Update app.py

app.py

@@ -55,7 +55,13 @@ def adr_predict(x):
     scores = tf.nn.softmax(scores)
    
     shap_values = explainer([str(x).lower()])
-    local_plot = shap.plots.text(shap_values[0], display=False)
+    # # Find the index of the class you want as the default reference (e.g., 'label_1')
+    # label_1_index = np.where(np.array(explainer.output_names) == 'label_1')[0][0]
+
+    # # Plot the SHAP values for a specific instance in your dataset (e.g., instance 0)
+    # shap.plots.text(shap_values[label_1_index][0])
+
+    local_plot = shap.plots.text(shap_values[0][1], display=False)
 
     # med = med_score(classifier(x+str(", There is a medication."))[0])
     # sym = sym_score(classifier(x+str(", There is a symptom."))[0])