allow flagging

app.py

@@ -6,6 +6,7 @@ import gradio as gr
 
 MODEL_PATH = "xiaopeiwu/hrw_v2"
 auth_token = os.environ.get("TOKEN_FROM_SECRET")
+hf_writer = gr.HuggingFaceDatasetSaver(auth_token, "hrw_v2_test_flagged_data")
 model = DistilBertForSequenceClassification.from_pretrained(MODEL_PATH, use_auth_token=auth_token)
 tokenizer = DistilBertTokenizer.from_pretrained("distilbert-base-uncased")
 
@@ -29,6 +30,9 @@ demo = gr.Interface(
     description="DistilBert for text classification model fine tuned on 70% of annotated RM production data combined with industry-specific webscrape data",
     inputs=gr.Textbox(placeholder="Enter sentence here and press Submit", label="Sentence to check"),
     outputs="textbox",
+    allow_flagging="manual",
+    flagging_options=["wrong result", "inconsistent result", "debatable input", "other"],
+    flagging_callback=hf_writer,
 )
 
 demo.launch()