Upload folder using huggingface_hub

app.py

@@ -33,7 +33,7 @@ customer_data = {
 
 if st.button("Predict", type='primary'):
     #response = requests.post("https://<user_name>-<space_name>.hf.space/v1/customer", json=customer_data)    # enter user name and space name before running the cell
-    response = requests.post("https://kjdeka-Frontend-1.hf.space/v1/customer", json=customer_data)    # enter user name and space name before running the cell
+    response = requests.post("https://kjdeka-Backend-1.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
@@ -48,7 +48,7 @@ file = st.file_uploader("Upload CSV file", type=["csv"])
 if file is not None:
     if st.button("Predict for Batch", type='primary'):
         #response = requests.post("https://<user_name>-<space_name>.hf.space/v1/customerbatch", files={"file": file})    # enter user name and space name before running the cell
-        response = requests.post("https://kjdeka-Frontend-1.hf.space/v1/customerbatch", files={"file": file})    # enter user name and space name before running the cell
+        response = requests.post("https://kjdeka-Backend-1.hf.space/v1/customerbatch", files={"file": file})    # enter user name and space name before running the cell
         if response.status_code == 200:
             result = response.json()
             st.header("Batch Prediction Results")