Create app.py

app.py

@@ -0,0 +1,87 @@
+import torch
+from threading import Thread
+
+from transformers import AutoProcessor
+from transformers import set_seed
+
+from utils.vocos_bark import BarkModel
+from scipy.io.wavfile import write
+from pydub import AudioSegment
+
+import numpy as np
+
+import os
+import gradio as gr
+import uuid
+import io
+
+
+set_seed(0)
+
+def _grab_best_device(use_gpu=True):
+    if torch.cuda.device_count() > 0 and use_gpu:
+        device = "cuda"
+    else:
+        device = "cpu"
+    return device
+
+device = _grab_best_device()
+
+HUB_PATH = "suno/bark"
+
+processor = AutoProcessor.from_pretrained(HUB_PATH)
+
+speaker_embeddings = sorted([key for key in processor.speaker_embeddings.keys() if "speaker" in key])
+
+SAMPLE_RATE = 24_000
+
+
+# import model
+if device == "cpu":
+    bark = BarkModel.from_pretrained(HUB_PATH)
+else:
+    bark = BarkModel.from_pretrained(HUB_PATH).to(device)
+    bark = bark.to_bettertransformer()
+
+
+# streaming inference
+def generate_audio(text, voice_preset = None, lag = 0):
+    if voice_preset not in speaker_embeddings:
+        voice_preset = None
+    
+    sentences = [
+        text,
+    ]
+    inputs = processor(sentences, voice_preset=voice_preset).to(device)
+    # Run the generation in a separate thread, so that we can fetch the generated text in a non-blocking way.
+
+    waveform = bark.generate(
+        **inputs, coarse_temperature = 0.8, semantic_temperature = 0.5
+    )
+
+    return (SAMPLE_RATE, waveform.squeeze().cpu().numpy())
+
+
+
+# Gradio blocks demo    
+with gr.Blocks() as demo_blocks:
+    gr.Markdown("""<h1 align="center">🐶BARK with Vocos</h1>""")
+    gr.HTML("""<h3 style="text-align:center;">📢Audio Streaming powered by Gradio 🦾! </h3>""")
+    with gr.Group():
+      with gr.Row():
+        inp_text = gr.Textbox(label="What should Bark say?", info="Enter text here")
+        dd = gr.Dropdown(
+                speaker_embeddings,
+                value=None, 
+                label="Available voice presets", 
+                info="Defaults to no speaker embeddings!"
+                )
+    
+    with gr.Row():
+        btn = gr.Button("Bark with Vocos TTS")
+    
+    with gr.Row():
+        out_audio = gr.Audio(type="numpy", autoplay=True)
+        btn.click(generate_audio, [inp_text, dd], out_audio)
+
+demo_blocks.queue().launch(debug=True)