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app.py

@@ -22,7 +22,7 @@ TotalCharges = st.number_input("Total Charges", min_value=0.0, value=600.0)
 # Convert categorical inputs to match model training
 customer_data = {
     'SeniorCitizen': 1 if SeniorCitizen == "Yes" else 0,
-    'Partner':Partner,
+    'Partner': Partner,
     'Dependents': Dependents,
     'tenure': tenure,
     'PhoneService': PhoneService,
@@ -33,9 +33,13 @@ customer_data = {
     'TotalCharges': TotalCharges
 }
 
-
+# Single Prediction
 if st.button("Predict", type='primary'):
-    response = requests.post("https://MainiSandeep1987-BackEndFlaskAPITelecomChurnPrediction.hf.space/v1/customer", json=customer_data)    # enter user name and space name before running the cell
+    response = requests.post(
+        "https://MainiSandeep1987-BackEndFlaskAPITelecomChurnPrediction.hf.space/v1/customer",
+        json=customer_data
+    )  # Send data to Flask API
+    
     if response.status_code == 200:
         result = response.json()
         churn_prediction = result["Prediction"]  # Extract only the value
@@ -43,32 +47,32 @@ if st.button("Predict", type='primary'):
     else:
         st.error("Error in API request")
 
-# Batch Prediction
+# Batch Prediction Section
 st.subheader("Batch Prediction")
-
 file = st.file_uploader("Upload CSV file", type=["csv"])
 
-# batch_input = {
-#     'file': batch_churn_dataset.to_csv(header=True, index=False).encode('utf-8')
-# }
-
 if file is not None:
     if st.button("Predict for Batch", type='primary'):
-         headers = {
+        try:
+            headers = {
                 # "Authorization": "Bearer YOUR_API_KEY",  # Replace with actual API key if needed
                 "Content-Type": "multipart/form-data"
             }
-        file_data = {"file": ("batch.csv", file.getvalue(), "text/csv")}  # Properly format file
-        response = requests.post(
+            file_data = {"file": ("batch.csv", file.getvalue(), "text/csv")}  # Properly format file
+
+            response = requests.post(
                 "https://MainiSandeep1987-BackEndFlaskAPITelecomChurnPrediction.hf.space/v1/customerbatch",
                 files=file_data,
                 headers=headers
-        )
-             
-        ##response = requests.post("https://MainiSandeep1987-BackEndFlaskAPITelecomChurnPrediction.hf.space/v1/customerbatch", files={"file": file.getvalue()})    # enter user name and space name before running the cell
-        if response.status_code == 200:
+            )
+
+            response.raise_for_status()  # Raise error if request fails
+
             result = response.json()
             st.header("Batch Prediction Results")
             st.write(result)
-        else:
-            st.error("Error in API request")
+
+        except requests.exceptions.RequestException as e:
+            st.error(f"Error in API request: {e}")
+        except Exception as e:
+            st.error(f"Unexpected error: {e}")