exclude domain

interfaces/ontolisst.py

@@ -12,9 +12,6 @@ HF_TOKEN = os.environ["hf_read"]
 languages = [
     "English"
 ]
-domains = {
-    "parliamentary speech": "parlspeech",
-}
 
 from label_dicts import ONTOLISST_LABEL_NAMES
 
@@ -49,7 +46,7 @@ def predict(text, model_id, tokenizer_id):
     output_info = f'<p style="text-align: center; display: block">Prediction was made using the <a href="https://huggingface.co/{model_id}">{model_id}</a> model.</p>'
     return output_pred, output_info
 
-def predict_cap(text, language, domain):
+def predict_cap(text, language):
     model_id = build_huggingface_path(language)
     tokenizer_id = "xlm-roberta-large"
     return predict(text, model_id, tokenizer_id)
@@ -57,6 +54,5 @@ def predict_cap(text, language, domain):
 demo = gr.Interface(
     fn=predict_cap,
     inputs=[gr.Textbox(lines=6, label="Input"),
-            gr.Dropdown(languages, label="Language"),
-            gr.Dropdown(domains.keys(), label="Domain")],
+            gr.Dropdown(languages, label="Language")],
     outputs=[gr.Label(num_top_classes=3, label="Output"), gr.Markdown()])