Update app.py

app.py

@@ -9,22 +9,23 @@ description = "Gradio Demo for SpeechMatrix. To use it, simply record your audio
 
 article = "<p style='text-align: center'><a href='ADD LINK' target='_blank'>SpeechMatrix</a> | <a href='https://github.com/facebookresearch/fairseq/tree/ust' target='_blank'>Github Repo</a></p>"
 
+SRC_LIST = ['cs', 'de', 'en', 'es', 'et', 'fi', 'fr', 'hr', 'hu', 'it', 'nl', 'pl', 'pt', 'ro', 'sk', 'sl']
+TGT_LIST = ['en', 'fr', 'es']
+MODEL_LIST = ['xm_transformer_sm_all-en']
+for src in SRC_LIST:
+    for tgt in TGT_LIST:
+        MODEL_LIST.append(f"textless_sm_{src}_{tgt}")
+        
 examples = []
 
-io1 = gr.Interface.load("huggingface/facebook/xm_transformer_sm_all-en")
+io_dict = {model: gr.Interface.load(f"huggingface/facebook/{model}") for model in MODEL_LIST}
    
 def inference(audio, model):
-    out_audio = io1(audio)   
+    out_audio = io_dict[model](audio)   
     return out_audio 
-
-model_choices = ["xm_transformer_sm_all-en"]
-for src in ['cs', 'de', 'en', 'es', 'et', 'fi', 'fr', 'hr', 'hu', 'it', 'nl', 'pl', 'pt', 'ro', 'sk', 'sl']:
-    for tgt in ['en', 'fr', 'de']:
-        if src != tgt:
-            model_choices.append(f"textless_sm_{src}_{tgt}")
 gr.Interface(
     inference,
-    [gr.inputs.Audio(source="microphone", type="filepath", label="Input"),gr.inputs.Dropdown(choices=model_choices, default="xm_transformer_sm_all-en",type="value", label="Model")
+    [gr.inputs.Audio(source="microphone", type="filepath", label="Input"),gr.inputs.Dropdown(choices=MODEL_LIST, default="xm_transformer_sm_all-en",type="value", label="Model")
 ],
     gr.outputs.Audio(label="Output"),
     article=article,