Update app.py

app.py

@@ -113,60 +113,60 @@ def main():
             os.unlink(f.name)
             os.path.exists(f.name)
     if len(data) > 0 :
-        try :
-            embeddings = load_embeddings()
-            sp_docs = split_docs(documents = data)
-            st.write(f"This document have {len(sp_docs)} chunks")
-            sp_docs_list.extend(sp_docs)
-            db = FAISS.from_documents(sp_docs_list, embeddings)
-            memory = ConversationBufferMemory(memory_key="chat_history", 
-                                      return_messages=True, 
-                                      input_key="query", 
-                                      output_key="result")
-            qa_chain = RetrievalQA.from_chain_type(
-                llm = llm,
-                chain_type = "stuff",
-                retriever = db.as_retriever(search_kwargs = {'k':3}), 
-                return_source_documents = True,
-                memory = memory,
-                chain_type_kwargs = {"prompt":qa_prompt})
-            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})
-        
-                start = time.time()
-        
-                response = qa_chain({'query': query})
-                
-                with st.chat_message("assistant"):
-                    st.markdown(response['result'])
-                
-                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']})
-        
-                with st.expander("See the related documents"):
-                    for count, url in enumerate(response['source_documents']):
-                        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() 
-
-        except:
-            st.write("Plaese upload your pdf file.")
+        embeddings = load_embeddings()
+        sp_docs = split_docs(documents = data)
+        st.write(f"This document have {len(sp_docs)} chunks")
+        sp_docs_list.extend(sp_docs)
+    try:
+        db = FAISS.from_documents(sp_docs_list, embeddings)
+        memory = ConversationBufferMemory(memory_key="chat_history", 
+                                  return_messages=True, 
+                                  input_key="query", 
+                                  output_key="result")
+        qa_chain = RetrievalQA.from_chain_type(
+            llm = llm,
+            chain_type = "stuff",
+            retriever = db.as_retriever(search_kwargs = {'k':3}), 
+            return_source_documents = True,
+            memory = memory,
+            chain_type_kwargs = {"prompt":qa_prompt})
+        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})
+    
+            start = time.time()
+    
+            response = qa_chain({'query': query})
+            
+            with st.chat_message("assistant"):
+                st.markdown(response['result'])
+            
+            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']})
+    
+            with st.expander("See the related documents"):
+                for count, url in enumerate(response['source_documents']):
+                    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() 
+
+    except:
+        st.write("Plaese upload your pdf file.")
 
 
 if __name__ == '__main__':