added sample questions

app.py

@@ -1,12 +1,14 @@
 
-from omegaconf import OmegaConf
-import streamlit as st
 import os
 from PIL import Image
 import sys
 import pandas as pd
 import requests
 
+from omegaconf import OmegaConf
+import streamlit as st
+from streamlit_pills import pills
+
 from dotenv import load_dotenv
 load_dotenv(override=True)
 
@@ -139,6 +141,15 @@ def initialize_agent(_cfg):
 def toggle_logs():
     st.session_state.show_logs = not st.session_state.show_logs
 
+def show_example_questions():        
+    if len(st.session_state.example_messages) > 0 and st.session_state.first_turn:            
+        selected_example = pills("Queries to Try:", st.session_state.example_messages, index=None)
+        if selected_example:
+            st.session_state.ex_prompt = selected_example
+            st.session_state.first_turn = False
+            return True
+    return False
+
 def launch_bot():
     def reset():
         st.session_state.messages = [{"role": "assistant", "content": initial_prompt, "avatar": "🦖"}]
@@ -146,6 +157,7 @@ def launch_bot():
         st.session_state.log_messages = []
         st.session_state.prompt = None
         st.session_state.show_logs = False
+        st.session_state.first_turn = True
 
     st.set_page_config(page_title="Financial Assistant", layout="wide")
     if 'cfg' not in st.session_state:
@@ -153,8 +165,12 @@ def launch_bot():
             'customer_id': str(os.environ['VECTARA_CUSTOMER_ID']),
             'corpus_id': str(os.environ['VECTARA_CORPUS_ID']),
             'api_key': str(os.environ['VECTARA_API_KEY']),
+            'examples': os.environ.get('QUERY_EXAMPLES', None)
         })
         st.session_state.cfg = cfg
+        st.session_state.ex_prompt = None
+        example_messages = [example.strip() for example in cfg.examples.split(",")] if cfg.examples else []
+        st.session_state.example_messages = [em for em in example_messages if len(em)>0]
         reset()
 
     cfg = st.session_state.cfg
@@ -193,8 +209,18 @@ def launch_bot():
         with st.chat_message(message["role"], avatar=message["avatar"]):
             st.write(message["content"])
 
+    example_container = st.empty()
+    with example_container:
+        if show_example_questions():
+            example_container.empty()
+            st.rerun()
+
     # User-provided prompt
-    if prompt := st.chat_input():
+    if st.session_state.ex_prompt:
+        prompt = st.session_state.ex_prompt
+    else:
+        prompt = st.chat_input()
+    if prompt:
         st.session_state.messages.append({"role": "user", "content": prompt, "avatar": '🧑‍💻'})
         st.session_state.prompt = prompt  # Save the prompt in session state
         st.session_state.log_messages = []
@@ -202,6 +228,7 @@ def launch_bot():
         with st.chat_message("user", avatar='🧑‍💻'):
             print(f"Starting new question: {prompt}\n")
             st.write(prompt)
+        st.session_state.ex_prompt = None
         
     # Generate a new response if last message is not from assistant
     if st.session_state.prompt:
@@ -212,8 +239,10 @@ def launch_bot():
             message = {"role": "assistant", "content": res, "avatar": '🤖'}
             st.session_state.messages.append(message)
             st.markdown(res)
-            st.session_state.prompt = None
-
+        st.session_state.ex_prompt = None
+        st.session_state.prompt = None
+        st.rerun()
+    
     log_placeholder = st.empty()
     with log_placeholder.container():
         if st.session_state.show_logs:

requirements.txt

@@ -1,5 +1,6 @@
 omegaconf==2.3.0
-streamlit==1.32.2
 pydantic==1.10.15
 python-dotenv==1.0.1
+streamlit==1.32.2
+streamlit_pills==0.3.0
 git+https://{GITHUB_TOKEN}@github.com/vectara/vectara-agent.git