Update app.py

app.py

@@ -7,26 +7,78 @@ st.set_page_config(page_title="Indian Spiritual RAG")
 from rag_engine import process_query, load_model
 from utils import setup_all_auth
 
-# Display title
-st.title("Indian Spiritual Texts Q&A")
+# Display title with custom styling
+st.markdown("""
+<style>
+    .main-title {
+        font-size: 2.5rem;
+        color: #FF5722;
+        text-align: center;
+        margin-bottom: 1rem;
+    }
+    .button-style {
+        border: 2px solid #FF5722;
+        border-radius: 8px;
+    }
+    .input-style {
+        border: 2px solid #4CAF50;
+        border-radius: 8px;
+    }
+    .stButton>button {
+        border: 2px solid #FF5722 !important;
+        border-radius: 8px !important;
+    }
+    .stTextInput>div>div>input {
+        border: 2px solid #4CAF50 !important;
+        border-radius: 8px !important;
+    }
+</style>
+<div class="main-title">Indian Spiritual Texts Q&A</div>
+""", unsafe_allow_html=True)
+
+# Initialize session state
+if 'initialized' not in st.session_state:
+    st.session_state.initialized = False
+if 'last_query' not in st.session_state:
+    st.session_state.last_query = ""
+if 'submit_clicked' not in st.session_state:
+    st.session_state.submit_clicked = False
 
 # Setup all authentication
-try:
-    setup_all_auth()
-except Exception as e:
-    st.error(f"Authentication error: {str(e)}")
+if not st.session_state.initialized:
+    try:
+        setup_all_auth()
+    except Exception as e:
+        st.error(f"Authentication error: {str(e)}")
 
 # Preload the model to avoid session state issues
-try:
-    with st.spinner("Initializing... This may take a minute."):
-        # Force model loading at startup to avoid session state issues
-        load_model()
-        st.success("System initialized successfully!")
-except Exception as e:
-    st.error(f"Error initializing: {str(e)}")
+if not st.session_state.initialized:
+    try:
+        with st.spinner("Hang in there! We are setting the system up for you. 😊"):
+            # Force model loading at startup to avoid session state issues
+            load_model()
+            st.session_state.initialized = True
+            st.success("System initialized successfully!")
+    except Exception as e:
+        st.error(f"Error initializing: {str(e)}")
+
+# Function to process when enter is pressed or button is clicked
+def process_input():
+    st.session_state.last_query = st.session_state.query
+    st.session_state.query = ""
+    st.session_state.submit_clicked = True
 
-# Query input
-query = st.text_input("Ask your question:")
+# Query input with callback for Enter key
+query = st.text_input(
+    "Ask your question:",
+    key="query",
+    on_change=process_input if st.session_state.query and st.session_state.query.strip() else None
+)
+
+# Display the current question if there is one
+if st.session_state.last_query:
+    st.markdown("### Current Question:")
+    st.info(st.session_state.last_query)
 
 # Sliders for customization
 col1, col2 = st.columns(2)
@@ -36,11 +88,15 @@ with col2:
     word_limit = st.slider("Word limit:", 50, 500, 200)
 
 # Process button
-if st.button("Get Answer"):
-    if query:
-        with st.spinner("Processing..."):
+if st.button("Get Answer") or st.session_state.submit_clicked:
+    if st.session_state.last_query:
+        # Reset the submit flag
+        st.session_state.submit_clicked = False
+        
+        # Single processing spinner for the entire operation
+        with st.spinner("Processing your question..."):
             try:
-                result = process_query(query, top_k=top_k, word_limit=word_limit)
+                result = process_query(st.session_state.last_query, top_k=top_k, word_limit=word_limit)
                 
                 st.subheader("Answer:")
                 st.write(result["answer_with_rag"])
@@ -57,6 +113,7 @@ if st.button("Get Answer"):
 st.markdown("---")
 st.markdown("""
 ### About this app
-This application uses a Retrieval-Augmented Generation (RAG) system to answer questions about Indian spiritual texts. 
+This application uses a Retrieval-Augmented Generation (RAG) system to answer questions about Indian spiritual texts.
+
 It searches through a database of texts to find relevant passages and generates answers based on those passages.
 """)