Update app.py

app.py

@@ -2,7 +2,6 @@ import streamlit as st
 import requests
 import os
 from streamlit_chat import message
-import random
 
 
 @st.cache
@@ -14,15 +13,23 @@ def query(payload):
     response = requests.post(API_URL, headers=headers, json=payload)
     return response.json()
 
-message("Let's find out the best task for your use case! Tell me about your use case :)") 
+
+
+st.title("Let's find out the best task for your use case! Tell me about your use case :)") 
 context = "To extract information from documents, use sentence similarity task. To do sentiment analysis from tweets, use text classification task. To detect masks from images, use object detection task. To extract information from invoices, use named entity recognition from token classification task."
 
-#for message_ in message_history:
-#        message(message_)   # display all the previous message
 
-#placeholder = st.empty()  # placeholder for latest message
 
-input = st.text_input("Ask me 🤗")
+ for message_ in message_history:
+        message(message_)   # display all the previous message
+
+placeholder = st.empty()  # placeholder for latest message
+input = st.text_input("You:")
+message_history.append(input)
+
+with placeholder.container():
+    message(message_history[-1]) # display the latest message
+
 message(input, is_user=True)  # align's the message to the right
 
 data = query(
@@ -30,16 +37,15 @@ data = query(
         "inputs": {
             "question": input,
             "context": context,
-        },
-    "options" : {"wait_for_model": True},
+        }
     }
 )
 try:
     bot_answer = data["answer"]
-    response_templates = [f"{bot_answer} is the best task for this 🤩", f"I think you should use {bot_answer} 🪄", f"I think {bot_answer} should work for you 🤓"]
-    message(random.choice(response_templates))
+    message(f"{bot_answer} is the best task for this :)")
 
 except:
-    message("I'm listening 👀 ")
+    message("Inference API is currently loading!")
+