Update app.py

app.py

@@ -10,13 +10,13 @@ from pathlib import Path
 from time import sleep
 import random
 import string
-
+import sys
 import os
 from dotenv import load_dotenv
 load_dotenv()
 
 st.set_page_config(page_title="Cheers! Open AI Doc-Chat Assistant", layout="wide")
-st.subheader("Cheers! Open AI Doc-Chat Assistant: Life Enhancing with AI!")
+st.subheader("Open AI Doc-Chat Assistant: Life Enhancing with AI!")
 
 css_file = "main.css"
 with open(css_file) as f:
@@ -25,6 +25,7 @@ with open(css_file) as f:
 HUGGINGFACEHUB_API_TOKEN = os.getenv("HUGGINGFACEHUB_API_TOKEN")
 
 documents=[]
+wechat_image= "WeChatCode.jpg"
 
 def generate_random_string(length):
     letters = string.ascii_lowercase
@@ -32,8 +33,6 @@ def generate_random_string(length):
 random_string = generate_random_string(20)
 directory_path=random_string
 
-wechat_image= "WeChatCode.jpg"
-
 st.sidebar.markdown(
     """
     <style>
@@ -60,6 +59,9 @@ st.markdown(
     """, unsafe_allow_html=True
 )
 
+question = st.text_input("Enter your query here:")
+display_output_text = st.checkbox("Check AI Repsonse", key="key_checkbox", help="Check me to get AI Response.")
+
 with st.sidebar:    
     pdf_files = st.file_uploader("Upload file and start AI Doc-Chat.", type=['pdf'], accept_multiple_files=True)
     st.write("Disclaimer: This app is for information purpose only. NO liability could be claimed against whoever associated with this app in any manner. User should consult a qualified legal professional for legal advice.")
@@ -75,11 +77,10 @@ with st.sidebar:
             with open(file_path, 'wb') as f:
                 f.write(pdf_file.read())
             st.success(f"File '{pdf_file.name}' saved successfully.")
-    
-try:
-    documents = SimpleDirectoryReader(directory_path).load_data()
-except Exception as e:
-    print("waiting for path creation.")
+        documents = SimpleDirectoryReader(directory_path).load_data()    
+    else:
+        print("waiting for path creation.")
+        sys.exit()
 
 embed_model = LangchainEmbedding(HuggingFaceEmbeddings(model_name='sentence-transformers/all-MiniLM-L6-v2'))
 
@@ -92,27 +93,20 @@ new_index = VectorStoreIndex.from_documents(
     service_context=service_context,
 )
 
-new_index.storage_context.persist("directory_path")
-
-storage_context = StorageContext.from_defaults(persist_dir="directory_path")
-
-loadedindex = load_index_from_storage(storage_context=storage_context, service_context=service_context)
-
-query_engine = loadedindex.as_query_engine()
-
-while True:
-    try:
-        question = st.text_input("Enter your query here:")
-        print("Your query:\n"+question)
-        if question.strip().isspace() or question == "" or question.strip() == "" or question.isspace():            
-            break        
-        elif question=="exit":
-            break
-        elif question!="":
-          with st.spinner("AI Thinking...Please wait a while to Cheers!"):
-            initial_response = query_engine.query(question)
-            temp_ai_response=str(initial_response)
-            final_ai_response=temp_ai_response.partition('<|end|>')[0]             
-            st.write("AI Response:\n\n"+final_ai_response)
-    except Exception as e:
-        st.stop()
+if question !="" and not question.strip().isspace() and not question == "" and not question.strip() == "" and not question.isspace():
+    if display_output_text==True:
+      with st.spinner("AI Thinking...Please wait a while to Cheers!"):
+        new_index.storage_context.persist("directory_path")
+        storage_context = StorageContext.from_defaults(persist_dir="directory_path")
+        loadedindex = load_index_from_storage(storage_context=storage_context, service_context=service_context)
+        query_engine = loadedindex.as_query_engine() 
+        initial_response = query_engine.query(question)
+        temp_ai_response=str(initial_response)
+        final_ai_response=temp_ai_response.partition('<|end|>')[0]
+        st.write("AI Response:\n\n"+final_ai_response)
+    else:
+        print("Check the Checkbox to get AI Response.")
+        sys.exit()          
+else:
+    print("Please enter your question first.")
+    st.stop()