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app.py

@@ -37,14 +37,14 @@ customer_data = pd.DataFrame([{
 
 
 # Single prediction section
-# 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
-#     if response.status_code == 200:
-#         result = response.json()
-#         churn_prediction = result["Prediction"]  # Extract only the value
-#         st.write(f"Based on the information provided, the customer with ID {CustomerID} is likely to {churn_prediction}.")
-#     else:
-#         st.error("Error in API request")
+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
+    if response.status_code == 200:
+        result = response.json()
+        churn_prediction = result["Prediction"]  # Extract only the value
+        st.write(f"Based on the information provided, the customer with ID {CustomerID} is likely to {churn_prediction}.")
+    else:
+        st.error("Error in API request")
 
 
 # Single prediction section
@@ -64,48 +64,48 @@ customer_data = pd.DataFrame([{
         
 
 
-# Function for handling retries with exponential backoff
-def make_request_with_backoff(url, payload, max_retries=5):
-    retry_delay = 2  # Initial retry delay (in seconds)
+# # Function for handling retries with exponential backoff
+# def make_request_with_backoff(url, payload, max_retries=5):
+#     retry_delay = 2  # Initial retry delay (in seconds)
 
-    for attempt in range(max_retries):
-        try:
-            response = requests.post(url, json=payload)
-            response.raise_for_status()  # Ensure successful response
+#     for attempt in range(max_retries):
+#         try:
+#             response = requests.post(url, json=payload)
+#             response.raise_for_status()  # Ensure successful response
 
-            return response.json()  # Return data if request succeeds
+#             return response.json()  # Return data if request succeeds
 
-        except requests.exceptions.RequestException as e:
-            if response.status_code == 429:  # Too many requests
-                st.warning(f"Rate limit exceeded. Retrying in {retry_delay} seconds...")
-                time.sleep(retry_delay)  # Wait before retrying
-                retry_delay *= 2  # Exponential backoff (2s, 4s, 8s, etc.)
-            else:
-                st.error(f"Request failed: {e}")
-                return None
+#         except requests.exceptions.RequestException as e:
+#             if response.status_code == 429:  # Too many requests
+#                 st.warning(f"Rate limit exceeded. Retrying in {retry_delay} seconds...")
+#                 time.sleep(retry_delay)  # Wait before retrying
+#                 retry_delay *= 2  # Exponential backoff (2s, 4s, 8s, etc.)
+#             else:
+#                 st.error(f"Request failed: {e}")
+#                 return None
 
-    st.error("Max retries reached. Try again later.")
-    return None
+#     st.error("Max retries reached. Try again later.")
+#     return None
 
-# Single prediction section with retry mechanism
-if st.button("Predict"):
-    try:
-        print(customer_data)  # Display input data for debugging
+# # Single prediction section with retry mechanism
+# if st.button("Predict"):
+#     try:
+#         print(customer_data)  # Display input data for debugging
         
-        result = make_request_with_backoff(
-            "https://MainiSandeep1987-BackEndFlaskAPITelecomChurnPrediction.hf.space/v1/customer",
-            customer_data.to_dict(orient='records')[0]
-        )
-
-        if result:
-            churn_prediction = result.get("Prediction", "Unknown")  # Safe key lookup
-            customer_id = customer_data.get("CustomerID", "Unknown")  # Prevent undefined errors
-            st.write(f"Based on the information provided, the customer with ID {customer_id} is likely to {churn_prediction}.")
+#         result = make_request_with_backoff(
+#             "https://MainiSandeep1987-BackEndFlaskAPITelecomChurnPrediction.hf.space/v1/customer",
+#             customer_data.to_dict(orient='records')[0]
+#         )
+
+#         if result:
+#             churn_prediction = result.get("Prediction", "Unknown")  # Safe key lookup
+#             customer_id = customer_data.get("CustomerID", "Unknown")  # Prevent undefined errors
+#             st.write(f"Based on the information provided, the customer with ID {customer_id} is likely to {churn_prediction}.")
         
-    except KeyError as e:
-        st.error(f"Unexpected response format: Missing key {e}")
-    except Exception as e:
-        st.error(f"Unexpected error: {e}")
+#     except KeyError as e:
+#         st.error(f"Unexpected response format: Missing key {e}")
+#     except Exception as e:
+#         st.error(f"Unexpected error: {e}")