restructure and empty col mapping when comfig changes

app_text_classification.py

@@ -7,12 +7,14 @@ from text_classification_ui_helpers import (
     get_related_datasets_from_leaderboard,
     align_columns_and_show_prediction,
     check_dataset,
-    precheck_model_ds_enable_example_btn,
     show_hf_token_info,
+    precheck_model_ds_enable_example_btn,
     try_submit,
+    empty_column_mapping,
     write_column_mapping_to_config,
+    enable_run_btn,
 )
-from text_classification import get_example_prediction, HuggingFaceInferenceAPIResponse
+
 import logging
 from wordings import (
   CONFIRM_MAPPING_DETAILS_MD, 
@@ -157,6 +159,12 @@ def get_demo():
         outputs=[dataset_config_input, dataset_split_input, loading_status]
     )
 
+    gr.on(
+        triggers=[model_id_input.change, dataset_id_input.change, dataset_config_input.change],
+        fn=empty_column_mapping,
+        inputs=[uid_label]
+    )
+
     gr.on(
         triggers=[label.change for label in column_mappings],
         fn=write_column_mapping_to_config,
@@ -234,24 +242,6 @@ def get_demo():
         outputs=[run_btn, logs, uid_label],
     )
 
-    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)
-        _, 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)
-
     gr.on(
         triggers=[
             run_inference.input,
@@ -260,6 +250,7 @@ def get_demo():
         ],
         fn=enable_run_btn,
         inputs=[
+            uid_label,
             run_inference, 
             inference_token, 
             model_id_input, 
@@ -274,6 +265,7 @@ def get_demo():
         triggers=[label.input for label in column_mappings],
         fn=enable_run_btn,
         inputs=[
+            uid_label,
             run_inference, 
             inference_token, 
             model_id_input, 

text_classification_ui_helpers.py

@@ -80,7 +80,8 @@ def check_dataset(dataset_id):
             ""
         )
 
-
+def empty_column_mapping(uid):
+    write_column_mapping(None, uid)
 
 def write_column_mapping_to_config(uid, *labels):
     # TODO: Substitute 'text' with more features for zero-shot
@@ -99,7 +100,6 @@ def write_column_mapping_to_config(uid, *labels):
 
     write_column_mapping(all_mappings, uid)
 
-
 def export_mappings(all_mappings, key, subkeys, values):
     if key not in all_mappings.keys():
         all_mappings[key] = dict()
@@ -308,12 +308,34 @@ def align_columns_and_show_prediction(
 def check_column_mapping_keys_validity(all_mappings):
     if all_mappings is None:
         gr.Warning(CONFIRM_MAPPING_DETAILS_FAIL_RAW)
-        return (gr.update(interactive=True), gr.update(visible=False))
+        return False
 
     if "labels" not in all_mappings.keys():
         gr.Warning(CONFIRM_MAPPING_DETAILS_FAIL_RAW)
-        return (gr.update(interactive=True), gr.update(visible=False))
+        return False
+
+    return True
 
+def enable_run_btn(uid, 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)
+    
+    all_mappings = read_column_mapping(uid)
+    if not check_column_mapping_keys_validity(all_mappings):
+        logger.warn("Column mapping is not valid")
+        return gr.update(interactive=False)
+
+    _, 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)
 
 def construct_label_and_feature_mapping(all_mappings, ds_labels, ds_features):
     label_mapping = {}
@@ -340,7 +362,8 @@ def show_hf_token_info(token):
 
 def try_submit(m_id, d_id, config, split, inference, inference_token, uid):
     all_mappings = read_column_mapping(uid)
-    check_column_mapping_keys_validity(all_mappings)
+    if not check_column_mapping_keys_validity(all_mappings):
+        return (gr.update(interactive=True), gr.update(visible=False))
 
     # get ds labels and features again for alignment
     ds = datasets.load_dataset(d_id, config, split=split, trust_remote_code=True)