Update app.py

app.py

@@ -176,6 +176,8 @@ def predict(file_obj):
             data=np.array([raw_freq_vector[kmer_dict[feat]] if feat != "Others" else np.sum(raw_freq_vector[others_mask]) for feat in top_features]),
             feature_names=top_features
         )
+        # Manually set expected_value to satisfy waterfall_legacy requirements
+        explanation.expected_value = 0
         
         # Generate waterfall plot using SHAP's legacy function
         fig = shap.plots._waterfall.waterfall_legacy(explanation, show=False)