finally added model refresh button, also searches in the training folder for outputted models so you don't even need to copy them

src/utils.py

@@ -838,7 +838,17 @@ def get_autoregressive_models(dir="./models/finetunes/"):
 	if os.path.exists(halfp):
 		base.append(halfp)
 
-	return base + sorted([f'{dir}/{d}' for d in os.listdir(dir) if d[-4:] == ".pth" ])
+	additionals = sorted([f'{dir}/{d}' for d in os.listdir(dir) if d[-4:] == ".pth" ])
+	found = []
+	for training in os.listdir(f'./training/'):
+		if not os.path.isdir(f'./training/{training}/') or not os.path.isdir(f'./training/{training}/models/'):
+			continue
+		#found = found + sorted([ f'./training/{training}/model/{d}' for d in os.listdir(f'./training/{training}/models/') if d[-8:] == "_gpt.pth" ])
+		models = sorted([ int(d[:-8]) for d in os.listdir(f'./training/{training}/models/') if d[-8:] == "_gpt.pth" ])
+		found = found + [ f'./training/{training}/model/{d}_gpt.pth' for d in models ]
+		#found.append(f'./training/{training}/model/{models[-1]}_gpt.pth')
+
+	return base + additionals + found
 
 def get_dataset_list(dir="./training/"):
 	return sorted([d for d in os.listdir(dir) if os.path.isdir(os.path.join(dir, d)) and len(os.listdir(os.path.join(dir, d))) > 0 and "train.txt" in os.listdir(os.path.join(dir, d)) ])

src/webui.py

@@ -343,9 +343,10 @@ def setup_gradio():
 					voice_list = get_voice_list(append_defaults=True)
 					voice = gr.Dropdown(choices=voice_list, label="Voice", type="value", value=voice_list[0]) # it'd be very cash money if gradio was able to default to the first value in the list without this shit
 					mic_audio = gr.Audio( label="Microphone Source", source="microphone", type="filepath" )
-					refresh_voices = gr.Button(value="Refresh Voice List")
 					voice_latents_chunks = gr.Slider(label="Voice Chunks", minimum=1, maximum=64, value=1, step=1)
-					recompute_voice_latents = gr.Button(value="(Re)Compute Voice Latents")
+					with gr.Row():
+						refresh_voices = gr.Button(value="Refresh Voice List")
+						recompute_voice_latents = gr.Button(value="(Re)Compute Voice Latents")
 
 					def update_baseline_for_latents_chunks( voice ):
 						path = f'{get_voice_dir()}/{voice}/'
@@ -524,7 +525,26 @@ def setup_gradio():
 					autoregressive_models = get_autoregressive_models()
 					autoregressive_model_dropdown = gr.Dropdown(choices=autoregressive_models, label="Autoregressive Model", value=args.autoregressive_model if args.autoregressive_model else autoregressive_models[0])
 					whisper_model_dropdown = gr.Dropdown(["tiny", "tiny.en", "base", "base.en", "small", "small.en", "medium", "medium.en", "large"], label="Whisper Model", value=args.whisper_model)
+					with gr.Row():
+						autoregressive_models_update_button = gr.Button(value="Refresh Model List")
+						gr.Button(value="Check for Updates").click(check_for_updates)
+						gr.Button(value="(Re)Load TTS").click(
+							reload_tts,
+							inputs=autoregressive_model_dropdown,
+							outputs=None
+						)
 
+					def update_model_list_proxy( val ):
+						autoregressive_models = get_autoregressive_models()
+						if val not in autoregressive_models:
+							val = autoregressive_models[0]
+						return gr.update( choices=autoregressive_models, value=val )
+
+					autoregressive_models_update_button.click(
+						update_model_list_proxy,
+						inputs=autoregressive_model_dropdown,
+						outputs=autoregressive_model_dropdown,
+					)
 
 					autoregressive_model_dropdown.change(
 						fn=update_autoregressive_model,
@@ -537,12 +557,6 @@ def setup_gradio():
 						outputs=None
 					)
 
-					gr.Button(value="Check for Updates").click(check_for_updates)
-					gr.Button(value="(Re)Load TTS").click(
-						reload_tts,
-						inputs=autoregressive_model_dropdown,
-						outputs=None
-					)
 
 				for i in exec_inputs:
 					i.change( fn=update_args, inputs=exec_inputs )