Uploading food classifier demo

app.py

@@ -1,5 +1,5 @@
 # Lets Launch Sagar's demo on web
-#  YAML metadata looks for app.py by default
+# YAML metadata looks for app.py by default
 # app.py import packages , define gradio function, create demo, run demo with demo.launch 
 # %%writefile  magic pyhton function 
 # Create Model Demo: Gradio App: inputs - model -output in gradio app
@@ -10,6 +10,10 @@
 # 4 Return the output from the pipeline in step 3 as a formatted dictionary with the format {"label_1": probability_1, "label_2: probability_2"}
 ######################################################################################################################
 # Import necessary packages
+import os
+# This looks for the 'Secret' you just added in the Settings tab
+hf_token = os.getenv("HF_TOKEN")
+
 import pprint
 from pathlib import Path