Update app.py

app.py

@@ -337,6 +337,28 @@ if __name__ == '__main__':
     
     client, collection_name, llm, dense_model, sparse_model = load_models_and_documents()
 
+    if "messages" not in st.session_state:
+        st.session_state.messages = []
+
+    for message in st.session_state.messages:
+        with st.chat_message(message["role"]):
+            st.markdown(message["content"])
+
+    if prompt := st.chat_input("Message Video Game Assistant"):
+        st.chat_message("user").markdown(prompt)
+        st.session_state.messages.append({"role": "user", "content": prompt})
+
+        ai_response = main(prompt, client, collection_name, llm, dense_model, sparse_model)
+        response = f"Echo: {ai_response}"
+        with st.chat_message("assistant"):
+            message_placeholder = st.empty()
+            full_response = ""
+            for chunk in re.split(r'(\s+)', response):
+                full_response += chunk + " "
+                time.sleep(0.01)
+                message_placeholder.markdown(full_response + "▌")
+        st.session_state.messages.append({"role": "assistant", "content": full_response})
+
     st.sidebar.title("Upload your file")
     uploaded_files = st.sidebar.file_uploader("Choose a file", accept_multiple_files=True, type=['docx', 'doc', 'odt', 'pptx', 'ppt', 'xlsx', 'csv', 'tsv', 'eml', 'msg', 'rtf', 'epub', 'html', 'xml', 'pdf', 'png', 'jpg', 'heic','txt'])
     print(f'uploaded-files : {uploaded_files}')
@@ -358,26 +380,4 @@ if __name__ == '__main__':
                 dense_embeddings, 
                 sparse_embeddings
             )
-        )
-
-    if "messages" not in st.session_state:
-        st.session_state.messages = []
-
-    for message in st.session_state.messages:
-        with st.chat_message(message["role"]):
-            st.markdown(message["content"])
-
-    if prompt := st.chat_input("Message Video Game Assistant"):
-        st.chat_message("user").markdown(prompt)
-        st.session_state.messages.append({"role": "user", "content": prompt})
-
-        ai_response = main(prompt, client, collection_name, llm, dense_model, sparse_model)
-        response = f"Echo: {ai_response}"
-        with st.chat_message("assistant"):
-            message_placeholder = st.empty()
-            full_response = ""
-            for chunk in re.split(r'(\s+)', response):
-                full_response += chunk + " "
-                time.sleep(0.01)
-                message_placeholder.markdown(full_response + "▌")
-        st.session_state.messages.append({"role": "assistant", "content": full_response})
+        )