Tortoise-upgrade

server.py

@@ -63,7 +63,10 @@ def reload_config_and_restart_ui():
     else default_config
 )
 
-with gr.Blocks(css=full_css) as demo:
+with gr.Blocks(
+    css=full_css,
+    title="TTS Generation WebUI",
+) as demo:
     gr.Markdown("# TTS Generation WebUI (Bark, MusicGen, Tortoise)")
     with gr.Tabs() as tabs:
         register_use_as_history_button = generation_tab_bark(tabs)

src/css/css.py

@@ -1,7 +1,7 @@
 from src.bark.bark_css import bark_css
 from src.css.material_symbols_css import material_symbols_css
 from src.history_tab.history_css import history_css
-from src.tortoise.generation_tab_tortoise import css_tortoise
+from src.tortoise.css_tortoise import css_tortoise
 from src.musicgen.musicgen_css import musicgen_css
 
 full_css = ""

src/musicgen/musicgen_tab.py

@@ -21,6 +21,9 @@
 
 import json
 from typing import Optional
+from importlib.metadata import version
+
+AUDIOCRAFT_VERSION = version("audiocraft")
 
 
 class MusicGenGeneration(TypedDict):
@@ -53,6 +56,7 @@ def generate_and_save_metadata(
         "_version": "0.0.1",
         "_hash_version": "0.0.3",
         "_type": "musicgen",
+        "_audiocraft_version": AUDIOCRAFT_VERSION,
         "models": {},
         "prompt": prompt,
         "hash": audio_array_to_sha256(audio_array),
@@ -209,6 +213,7 @@ def predict(params: MusicGenGeneration, melody_in: Optional[Tuple[int, np.ndarra
 def generation_tab_musicgen():
     with gr.Tab("MusicGen") as tab:
         musicgen_atom.render()
+        gr.Markdown(f"""Audiocraft version: {AUDIOCRAFT_VERSION}""")
         with gr.Row():
             with gr.Column():
                 text = gr.Textbox(
@@ -259,7 +264,7 @@ def generation_tab_musicgen():
                         interactive=True,
                         step=0.1,
                     )
-                seed, set_old_seed_button = setup_seed_ui_musicgen()
+                seed, set_old_seed_button, _ = setup_seed_ui_musicgen()
 
         with gr.Column():
             output = gr.Audio(

src/musicgen/setup_seed_ui_musicgen.py

@@ -20,4 +20,12 @@ def setup_seed_ui_musicgen():
         )
 
         set_old_seed_button.style(size="sm")
-    return seed_input, set_old_seed_button
+
+        def link_seed_cache(seed_cache):
+            set_old_seed_button.click(
+                fn=lambda x: gr.Number.update(value=x),
+                inputs=seed_cache,
+                outputs=seed_input,
+            )
+
+    return seed_input, set_old_seed_button, link_seed_cache

src/tortoise/css_tortoise.py

@@ -0,0 +1,6 @@
+css_tortoise = """
+.btn-sm {
+    min-width: 2em !important;
+    flex-grow: 0 !important;
+}
+"""

src/tortoise/gen_tortoise.py

@@ -9,28 +9,39 @@
 
 from models.tortoise.tortoise.api import TextToSpeech, MODELS_DIR
 from models.tortoise.tortoise.utils.audio import load_voices
+import gradio as gr
 
 SAMPLE_RATE = 24_000
 OUTPUT_PATH = "outputs/"
 
+MODEL = None
+
+
+def get_tts():
+    global MODEL
+    if MODEL is None:
+        MODEL = TextToSpeech(models_dir=MODELS_DIR)
+    return MODEL
+
 
 def generate_tortoise(
     text="The expressiveness of autoregressive transformers is literally nuts! I absolutely adore them.",
     voice="random",
     preset="fast",
-    model_dir=MODELS_DIR,
     candidates=3,
     seed=None,
     cvvp_amount=0.0,
 ):
     os.makedirs(OUTPUT_PATH, exist_ok=True)
 
-    tts = TextToSpeech(models_dir=model_dir)
-
-    filenames = []
+    datas = []
     voice_sel = voice.split("&") if "&" in voice else [voice]
     voice_samples, conditioning_latents = load_voices(voice_sel)
 
+    if seed == -1:
+        seed = None
+
+    tts = get_tts()
     gen, state = tts.tts_with_preset(
         text,
         k=candidates,
@@ -46,16 +57,14 @@ def generate_tortoise(
 
     if isinstance(gen, list):
         for j, g in enumerate(gen):
-            process_gen(
-                text, voice, preset, candidates, seed, cvvp_amount, filenames, g, j
-            )
+            process_gen(text, voice, preset, candidates, seed, cvvp_amount, datas, g, j)
     else:
-        process_gen(text, voice, preset, candidates, seed, cvvp_amount, filenames, gen)
-    return filenames
+        process_gen(text, voice, preset, candidates, seed, cvvp_amount, datas, gen)
+    return datas
 
 
 def process_gen(
-    text, voice, preset, candidates, seed, cvvp_amount, filenames, gen, j=0
+    text, voice, preset, candidates, seed, cvvp_amount, datas, gen, j=0
 ):
     audio_tensor = gen.squeeze(0).cpu()
 
@@ -74,19 +83,32 @@ def process_gen(
     filename_json = f"{base_filename}.json"
 
     metadata = {
+        "_version": "0.0.1",
+        "_type": model,
+        "date": date,
         "text": text,
         "voice": voice,
         "preset": preset,
         "candidates": candidates,
-        "seed": seed,
+        "seed": str(seed),
         "cvvp_amount": cvvp_amount,
     }
     import json
 
     with open(filename_json, "w") as f:
         json.dump(metadata, f)
 
-    filenames.extend((filename, filename_png))
+    history_bundle_name_data = os.path.dirname(filename)
+
+    datas.extend(
+        (
+            filename,
+            filename_png,
+            gr.Button.update(value="Save to favorites", visible=True),
+            seed,
+            history_bundle_name_data,
+        )
+    )
 
 
 def generate_tortoise_n(n):