Update app.py

app.py

@@ -194,8 +194,8 @@ def compare_embeddings(file, query, model_types, model_names, split_strategy, ch
         stats = calculate_statistics(results, search_time)
         stats["model"] = f"{model_type} - {model_name}"
 
-        all_results.append(pd.DataFrame(results))
-        all_stats.append(pd.DataFrame(stats))
+        all_results.append(results)
+        all_stats.append(stats)
 
     # Flatten the return values to match Gradio's expectation for each output
     return [item for sublist in all_results for item in sublist] + [item for sublist in all_stats for item in sublist]
@@ -217,8 +217,8 @@ iface = gr.Interface(
         gr.Slider(1, 10, step=1, value=5, label="Top K")
     ],
     #outputs=[gr.DataFrame(label="Results"), gr.DataFrame(label="Statistics")] * len(MODELS),
-    outputs = [gr.DataFrame(label=f"Results {i+1}") for i in range(len(MODELS)-1)] + \
-          [gr.DataFrame(label=f"Statistics {i+1}") for i in range(len(MODELS)-1)],
+    outputs = [gr.Text(label=f"Results {i+1}") for i in range(len(MODELS)-1)] + \
+          [gr.Text(label=f"Statistics {i+1}") for i in range(len(MODELS)-1)],
     title="Embedding Comparison Tool",
     description="Compare different embedding models and retrieval strategies"
 )