Update app.py

app.py

@@ -3,7 +3,7 @@ from query import VectaraQuery
 import os
 
 import streamlit as st
-import streamlit_analytics2 as streamlit_analytics
+import streamlit_analytics2
 from PIL import Image
 
 
@@ -42,76 +42,76 @@ def launch_bot():
     st.set_page_config(page_title=cfg.title, layout="wide")
 
 
-    with streamlit_analytics.track():
-        # left side content
-        with st.sidebar:
-            image = Image.open('Vectara-logo.png')
-            st.markdown(f"## Welcome to {cfg.title}\n\n"
-                        f"This demo uses Retrieval Augmented Generation to ask questions about {cfg.source_data_desc}\n\n")
-    
-            st.markdown("---")
-            st.markdown(
-                "## How this works?\n"
-                "This app was built with [Vectara](https://vectara.com).\n"
-                "Vectara's [Indexing API](https://docs.vectara.com/docs/api-reference/indexing-apis/indexing) was used to ingest the data into a Vectara corpus (or index).\n\n"
-                "This app uses Vectara [Chat API](https://docs.vectara.com/docs/console-ui/vectara-chat-overview) to query the corpus and present the results to you, answering your question.\n\n"
-            )
-            st.markdown("---")
-            st.image(image, width=250)
-    
-        st.markdown(f"<center> <h2> Vectara chat demo: {cfg.title} </h2> </center>", unsafe_allow_html=True)
-        st.markdown(f"<center> <h4> {cfg.description} </h4> </center>", unsafe_allow_html=True)
-    
-        
-        if "messages" not in st.session_state.keys():
-            st.session_state.messages = [{"role": "assistant", "content": "How may I help you?"}]
-    
-    
-        if cfg.examples:
-            example_messages = [example.strip() for example in cfg.examples.split(",")]
-        else:
-            example_messages = []
+    # with streamlit_analytics.track():
+    # left side content
+    with st.sidebar:
+        image = Image.open('Vectara-logo.png')
+        st.markdown(f"## Welcome to {cfg.title}\n\n"
+                    f"This demo uses Retrieval Augmented Generation to ask questions about {cfg.source_data_desc}\n\n")
+
+        st.markdown("---")
+        st.markdown(
+            "## How this works?\n"
+            "This app was built with [Vectara](https://vectara.com).\n"
+            "Vectara's [Indexing API](https://docs.vectara.com/docs/api-reference/indexing-apis/indexing) was used to ingest the data into a Vectara corpus (or index).\n\n"
+            "This app uses Vectara [Chat API](https://docs.vectara.com/docs/console-ui/vectara-chat-overview) to query the corpus and present the results to you, answering your question.\n\n"
+        )
+        st.markdown("---")
+        st.image(image, width=250)
+
+    st.markdown(f"<center> <h2> Vectara chat demo: {cfg.title} </h2> </center>", unsafe_allow_html=True)
+    st.markdown(f"<center> <h4> {cfg.description} </h4> </center>", unsafe_allow_html=True)
+
     
-        if len(example_messages) > 0:
-            st.markdown("<h6>Queries To Try:</h6>", unsafe_allow_html=True)
-            cols = st.columns(8)
-        
-        # Display chat messages
-        for message in st.session_state.messages:
-            with st.chat_message(message["role"]):
-                st.write(message["content"])
+    if "messages" not in st.session_state.keys():
+        st.session_state.messages = [{"role": "assistant", "content": "How may I help you?"}]
+
+
+    if cfg.examples:
+        example_messages = [example.strip() for example in cfg.examples.split(",")]
+    else:
+        example_messages = []
+
+    if len(example_messages) > 0:
+        st.markdown("<h6>Queries To Try:</h6>", unsafe_allow_html=True)
+        cols = st.columns(8)
     
-        # User-provided prompt
-        if prompt := st.chat_input():
+    # Display chat messages
+    for message in st.session_state.messages:
+        with st.chat_message(message["role"]):
+            st.write(message["content"])
+
+    # User-provided prompt
+    if prompt := st.chat_input():
+        st.session_state.messages.append({"role": "user", "content": prompt})
+        with st.chat_message("user"):
+            st.write(prompt)
+
+    # Example prompt
+    for i, example in enumerate(example_messages):
+        button_pressed = False
+        with cols[i]:
+            if st.button(example):
+                prompt = example
+                button_pressed = True
+
+        if button_pressed:
             st.session_state.messages.append({"role": "user", "content": prompt})
             with st.chat_message("user"):
                 st.write(prompt)
     
-        # Example prompt
-        for i, example in enumerate(example_messages):
-            button_pressed = False
-            with cols[i]:
-                if st.button(example):
-                    prompt = example
-                    button_pressed = True
-    
-            if button_pressed:
-                st.session_state.messages.append({"role": "user", "content": prompt})
-                with st.chat_message("user"):
-                    st.write(prompt)
-        
-        # Generate a new response if last message is not from assistant
-        if st.session_state.messages[-1]["role"] != "assistant":
-            with st.chat_message("assistant"):
-                if cfg.streaming:
-                    stream = generate_streaming_response(prompt) 
-                    response = st.write_stream(stream) 
-                else:
-                    with st.spinner("Thinking..."):
-                        response = generate_response(prompt)
-                        st.write(response)
-                message = {"role": "assistant", "content": response}
-                st.session_state.messages.append(message)
+    # Generate a new response if last message is not from assistant
+    if st.session_state.messages[-1]["role"] != "assistant":
+        with st.chat_message("assistant"):
+            if cfg.streaming:
+                stream = generate_streaming_response(prompt) 
+                response = st.write_stream(stream) 
+            else:
+                with st.spinner("Thinking..."):
+                    response = generate_response(prompt)
+                    st.write(response)
+            message = {"role": "assistant", "content": response}
+            st.session_state.messages.append(message)
     
 if __name__ == "__main__":
     launch_bot()