Update app.py

app.py

@@ -3,7 +3,7 @@ from transformers import T5ForConditionalGeneration, T5Tokenizer, pipeline
 import torch
 
 # Streamlit app setup
-st.set_page_config(page_title="Hugging Face Chat", layout="wide")
+st.set_page_config(page_title="Chat", layout="wide")
 
 # Sidebar: Model controls
 st.sidebar.title("Model Controls")
@@ -52,12 +52,16 @@ if clear_model_button:
     st.success("Model cleared.")
 
 # Chat Conversation Display
-st.subheader("Conversation")
-for idx, (speaker, message) in enumerate(st.session_state["conversation"]):
-    if speaker == "You":
-        st.markdown(f"**You:** {message}")
-    else:
-        st.markdown(f"**Model:** {message}")
+def display_conversation():
+    """Display the chat conversation dynamically."""
+    st.subheader("Conversation")
+    for idx, (speaker, message) in enumerate(st.session_state["conversation"]):
+        if speaker == "You":
+            st.markdown(f"**You:** {message}")
+        else:
+            st.markdown(f"**Model:** {message}")
+
+display_conversation()
 
 # Input Area
 if st.session_state["qa_pipeline"]:
@@ -70,11 +74,19 @@ if st.session_state["qa_pipeline"]:
         if user_input:
             with st.spinner("Generating response..."):
                 try:
+                    # Generate the model response
                     response = st.session_state["qa_pipeline"](f"Q: {user_input}", max_length=400)
                     generated_text = response[0]["generated_text"]
+
+                    # Update the conversation
                     st.session_state["conversation"].append(("You", user_input))
                     st.session_state["conversation"].append(("Model", generated_text))
-                    st.session_state["user_input"] = ""  # Clear input after submission
+
+                    # Clear the input field after submission
+                    st.session_state["user_input"] = ""
+
+                    # Rerender the conversation immediately
+                    display_conversation()
                 except Exception as e:
                     st.error(f"Error generating response: {e}")