added spinners

app.py

@@ -42,14 +42,20 @@ for msg in st.session_state.langchain_messages:
     with st.chat_message(msg.type, avatar=avatar):
         st.markdown(msg.content)
 
-if prompt := st.chat_input(placeholder="What do you need to know about SUP'COM ?"):
-    st.chat_message("user").write(prompt)
+
+prompt = st.chat_input(placeholder="What do you need to know about SUP'COM ?")
+
+if prompt :
+    with st.chat_message("user"):
+        st.write(prompt)
+    
     with st.chat_message("assistant", avatar="🦜"):
         message_placeholder = st.empty()
         full_response = ""
         # Define the basic input structure for the chains
         input_dict = {"input": prompt}
 
+
         with collect_runs() as cb:
             for chunk in chain.stream(input_dict, config={"tags": ["SUP'ASSISTANT"]}):
                 full_response += chunk.content
@@ -58,23 +64,24 @@ if prompt := st.chat_input(placeholder="What do you need to know about SUP'COM ?
             st.session_state.run_id = cb.traced_runs[0].id
         message_placeholder.markdown(full_response)
 
-        run_id = st.session_state.run_id
-        question_embedding = get_embeddings(prompt)
-        answer_embedding = get_embeddings(full_response)
-        # Add question and answer to Qdrant
-        qdrant_client.upload_collection(            
-            collection_name="chat-history",
-            payload=[
-                {"text": prompt, "type": "question", "question_ID": run_id},
-                {"text": full_response, "type": "answer", "question_ID": run_id}
-            ],
-            vectors=[
-                question_embedding,
-                answer_embedding,
-            ],
-            parallel=4,
-            max_retries=3,
-            )
+        with st.spinner("Just a sec! Dont enter prompts while loading pelase!"):
+            run_id = st.session_state.run_id
+            question_embedding = get_embeddings(prompt)
+            answer_embedding = get_embeddings(full_response)
+            # Add question and answer to Qdrant
+            qdrant_client.upload_collection(            
+                collection_name="chat-history",
+                payload=[
+                    {"text": prompt, "type": "question", "question_ID": run_id},
+                    {"text": full_response, "type": "answer", "question_ID": run_id}
+                ],
+                vectors=[
+                    question_embedding,
+                    answer_embedding,
+                ],
+                parallel=4,
+                max_retries=3,
+                )
 
         
 
@@ -106,35 +113,37 @@ if st.session_state.get("run_id"):
 
             # Record the feedback with the formulated feedback type string
             # and optional comment
-            feedback_record = client.create_feedback(
-                run_id,
-                feedback_type_str,
-                score=score,
-                comment=feedback.get("text"),
-            )
-            st.session_state.feedback = {
-                "feedback_id": str(feedback_record.id),
-                "score": score,
-            }
+            with st.spinner("Just a sec! Dont enter prompts while loading pelase!"):
+                feedback_record = client.create_feedback(
+                    run_id,
+                    feedback_type_str,
+                    score=score,
+                    comment=feedback.get("text"),
+                )
+                st.session_state.feedback = {
+                    "feedback_id": str(feedback_record.id),
+                    "score": score,
+                }
         else:
             st.warning("Invalid feedback score.")
-        if feedback.get("text"):
-            comment = feedback.get("text")
-            feedback_embedding = get_embeddings(comment)
-        else:
-            comment = "no comment"
-            feedback_embedding = get_embeddings(comment)
 
-        
-        qdrant_client.upload_collection(            
-            collection_name="chat-history",
-            payload=[
-                {"text": comment,"Score:":score, "type": "feedback", "question_ID": run_id}
-            ],
-            vectors=[
-                feedback_embedding
-            ],
-            parallel=4,
-            max_retries=3,
-            )
+        with st.spinner("Just a sec! Dont enter prompts while loading pelase!"):
+            if feedback.get("text"):
+                comment = feedback.get("text")
+                feedback_embedding = get_embeddings(comment)
+            else:
+                comment = "no comment"
+                feedback_embedding = get_embeddings(comment)
+
             
+            qdrant_client.upload_collection(            
+                collection_name="chat-history",
+                payload=[
+                    {"text": comment,"Score:":score, "type": "feedback", "question_ID": run_id}
+                ],
+                vectors=[
+                    feedback_embedding
+                ],
+                parallel=4,
+                max_retries=3,
+                )