Update app.py

app.py

@@ -58,21 +58,21 @@ def find_sentences(query):
     saved = corpus[corpus_id]
     return saved
 
-
-message_history = [{"text":"Let's find out the best task for your use case! Tell me about your use case :)", "is_user":False}]
-
 st.subheader("If you don't know how to build your machine learning product for your use case, Taskmaster is here to help you! 🪄✨")
-st.write("Hint: Try to ask your use case in a question form.")
-for msg in message_history:
-    message(msg["text"], is_user = msg["is_user"])   # display all the previous message
 
-placeholder = st.empty()  # placeholder for latest message
+message("Let's find out the best task for your use case! Tell me about your use case :)")
+
+#message_history = [{"text":"Let's find out the best task for your use case! Tell me about your use case :)", "is_user":False}]
+#for msg in message_history:
+#    message(msg["text"], is_user = msg["is_user"]) 
+#placeholder = st.empty()  # placeholder for latest message
 
 
 input = st.text_input("Ask me 🤗")
 if input:
+    message(input, is_user = True)
 
-    message_history.append({"text":input, "is_user" : True})
+    #message_history.append({"text":input, "is_user" : True})
 
     model_answer = find_sentences(input)
 
@@ -84,17 +84,14 @@ if input:
             response_templates = [f"I think that {key} is the best task for this 🤩 Check out the page 👉🏼 {url}", f"I think you should use {key} 🪄 Check it out here 👉🏼 {url}", f"I think {key} should work for you 🤓 Check out the page 👉🏼 {url}"]
     
             bot_answer = random.choice(response_templates)
-            message_history.append({"text":bot_answer, "is_user" : False})
+            message(bot_answer)
+            #message_history.append({"text":bot_answer, "is_user" : False})
     if key_exists == False:
         fallback_template = ["I didn't get the question 🧐 Could you please ask again? Try 'What should I use for detecting masks in an image?'",
                                  "Hmm, not sure I know the answer, maybe you could ask differently? 🤓",
                                  "Sorry, I didn't understand you, maybe you could ask differently? 🤓 Try asking 'What should I use to extract name in a document' 🤗"]
         bot_answer = random.choice(fallback_template)
-        message_history.append({"text":bot_answer, "is_user" : False})
-    
-    with placeholder.container():
-        last_message = message_history[-1]
-        if last_message:
-            message(last_message["text"], last_message["is_user"])
-          
-    
+        message(bot_answer)
+        #message_history.append({"text":bot_answer, "is_user" : False})
+   
+