updated chatbot ui in streamlit

app.py

@@ -1,13 +1,18 @@
+# https://docs.streamlit.io/knowledge-base/tutorials/build-conversational-apps
+
 import os
+import time
 
 import openai
 import requests
 import streamlit as st
-from streamlit_chat import message
 
 from models import bloom
 from utils.util import *
 
+# from streamlit_chat import message
+
+
 st.title("Welcome to RegBotBeta")
 st.header("Powered by `LlamaIndex🦙` and `OpenAI API`")
 
@@ -30,19 +35,52 @@ if api_key:
 
 st.write("---")
 if index:
-    input_text = st.text_area("Ask your question")
-
-    if input_text:
-        if st.button("Ask"):
-            st.session_state.messages.append(("User", input_text))
-            with st.spinner("Processing your query..."):
-                bot_response = get_response(index, input_text)
-            print("bot: ", bot_response)
-            st.session_state.messages.append(("Bot", bot_response))
-
-# Display previous messages
-msg_key = 0
-for sender, msg in st.session_state.messages[::-1]:
-    is_user = sender == "User"
-    message(str(msg), is_user, key=str(msg_key) + f"_{sender}")
-    msg_key += 1
+    # Display chat messages from history on app rerun
+    for message in st.session_state.messages:
+        with st.chat_message(message["role"]):
+            st.markdown(message["content"])
+
+    if prompt := st.chat_input("Say something"):
+        # Display user message in chat message container
+        st.chat_message("user").markdown(prompt)
+
+        # Add user message to chat history
+        st.session_state.messages.append({"role": "user", "content": prompt})
+
+        with st.spinner("Processing your query..."):
+            bot_response = get_response(index, prompt)
+
+        print("bot: ", bot_response)
+
+        # Display assistant response in chat message container
+        with st.chat_message("assistant"):
+            message_placeholder = st.empty()
+            full_response = ""
+
+            # simulate the chatbot "thinking" before responding
+            # (or stream its response)
+            for chunk in bot_response.split():
+                full_response += chunk + " "
+                time.sleep(0.05)
+
+                # add a blinking cursor to simulate typing
+                message_placeholder.markdown(full_response + "▌")
+
+            message_placeholder.markdown(full_response)
+            # st.markdown(response)
+
+        # Add assistant response to chat history
+        st.session_state.messages.append(
+            {"role": "assistant", "content": full_response}
+        )
+
+        # Scroll to the bottom of the chat container
+        # st.markdown(
+        #     """
+        #     <script>
+        #     const chatContainer = document.getElementsByClassName("css-1n76uvr")[0];
+        #     chatContainer.scrollTop = chatContainer.scrollHeight;
+        #     </script>
+        #     """,
+        #     unsafe_allow_html=True,
+        # )

requirements.txt

@@ -8,5 +8,4 @@ openai
 faiss-cpu
 python-dotenv
 streamlit
-streamlit-chat
 huggingface_hub

utils/util.py

@@ -5,29 +5,23 @@ def validate(token: str):
     api_endpoint = "https://api.openai.com/v1/chat/completions"
     api_key = token
 
-    headers = {
-        "Content-Type" : "application/json",
-        "Authorization": f"Bearer {api_key}"
-    }
+    headers = {"Content-Type": "application/json", "Authorization": f"Bearer {api_key}"}
 
-    messages = [
-        {"role": "user", "content": "Say this is a test!"}
-    ]
+    messages = [{"role": "user", "content": "Say this is a test!"}]
 
-    data = {
-        "model": "gpt-3.5-turbo",
-        "messages": messages
-    }
+    data = {"model": "gpt-3.5-turbo", "messages": messages}
 
     response = requests.post(api_endpoint, json=data, headers=headers)
     return response
 
+
 def create_index(model):
     index = model.initialize_index("bloomLlama")
     return index
 
+
 def get_response(vector_index, query_str):
     print("query_str: ", query_str)
     query_engine = vector_index.as_query_engine()
     response = query_engine.query(query_str)
-    return response
+    return str(response)