Update app.py

app.py

@@ -399,21 +399,20 @@ if uploaded_image:
         # Display the image
         st.image(input_image, caption="Uploaded Image.", use_container_width=True)
 
-        if recipe_submit:
-            predictions = classifyImage(input_image)
-            print("Predictions: ", predictions)
-            fpredictions = ""
-        
-            # Show the top predictions with percentages
-            st.write("Top Predictions:")
-            for class_name, confidence in predictions:
-                if int(confidence) > 0.05:
-                    fpredictions += f"{class_name}: {confidence:.2f}%,"
-                if int(confidence) > 5:
-                    class_name = class_name.replace("_", " ")
-                    class_name = class_name.title()
-                    st.markdown(f"*{class_name}*: {confidence:.2f}%")
-            print(fpredictions)
+        predictions = classifyImage(input_image)
+        print("Predictions: ", predictions)
+        fpredictions = ""
+    
+        # Show the top predictions with percentages
+        st.write("Top Predictions:")
+        for class_name, confidence in predictions:
+            if int(confidence) > 0.05:
+                fpredictions += f"{class_name}: {confidence:.2f}%,"
+            if int(confidence) > 5:
+                class_name = class_name.replace("_", " ")
+                class_name = class_name.title()
+                st.markdown(f"*{class_name}*: {confidence:.2f}%")
+        print(fpredictions)
 
     # call openai to pick the best classification result based on query
     openAICall = [
@@ -459,6 +458,7 @@ if uploaded_image:
             RAGresponse = get_response(predictions[0][0])
         print("RAGresponse: ", RAGresponse)
         display_response(RAGresponse)
+        print("COL 2 WQEQOEWIQOIEWQWOIJQEWIJQWQEPJIEWQPIJEQPJIWEQPEWQEWQPOKWEQPOKWQEPOKWQOPKEWQOPKQQEWOPKWQEWQE")
 elif uploaded_image is not None:
     with col1:
         # Open the image