Update app.py

app.py

@@ -170,7 +170,6 @@ def generate_focused_summary(question, abstracts, model, tokenizer):
     
     return tokenizer.decode(summary_ids[0], skip_special_tokens=True)
 
-
 def main():
     st.title("🔬 Biomedical Papers Analysis")
     
@@ -198,9 +197,6 @@ def main():
         df = st.session_state.processed_data
         st.write(f"📊 Loaded {len(df)} papers")
         
-        # Individual Summaries Section
-        st.header("📝 Individual Paper Summaries")
-        
         # Question input before the unified generate button
         st.header("❓ Question-focused Summary (Optional)")
         question = st.text_input("Enter your research question (optional):")
@@ -217,7 +213,7 @@ def main():
                         progress_bar = st.progress(0)
                         
                         # Create a table for live updates
-                        summary_table = st.table([])
+                        summary_table = st.empty()
                         summaries = []
                         table_data = []
                         
@@ -230,14 +226,14 @@ def main():
                             
                             # Update table data
                             table_data.append({
-                                "Title": row['Article Title'],
-                                "Summary": summary
+                                "PAPER": f"{row['Article Title']}\n{row['Authors']}\nDOI: {row['DOI']}",
+                                "SUMMARY": summary
                             })
                             summary_table.dataframe(
                                 pd.DataFrame(table_data),
                                 column_config={
-                                    "Title": st.column_config.TextColumn("Paper Title", width="medium"),
-                                    "Summary": st.column_config.TextColumn("Generated Summary", width="large")
+                                    "PAPER": st.column_config.TextColumn("PAPER", width=300),
+                                    "SUMMARY": st.column_config.TextColumn("SUMMARY", width="medium")
                                 },
                                 hide_index=True
                             )
@@ -257,12 +253,14 @@ def main():
                         torch.cuda.empty_cache()
                         gc.collect()
                         
+                        # Find relevant abstracts
                         results = st.session_state.text_processor.find_most_relevant_abstracts(
                             question,
                             df['Abstract'].tolist(),
                             top_k=5
                         )
                         
+                        # Load question model
                         model, tokenizer = load_model("question_focused")
                         
                         relevant_abstracts = df['Abstract'].iloc[results['top_indices']].tolist()
@@ -303,38 +301,37 @@ def main():
         
         # Display sorted summaries if they exist
         if st.session_state.summaries is not None:
-            st.subheader("All Paper Summaries")
-            sort_options = {
-                'Article Title': 'Article Title',
-                'Authors': 'Authors',
-                'Publication Year': 'Publication Year',
-                'Source Title': 'Source Title'
-            }
-            
-            col1, col2 = st.columns(2)
+            st.header("📝 Individual Paper Summaries")
+            col1, col2 = st.columns([2, 1])
             with col1:
-                sort_column = st.selectbox("Sort by:", list(sort_options.keys()))
+                sort_by = st.selectbox(
+                    "Sort By",
+                    ["Article Title", "Publication Year"],
+                    key="sort_summaries"
+                )
             with col2:
-                ascending = st.checkbox("Ascending order", True)
+                ascending = st.checkbox("Ascending order", True, key="sort_order")
             
+            # Create display dataframe
             display_df = df.copy()
-            display_df['Summary'] = st.session_state.summaries
-            display_df['Publication Year'] = display_df['Publication Year'].astype(int)
-            sorted_df = display_df.sort_values(by=sort_options[sort_column], ascending=ascending)
+            display_df['PAPER'] = display_df.apply(
+                lambda x: f"{x['Article Title']}\n{x['Authors']}\nDOI: {x['DOI']}", 
+                axis=1
+            )
+            display_df['SUMMARY'] = st.session_state.summaries
+            
+            # Sort the dataframe
+            sorted_df = display_df.sort_values(by=sort_by, ascending=ascending)
             
+            # Display the table
             st.dataframe(
-                sorted_df[['Article Title', 'Authors', 'Source Title', 
-                          'Publication Year', 'DOI', 'Summary']],
+                sorted_df[['PAPER', 'SUMMARY']],
                 column_config={
-                    'Article Title': st.column_config.TextColumn('Article Title', width='medium'),
-                    'Authors': st.column_config.TextColumn('Authors', width='medium'),
-                    'Source Title': st.column_config.TextColumn('Source Title', width='medium'),
-                    'Publication Year': st.column_config.NumberColumn('Year', format="%d"),
-                    'DOI': st.column_config.TextColumn('DOI', width='small'),
-                    'Summary': st.column_config.TextColumn('Summary', width='large'),
+                    "PAPER": st.column_config.TextColumn("PAPER", width=300),
+                    "SUMMARY": st.column_config.TextColumn("SUMMARY", width="medium")
                 },
                 hide_index=True
             )
 
 if __name__ == "__main__":
-    main()
+    main()