Update app.py

app.py

@@ -1,3 +1,36 @@
+import os
 import gradio as gr
+from gradio import FlaggingCallback
+from gradio.components import IOComponent
 
-gr.Interface.load("models/deprem-ml/deprem-ner").launch()
+from transformers import pipeline
+
+from typing import List, Optional, Any
+
+import argilla as rg
+
+class ArgillaLogger(FlaggingCallback):
+    def __init__(self, api_url, api_key, dataset_name):
+        rg.init(api_url=api_url, api_key=api_key)
+        self.dataset_name = dataset_name
+    def setup(self, components: List[IOComponent], flagging_dir: str):
+        pass
+    def flag(
+        self,
+        flag_data: List[Any],
+        flag_option: Optional[str] = None,
+        flag_index: Optional[int] = None,
+        username: Optional[str] = None,
+    ) -> int:
+        text = flag_data[0]
+        inference = flag_data[1]
+        print(flag_data)
+        #rg.log(name=dataset_name,records=rg.TextClassificationRecord(inputs={"answer": text, "response": inference}))
+
+
+
+gr.Interface.load(
+    "models/deprem-ml/deprem-ner",
+    allow_flagging="manual",
+    flagging_callback=ArgillaLogger(api_url="https://dvilasuero-argilla-template-space.hf.space", api_key="team.apikey", dataset_name="ner-example")
+).launch()