Update app.py

app.py

@@ -4,61 +4,39 @@ import os
 
 import streamlit as st
 from PIL import Image
-from functools import partial
-
-def generate_response(question):
-    response = st.session_state.vq.submit_query(question)
-    return response
-
-def generate_streaming_response(question):
-    response = st.session_state.vq.submit_query_streaming(question)
-    return response
-
-
-def set_query(q: str):
-    st.session_state.messages.append({"role": "user", "content": q})
-    if st.session_state.cfg.streaming:
-        stream = generate_streaming_response(q) 
-        response = st.write_stream(stream)
-    else:
-        with st.spinner("Thinking..."):
-            response = generate_response(q)
-            st.write(response)
-    message = {"role": "assistant", "content": response}
-    st.session_state.messages.append(message)
-
 
 
 def launch_bot():
+    def generate_response(question):
+        response = vq.submit_query(question)
+        return response
+    
+    def generate_streaming_response(question):
+        response = vq.submit_query_streaming(question)
+        return response
 
     if 'cfg' not in st.session_state:
         corpus_ids = str(os.environ['corpus_ids']).split(',')
-        questions = list(eval(os.environ['examples']))
         cfg = OmegaConf.create({
             'customer_id': str(os.environ['customer_id']),
             'corpus_ids': corpus_ids,
             'api_key': str(os.environ['api_key']),
             'title': os.environ['title'],
             'description': os.environ['description'],
-            'examples': questions,
             'source_data_desc': os.environ['source_data_desc'],
             'streaming': os.environ.get('streaming', False),
-            'prompt_name': os.environ.get('prompt_name', None),
-            
+            'prompt_name': os.environ.get('prompt_name', None)
         })
         st.session_state.cfg = cfg
         st.session_state.vq = VectaraQuery(cfg.api_key, cfg.customer_id, cfg.corpus_ids, cfg.prompt_name)
 
     cfg = st.session_state.cfg
     vq = st.session_state.vq
-    
     st.set_page_config(page_title=cfg.title, layout="wide")
-    sidebar, main_content, questions_col = st.columns([2, 5, 3])  # Adjust column widths as needed
 
     # left side content
-    with sidebar:
+    with st.sidebar:
         image = Image.open('Vectara-logo.png')
-        st.image(image, width=250)
         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")
 
@@ -70,42 +48,37 @@ def launch_bot():
             "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)
 
-    with questions_col:
-        st.markdown("### Sample Questions")
-        for example in st.session_state.cfg.examples:
-            st.button(example, on_click=partial(set_query, example), use_container_width=True)
+    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)
 
-    with main_content:    
-        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 "messages" not in st.session_state.keys():
-            st.session_state.messages = [{"role": "assistant", "content": "How may I help you?"}]
-    
-        # Display chat messages
-        for message in st.session_state.messages:
-            with st.chat_message(message["role"]):
-                st.write(message["content"])
+    # 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)
     
-        # 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)
-        
-        # 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()