Update app.py

app.py

@@ -11,28 +11,28 @@ from utils import setup_all_auth
 # 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;
-    }
+.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)
@@ -103,10 +103,8 @@ if st.button("Get Answer") or st.session_state.submit_clicked:
         with st.spinner("Processing your question..."):
             try:
                 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"])
-                
                 st.subheader("Sources:")
                 for citation in result["citations"].split("\n"):
                     st.write(citation)
@@ -120,6 +118,5 @@ st.markdown("---")
 st.markdown("""
 ### About this app
 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.
 """)