Update app.py

app.py

@@ -23,7 +23,7 @@ style = '''
 '''
 st.markdown(style, unsafe_allow_html=True)
 
-st.markdown('<p style="font-family:sans-serif;font-size: 1.9rem;"> HertogAI Q&A using TAPAS and Model Language</p>', unsafe_allow_html=True)
+st.markdown('<p style="font-family:sans-serif;font-size: 1.9rem;"> HertogAI Table Q&A using TAPAS and Model Language</p>', unsafe_allow_html=True)
 st.markdown("<p style='font-family:sans-serif;font-size: 0.9rem;'>Pre-trained TAPAS model runs on max 64 rows and 32 columns data. Make sure the file data doesn't exceed these dimensions.</p>", unsafe_allow_html=True)
 
 # Initialize TAPAS pipeline
@@ -87,7 +87,7 @@ else:
                 # Get the raw answer from TAPAS
                 raw_answer = tqa(table=df, query=question, truncation=True)
                 
-                st.markdown("<p style='font-family:sans-serif;font-size: 0.9rem;'> Raw Result: </p>",
+                st.markdown("<p style='font-family:sans-serif;font-size: 0.9rem;'> Raw Result From TAPAS: </p>",
                            unsafe_allow_html=True)
                 st.success(raw_answer)
                 
@@ -116,7 +116,7 @@ else:
                 generated_text = t5_tokenizer.decode(summary_ids[0], skip_special_tokens=True)
 
                 # Display the final generated response
-                st.markdown("<p style='font-family:sans-serif;font-size: 0.9rem;'> Final Generated Response: </p>", unsafe_allow_html=True)
+                st.markdown("<p style='font-family:sans-serif;font-size: 0.9rem;'> Final Generated Response with LLM: </p>", unsafe_allow_html=True)
                 st.success(generated_text)
 
             except Exception as e: