dataset tab receives links

app.py

@@ -101,8 +101,11 @@ def predict(audio_path):
 
     return label_map.get(str(pred), str(pred))
 
-def evaluate_dataset():
-    ds = load_dataset("karenlu653/dialect_model_demo", split="train")
+def evaluate_dataset(repo_id):
+    try:
+        ds = load_dataset(repo_id, split="train")
+    except Exception as e:
+        return f"Could not load dataset: {e}"
 
     y_true, y_pred = [], []
     for row in ds:
@@ -121,11 +124,15 @@ def evaluate_dataset():
 
     # Plot
     fig, ax = plt.subplots(figsize=(5, 4))
-    sns.heatmap(cm, annot=True, fmt="d", cmap="Blues", xticklabels=[label_map[str(l)] for l in labels],
-                yticklabels=[label_map[str(l)] for l in labels], ax=ax)
+    sns.heatmap(
+        cm, annot=True, fmt="d", cmap="Blues",
+        xticklabels=[label_map[str(l)] for l in labels],
+        yticklabels=[label_map[str(l)] for l in labels],
+        ax=ax
+    )
     ax.set_xlabel("Predicted")
     ax.set_ylabel("True")
-    ax.set_title("Confusion Matrix of Shanghai Demo Samples")
+    ax.set_title(f"Confusion Matrix\n{repo_id}")
     plt.tight_layout()
 
     return fig
@@ -142,9 +149,14 @@ with gr.Blocks() as demo:
             live=False
         )
     with gr.Tab("Dataset Evaluation"):
-        eval_btn = gr.Button("Run Evaluation on Uploaded Dataset")
+        dataset_input = gr.Textbox(
+            label="Hugging Face Dataset ID",
+            value="karenlu653/dialect_model_demo",  # default
+            placeholder="e.g. username/repo_name"
+        )
+        eval_btn = gr.Button("Run Evaluation")
         eval_output = gr.Plot()
-        eval_btn.click(evaluate_dataset, inputs=None, outputs=eval_output)
+        eval_btn.click(evaluate_dataset, inputs=dataset_input, outputs=eval_output)
 
 if __name__ == "__main__":
     demo.launch()