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Dockerfile

@@ -11,6 +11,6 @@ COPY . .
 RUN pip3 install -r requirements.txt
 
 # Define the command to run the Streamlit app on port 8501 and make it accessible externally
-CMD ["streamlit", "run", "app.py", "--server.port=8501", "--server.address=0.0.0.0", "--server.enableXsrfProtection=false"]
+CMD ["streamlit", "run", "app.py", "--server.port=7860", "--server.address=0.0.0.0", "--server.enableXsrfProtection=false"]
 
 # NOTE: Disable XSRF protection for easier external access in order to make batch predictions

app.py

@@ -68,10 +68,10 @@ input_data = pd.DataFrame([{
 
 # Make prediction when the "Predict" button is clicked
 if st.button("Predict"):
-    response = requests.post("https://<username>-<repo_id>.hf.space/v1/salesrevenue", json=input_data.to_dict(orient='records')[0])  # Send data to Flask API
+    response = requests.post("https://sureshsharma4747--ProductStoreSalesPricePredictionBackend.hf.space/v1/salesrevenue", json=input_data.to_dict(orient='records')[0])  # Send data to Flask API
     if response.status_code == 200:
-        prediction = response.json()['Predicted total revenue (in dollars)']
-        st.success(f"Predicted total revenue(in dollars): {prediction}")
+        prediction = response.json()['Predicted total sales']
+        st.success(f"Predicted total sales: {prediction}")
     else:
         st.error("Error making prediction.")
 
@@ -84,7 +84,7 @@ 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://<username>-<repo_id>.hf.space/v1/salesrevenuebatch", files={"file": uploaded_file})  # Send file to Flask API
+        response = requests.post("https://sureshsharma4747--ProductStoreSalesPricePredictionBackend.hf.space/v1/salesrevenuebatch", files={"file": uploaded_file})  # Send file to Flask API
         if response.status_code == 200:
             predictions = response.json()
             st.success("Batch predictions completed!")