comment chat system

app.py

@@ -202,12 +202,11 @@ def load_embeddings():
     return embeddings
 
 def main():
-    msgs = StreamlitChatMessageHistory(key="langchain_messages")
-    print(msgs)
-    if "messages" not in st.session_state:
-        st.session_state.messages = []
+    # msgs = StreamlitChatMessageHistory(key="langchain_messages")
+    # print(msgs)
+    # if "messages" not in st.session_state:
+    #     st.session_state.messages = []
 
-    data = []
     # DB_FAISS_UPLOAD_PATH = "vectorstores/db_faiss"
     st.header("DOCUMENT QUESTION ANSWERING IS2")
     # directory = "data"
@@ -254,6 +253,15 @@ def main():
             return_source_documents = True,
             memory = memory,
             chain_type_kwargs = {"prompt":qa_prompt}) 
+
+        query = st.text_input("ASK ABOUT THE DOCS:")        
+        if query:
+            start = time.time()
+            response = qa_chain({'query': query})
+            st.write(response["result"])
+            end = time.time()
+            st.write("Respone time:",int(end-start),"sec")
+    
         # qa_chain = ConversationalRetrievalChain(
         #     retriever =db.as_retriever(search_kwargs={'k':2}), 
         #     question_generator=question_generator,
@@ -264,44 +272,44 @@ def main():
         #     #get_chat_history=lambda h :h
         # )
 
-        for message in st.session_state.messages:
-            with st.chat_message(message["role"]):
-                st.markdown(message["content"])
+        # for message in st.session_state.messages:
+        #     with st.chat_message(message["role"]):
+        #         st.markdown(message["content"])
 
-            # Accept user input
-        if query := st.chat_input("What is up?"):
-            # Display user message in chat message container
-            with st.chat_message("user"):
-                st.markdown(query)
-            # Add user message to chat history
-            st.session_state.messages.append({"role": "user", "content": query})
+        #     # Accept user input
+        # if query := st.chat_input("What is up?"):
+        #     # Display user message in chat message container
+        #     with st.chat_message("user"):
+        #         st.markdown(query)
+        #     # Add user message to chat history
+        #     st.session_state.messages.append({"role": "user", "content": query})
 
-            start = time.time()
+        #     start = time.time()
 
-            response = qa_chain({'query': query})
+        #     response = qa_chain({'query': query})
 
-            # url_list = set([i.metadata['source']  for i in response['source_documents']])
-            #print(f"condensed quesion : {question_generator.run({'chat_history': response['chat_history'], 'question' : query})}")
+        #     # url_list = set([i.metadata['source']  for i in response['source_documents']])
+        #     #print(f"condensed quesion : {question_generator.run({'chat_history': response['chat_history'], 'question' : query})}")
             
-            with st.chat_message("assistant"):
-                st.markdown(response['result'])
+        #     with st.chat_message("assistant"):
+        #         st.markdown(response['result'])
             
-            end = time.time()
-            st.write("Respone time:",int(end-start),"sec")
-            print(response)
+        #     end = time.time()
+        #     st.write("Respone time:",int(end-start),"sec")
+        #     print(response)
                     
-            # Add assistant response to chat history
-            st.session_state.messages.append({"role": "assistant", "content": response['result']})
+        #     # Add assistant response to chat history
+        #     st.session_state.messages.append({"role": "assistant", "content": response['result']})
 
-            # with st.expander("See the related documents"):
-            #     for count, url in enumerate(url_list):
-            #         #url_reg = regex_source(url)
-            #         st.write(str(count+1)+":", url)
+        #     # with st.expander("See the related documents"):
+        #     #     for count, url in enumerate(url_list):
+        #     #         #url_reg = regex_source(url)
+        #     #         st.write(str(count+1)+":", url)
 
-        clear_button = st.button("Start new convo")
-        if clear_button :
-            st.session_state.messages = []
-            qa_chain.memory.chat_memory.clear() 
+        # clear_button = st.button("Start new convo")
+        # if clear_button :
+        #     st.session_state.messages = []
+        #     qa_chain.memory.chat_memory.clear() 
             
   
 if __name__ == '__main__':