LIMIT"], data["PAYMENTS"], data["MINIMUM_PAYMENTS"], data["PRC_FULL_PAYMENT"],
+        data["TENURE"]
+    ]]))
+
+    # Predict the cluster label using the model
+    cluster_label = model.predict(processed_data)[0]
+
+    # Map the cluster label to a human-readable description
+    cluster_descriptions = {
+        0: "Low Value Customer",
+        1: "Medium Value Customer",
+        2: "High Value Customer",
+        3: "Premium Customer"
+    }
+
+    return cluster_descriptions.get(cluster_label, "Unknown Cluster")
 
 # Function to handle predictions from form input
 def predict_from_form(CUST_ID, BALANCE, BALANCE_FREQUENCY, PURCHASES, ONEOFF_PURCHASES, INSTALLMENTS_PURCHASES, CASH_ADVANCE, PURCHASES_FREQUENCY, ONEOFF_PURCHASES_FREQUENCY, PURCHASES_INSTALLMENTS_FREQUENCY, CASH_ADVANCE_FREQUENCY, CASH_ADVANCE_TRX, PURCHASES_TRX, CREDIT_LIMIT, PAYMENTS, MINIMUM_PAYMENTS, PRC_FULL_PAYMENT, TENURE):