Update app.py

app.py

@@ -315,8 +315,7 @@ with st.expander("**What is FOOD CHAIN?**"):
         Made by the Classify Crew: [Contact List](https://linktr.ee/classifycrew)
         """
     )
-if not query and not uploaded_image:
-    st.warning("Please input an image and/or a prompt.", icon=':material/no_meals:')
+
 #################
 
 sample_RAG = {
@@ -391,7 +390,7 @@ with col2:
         display_response(sample_RAG)
 
 # Image Classification Section
-if uploaded_image:
+if recipe_submit and uploaded_image:
     with col1:
         # Open the image
         input_image = Image.open(uploaded_image)
@@ -458,33 +457,34 @@ 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
-        input_image = Image.open(uploaded_image)
+else:
+    st.warning("Please upload an image before submitting.", icon=':material/no_meals:')
+# elif uploaded_image is not None:
+#     with col1:
+#         # Open the image
+#         input_image = Image.open(uploaded_image)
     
-        # Display the image
-        st.image(input_image, caption="Uploaded Image.", use_container_width=True)
+#         # Display the image
+#         st.image(input_image, caption="Uploaded Image.", use_container_width=True)
     
-        # Classify the image and display the result
-        predictions = classifyImage(input_image)
-        fpredictions = ""
+#         # Classify the image and display the result
+#         predictions = classifyImage(input_image)
+#         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)
-
-elif recipe_submit:
-    with col2:
-        response = get_response(query)
-        print(response)
-        display_response(response)
+#         # 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)
+
+# elif recipe_submit:
+#     with col2:
+#         response = get_response(query)
+#         print(response)
+#         display_response(response)