Update streamlit_app.py

streamlit_app.py

@@ -1,16 +1,17 @@
 import streamlit as st
+import os
+import re
 from src.tools.accent_tool import AccentAnalyzerTool
 from src.app.main_agent import create_agent
 from langchain_core.messages import HumanMessage, AIMessage
-import re
 
 st.set_page_config(page_title="Accent Analyzer Agent", page_icon="💬", layout="centered")
-
 st.warning("⚠️ High latency 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`")
 
+# Load tool and agent
 @st.cache_resource
 def load_tool_and_agent():
     with st.spinner("Loading AI models and tools... This might take a moment."):
@@ -22,9 +23,17 @@ def load_tool_and_agent():
 
 accent_tool_obj, analysis_agent, follow_up_agent = load_tool_and_agent()
 
+# Session state initialization
 if "chat_history" not in st.session_state:
     st.session_state.chat_history = []
 
+if "pending_user_input" not in st.session_state:
+    st.session_state.pending_user_input = None
+
+if "pending_spinner_msg" not in st.session_state:
+    st.session_state.pending_spinner_msg = ""
+
+# Prompt configuration
 if hasattr(accent_tool_obj, "last_transcript") and accent_tool_obj.last_transcript:
     prompt_label = "Ask more about the video..."
     input_key = "followup"
@@ -32,43 +41,39 @@ else:
     prompt_label = "Paste your prompt here..."
     input_key = "initial"
 
+# Chat input
 user_input = st.chat_input(prompt_label, key=input_key)
 
-# Variable to defer assistant response
-deferred_response = None
-deferred_spinner_msg = ""
-
+# Queue input for processing
 if user_input:
     st.session_state.chat_history.append(HumanMessage(content=user_input))
-
+    st.session_state.pending_user_input = 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.pending_spinner_msg = "Analyzing new video..."
     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.pending_spinner_msg = "Responding based on transcript..."
+    st.rerun()
 
-# Display full chat history (before running spinner)
+# Display chat history
 for msg in st.session_state.chat_history:
     with st.chat_message("user" if isinstance(msg, HumanMessage) else "assistant"):
         st.markdown(msg.content)
 
-# Only process response at the bottom, after chat is shown
-if user_input:
-    process_response()
-
-
-
+# Process pending input (after chat is rendered)
+if st.session_state.pending_user_input:
+    with st.spinner(st.session_state.pending_spinner_msg):
+        try:
+            if re.search(r'https?://\S+', st.session_state.pending_user_input):
+                response = analysis_agent.invoke(st.session_state.chat_history)[-1].content
+            else:
+                response = follow_up_agent.invoke(st.session_state.chat_history).content
+        except Exception as e:
+            response = f"Error: {str(e)}"
+
+        st.session_state.chat_history.append(AIMessage(content=response))
+
+    # Clear pending flags
+    st.session_state.pending_user_input = None
+    st.session_state.pending_spinner_msg = ""
+    st.rerun()