fix: remove duplication in table view

app.py

@@ -367,30 +367,34 @@ def refresh_gallery():
 
     # Convert data to pandas DataFrame for table view
     table_data = []
+    
+    # First, count authors across all cards
+    author_counts = {}
     for card in eval_cards:
-        author_counts = {}
-        for card in eval_cards:
-            authors = card["authors"].split(", ")
-            for author in authors:
+        authors = card["authors"].split(", ")
+        for author in authors:
+            if author and author.strip():  # Skip empty authors
                 if author in author_counts:
                     author_counts[author] += 1
                 else:
                     author_counts[author] = 1
-
-        top_authors = sorted(author_counts.items(), key=lambda x: x[1], reverse=True)[:20]
-        top_authors = [author for author, count in top_authors]
-
-        for card in eval_cards:
-            authors = card["authors"].split(", ")
-            filtered_authors = [author for author in authors if author in top_authors]
-            table_data.append(
-                {
-                    "Title": card["title"],
-                    "Authors": ", ".join(filtered_authors),
-                    "Creation Date": card["creation_date"],
-                    "Coverage Score": f"{card['coverage_score']}%",
-                }
-            )
+    
+    # Get top authors
+    top_authors = sorted(author_counts.items(), key=lambda x: x[1], reverse=True)[:20]
+    top_authors = [author for author, count in top_authors]
+    
+    # Create table data with one entry per card
+    for card in eval_cards:
+        authors = card["authors"].split(", ")
+        filtered_authors = [author for author in authors if author in top_authors]
+        table_data.append(
+            {
+                "Title": card["title"],
+                "Authors": ", ".join(filtered_authors),
+                "Creation Date": card["creation_date"],
+                "Coverage Score": f"{card['coverage_score']}%",
+            }
+        )
 
     df = pd.DataFrame(table_data)