added feedback button

streamlit_app.py

@@ -1,6 +1,9 @@
 import streamlit as st
+from streamlit_feedback import streamlit_feedback
+
 import os
 import pandas as pd
+import time
 
 import openai
 
@@ -102,12 +105,16 @@ with st.sidebar:
 
 if "init" not in st.session_state.keys():
     st.session_state.init = {"warm_start": "No"}
+    st.session_state.feedback = False
 
 # Store LLM generated responses
 if "messages" not in st.session_state.keys():
     st.session_state.messages = [{"role": "assistant", 
                                   "content": "How may I assist you today?"}]
 
+if "feedback_key" not in st.session_state:
+    st.session_state.feedback_key = 0
+
 # Display or clear chat messages
 for message in st.session_state.messages:
     with st.chat_message(message["role"]):
@@ -122,7 +129,11 @@ def clear_chat_history():
                                    embedding_model=embedding_model,
                                    system_content=system_content)
     chat_engine.reset()
+
 st.sidebar.button("Clear Chat History", on_click=clear_chat_history)
+if st.sidebar.button("I want to submit a feedback!"):
+    st.session_state.feedback = True
+    st.session_state.feedback_key += 1  # overwrite feedback component
 
 @st.cache_resource
 def get_document_object(input_files):
@@ -172,6 +183,10 @@ def generate_llm_response(prompt_input):
     response = chat_engine.stream_chat(prompt_input)
     return response
 
+def handle_feedback(user_response):
+    st.toast("✔️ Feedback received!")
+    st.session_state.feedback = False
+
 # Warm start
 if st.session_state.init["warm_start"] == "No":
     clear_chat_history()
@@ -196,5 +211,14 @@ if st.session_state.messages[-1]["role"] != "assistant":
                 full_response += token
                 placeholder.markdown(full_response)
             placeholder.markdown(full_response)
+
     message = {"role": "assistant", "content": full_response}
-    st.session_state.messages.append(message)
+    st.session_state.messages.append(message)
+
+if st.session_state.feedback:
+    result = streamlit_feedback(
+                feedback_type="thumbs",
+                optional_text_label="[Optional] Please provide an explanation",
+                on_submit=handle_feedback,
+                key=f"feedback_{st.session_state.feedback_key}"
+    )