Update streamlit_app.py

streamlit_app.py

@@ -7,12 +7,7 @@ import os
 
 st.set_page_config(page_title="Accent Analyzer Agent", page_icon="💬", layout="centered")
 
-# # Clear chat history only once per session
-# if "initialized" not in st.session_state:
-#     st.session_state.initialized = True
-#     st.session_state.chat_history = []
-
-st.warning("⚠️ High latency due to CPU usage. Once migrated to GPU, response time will improve significantly.")
+st.warning("⚠️ High latency(~11min for 0:59s video) due to CPU usage. Once migrated to GPU, response time will improve significantly.")
 
 st.title("English Accent Analyzer (Conversational)")
 st.subheader("Ask me to analyze a video URL, e.g.: \n\n> *Analyze this video: https://github.com/ash-171/Data-mp4/raw/refs/heads/main/NWRNVTFlRGlnV0FfNDgwcA_out.mp4*")
@@ -41,28 +36,60 @@ user_input = st.chat_input(prompt_label, key=input_key)
 deferred_response = None
 deferred_spinner_msg = ""
 
-if user_input:
-    st.session_state.chat_history.append(HumanMessage(content=user_input))
+# if user_input:
+#     st.session_state.chat_history.append(HumanMessage(content=user_input))
 
+#     if re.search(r'https?://\S+', user_input):
+#         accent_tool_obj.last_transcript = ""
+#         deferred_spinner_msg = "Analyzing new video..."
+#         def run_agent():
+#             return analysis_agent.invoke(st.session_state.chat_history)[-1].content
+#     else:
+#         deferred_spinner_msg = "Responding based on transcript..."
+#         def run_agent():
+#             return follow_up_agent.invoke(st.session_state.chat_history).content
+
+#     # Run response generation inside spinner after chat is rendered
+#     def process_response():
+#         with st.spinner(deferred_spinner_msg):
+#             try:
+#                 result = run_agent()
+#             except Exception as e:
+#                 result = f"Error: {str(e)}"
+#             st.session_state.chat_history.append(AIMessage(content=result))
+#             st.rerun() 
+
+if user_input and not st.session_state.get("processing_started", False):
+    st.session_state.chat_history.append(HumanMessage(content=user_input))
+    
     if re.search(r'https?://\S+', user_input):
         accent_tool_obj.last_transcript = ""
-        deferred_spinner_msg = "Analyzing new video..."
-        def run_agent():
-            return analysis_agent.invoke(st.session_state.chat_history)[-1].content
+        st.session_state.deferred_spinner_msg = "Analyzing new video..."
+        st.session_state.run_agent_type = "analysis"
     else:
-        deferred_spinner_msg = "Responding based on transcript..."
-        def run_agent():
-            return follow_up_agent.invoke(st.session_state.chat_history).content
-
-    # Run response generation inside spinner after chat is rendered
-    def process_response():
-        with st.spinner(deferred_spinner_msg):
-            try:
-                result = run_agent()
-            except Exception as e:
-                result = f"Error: {str(e)}"
-            st.session_state.chat_history.append(AIMessage(content=result))
-            st.rerun() 
+        st.session_state.deferred_spinner_msg = "Responding based on transcript..."
+        st.session_state.run_agent_type = "followup"
+    
+    st.session_state.processing_started = True
+    st.rerun() 
+
+for msg in st.session_state.chat_history:
+    with st.chat_message("user" if isinstance(msg, HumanMessage) else "assistant"):
+        st.markdown(msg.content)
+
+if st.session_state.get("processing_started", False):
+    with st.spinner(st.session_state.deferred_spinner_msg):
+        try:
+            if st.session_state.run_agent_type == "analysis":
+                result = analysis_agent.invoke(st.session_state.chat_history)[-1].content
+            else:
+                result = follow_up_agent.invoke(st.session_state.chat_history).content
+        except Exception as e:
+            result = f"Error: {str(e)}"
+    
+    st.session_state.chat_history.append(AIMessage(content=result))
+    st.session_state.processing_started = False
+    st.rerun() 
 
 # Display full chat history (before running spinner)
 for msg in st.session_state.chat_history: