Update app.py

app.py

@@ -18,7 +18,8 @@ from textattack.attack_recipes import (
     CLARE2020,
 )
 from textattack.attack_results import SuccessfulAttackResult
-from utils import SentAttacker, get_agnews_example, get_sst2_example, get_amazon_example, get_imdb_example, diff_texts
+from utils import SentAttacker, get_agnews_example, get_sst2_example, get_amazon_example, get_imdb_example, diff_texts, \
+    get_yahoo_example
 
 sent_attackers = {}
 tad_classifiers = {}
@@ -47,7 +48,7 @@ def init():
             "agnews10k",
             "amazon",
             "sst2",
-            # "yahoo",
+            "yahoo",
             # 'imdb'
         ]:
             if "tad-{}".format(dataset) not in tad_classifiers:
@@ -168,6 +169,7 @@ def run_demo(dataset, attacker, text=None, label=None):
             result["output"],
             pd.DataFrame(result["classification_df"]),
             pd.DataFrame(result["advdetection_df"]),
+            result["message"]
         )
     except Exception as e:
         print(e)
@@ -186,11 +188,11 @@ def check_gpu():
 
 
 if __name__ == "__main__":
-    try:
-        init()
-    except Exception as e:
-        print(e)
-        print("Failed to initialize the demo. Please try again later.")
+    # try:
+    #     init()
+    # except Exception as e:
+    #     print(e)
+    #     print("Failed to initialize the demo. Please try again later.")
 
     demo = gr.Blocks()
 
@@ -217,15 +219,22 @@ if __name__ == "__main__":
                     label="Choose an Adversarial Attacker for generating an adversarial example to attack the model.",
                 )
             with gr.Group():
+
                 with gr.Row():
                     input_sentence = gr.Textbox(
                         placeholder="Input a natural example...",
                         label="Alternatively, input a natural example and its original label (from above datasets) to generate an adversarial example.",
                     )
                     input_label = gr.Textbox(
-                        placeholder="Original label, must be an integer...", label="Original Label"
+                        placeholder="Original label, （must be a integer, because we use digits to represent labels in training）", label="Original Label"
                     )
+                gr.Markdown(
+                    "<h3 align='center'>To input an example, please select a dataset which the example belongs to or resembles.</h2>")
 
+        msg_text = gr.Textbox(
+            label="Message",
+            placeholder="This is a message box to show any error messages.",
+        )
         button_gen = gr.Button(
             "Generate an adversarial example to repair using Rapid (GPU: < 1 minute, CPU: 1-10 minutes)",
             variant="primary",
@@ -322,6 +331,7 @@ if __name__ == "__main__":
                 output_adv_label,
                 output_df,
                 output_is_adv_df,
+                msg_text
             ],
         )