add get prediction sample from the hf token

app_text_classification.py

@@ -12,11 +12,8 @@ from text_classification_ui_helpers import (
     try_submit,
     write_column_mapping_to_config,
 )
-
-from text_classification import (
-  get_example_prediction, 
-  HuggingFaceInferenceAPIResponse
-)
+from text_classification import get_example_prediction, HuggingFaceInferenceAPIResponse
+import logging
 from wordings import (
   CONFIRM_MAPPING_DETAILS_MD, 
   INTRODUCTION_MD, 
@@ -30,7 +27,7 @@ MAX_FEATURES = 20
 
 EXAMPLE_MODEL_ID = "cardiffnlp/twitter-roberta-base-sentiment-latest"
 CONFIG_PATH = "./config.yaml"
-
+logger = logging.getLogger(__name__)
 
 def get_demo():
     with gr.Row():
@@ -239,12 +236,19 @@ def get_demo():
 
     def enable_run_btn(run_inference, inference_token, model_id, dataset_id, dataset_config, dataset_split):
         if not run_inference or inference_token == "":
+            logger.warn("Inference API is not enabled")
             return gr.update(interactive=False)
         if model_id == "" or dataset_id == "" or dataset_config == "" or dataset_split == "":
+            logger.warn("Model id or dataset id is not selected")
             return gr.update(interactive=False)
         if not column_mapping_accordion.visible:
+            logger.warn("Column mapping is not confirmed")
             return gr.update(interactive=False)
-        if inference_token_info.visible:
+        _, prediction_response = get_example_prediction(
+            model_id, dataset_id, dataset_config, dataset_split, inference_token
+        )
+        if not isinstance(prediction_response, HuggingFaceInferenceAPIResponse):
+            logger.warn("Failed to get example prediction from inference API with this token")
             return gr.update(interactive=False)
         return gr.update(interactive=True)