change textbox to dropdown

app_text_classification.py

@@ -19,7 +19,6 @@ MAX_LABELS = 40
 MAX_FEATURES = 20
 
 EXAMPLE_MODEL_ID = "cardiffnlp/twitter-roberta-base-sentiment-latest"
-EXAMPLE_DATA_ID = "tweet_eval"
 CONFIG_PATH = "./config.yaml"
 
 
@@ -36,11 +35,11 @@ def get_demo():
         )
 
         with gr.Column():
-            no_dataset_checkbox = gr.Checkbox(label="Recommend a dataset", value=False, visible=True)
-
-            dataset_id_input = gr.Textbox(
+            dataset_id_input = gr.Dropdown(
+                choices=[],
+                value="",
+                allow_custom_value=True,
                 label="Hugging Face Dataset id",
-                placeholder=EXAMPLE_DATA_ID + " (press enter to confirm)",
             )
 
     with gr.Row():
@@ -154,9 +153,9 @@ def get_demo():
     )
 
     gr.on(
-        triggers=[model_id_input.change, no_dataset_checkbox.change],
+        triggers=[model_id_input.change],
         fn=get_related_datasets_from_leaderboard,
-        inputs=[model_id_input, no_dataset_checkbox],
+        inputs=[model_id_input],
         outputs=[dataset_id_input],
     )
 

text_classification_ui_helpers.py

@@ -43,17 +43,13 @@ HF_GSK_HUB_HF_TOKEN = "GSK_HF_TOKEN"
 HF_GSK_HUB_UNLOCK_TOKEN = "GSK_HUB_UNLOCK_TOKEN"
 
 LEADERBOARD = "giskard-bot/evaluator-leaderboard"
-def get_related_datasets_from_leaderboard(model_id, rec_dataset=False):
-    if not rec_dataset:
-        return gr.update()
+def get_related_datasets_from_leaderboard(model_id):
     records = leaderboard.records
     model_records = records[records["model_id"] == model_id]
-    print(model_records)
     datasets_unique = model_records["dataset_id"].unique()
-    print(datasets_unique)
     if len(datasets_unique) == 0:
-        return gr.Textbox(placeholder="Sorry, we don't have recommendations for this model yet.", visible=True)
-    return gr.Textbox(label="Recommended Datasets", value=datasets_unique[0], visible=True)
+        return gr.update()
+    return gr.update(choices=datasets_unique, value=datasets_unique[0])
 
 
 logger = logging.getLogger(__file__)