Upload folder using huggingface_hub

app.py

@@ -77,7 +77,7 @@ input_data = pd.DataFrame([{
 if st.button("Predict"):
     print(input_data.to_dict(orient='records')[0])
     # Send the input data to the Flask API for prediction
-    response = requests.post("https://anithajk-SuperKart-Model-Deployment.hf.space/v1/productsale", json=input_data.to_dict(orient='records')[0])  # Send data to Flask API
+    response = requests.post("https://anithajk-SuperKartDecesionMakingModelBackend.hf.space/v1/productsale", json=input_data.to_dict(orient='records')[0])  # Send data to Flask API
     if response.status_code == 200:
         prediction = response.json()['Predicted Revenue (in dollars)']
         st.success(f"Predicted Revenue (in dollars): {prediction}")
@@ -93,7 +93,7 @@ uploaded_file = st.file_uploader("Upload CSV file for batch prediction", type=["
 # Make batch prediction when the "Predict Batch" button is clicked
 if uploaded_file is not None:
     if st.button("Predict Batch"):
-        response = requests.post("https://anithajk-SuperKart-Model-Deployment.hf.space/v1/productsalebatch", files={"file": uploaded_file})  # Send file to Flask API
+        response = requests.post("https://anithajk-SuperKartDecesionMakingModelBackend.hf.space/v1/productsalebatch", files={"file": uploaded_file})  # Send file to Flask API
         if response.status_code == 200:
             predictions = response.json()
             st.success("Batch predictions completed!")