web ui for gradio

webui.py

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+import argparse
+import gradio as gr
+import soundfile as sf
+import numpy as np
+import tempfile
+from pathlib import Path
+from transformer_infer import PhemeClient
+
+def generate_audio(text, voice, temperature, top_k, max_new_tokens):
+    start_time = time.time()  # 開始時間を記録
+    audio_array = client.infer(text, voice=voice, temperature=temperature, top_k=top_k, max_new_tokens=max_new_tokens)
+
+    # NumPy 配列をオーディオファイルに変換
+    with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as temp_file:
+        sf.write(temp_file.name, audio_array, args.target_sample_rate)
+
+    return temp_file.name
+
+def parse_arguments():
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--manifest_path", type=str, default="demo/manifest.json")
+    parser.add_argument("--outputdir", type=str, default="demo/")
+    parser.add_argument("--featuredir", type=str, default="demo/")
+    parser.add_argument("--text_tokens_file", type=str, default="ckpt/unique_text_tokens.k2symbols")
+    parser.add_argument("--t2s_path", type=str, default="ckpt/t2s/")
+    parser.add_argument("--s2a_path", type=str, default="ckpt/s2a/s2a.ckpt")
+    parser.add_argument("--target_sample_rate", type=int, default=16_000)
+    return parser.parse_args()
+
+iface = gr.Interface(
+    fn=generate_audio,
+    inputs=[
+        gr.inputs.Textbox(label="Text"),
+        gr.inputs.Dropdown(voice_list, label="Voice"),
+        gr.Slider(minimum=0.1, maximum=1.0, value=0.7, step=0.1, label="Temperature"),
+        gr.Slider(minimum=1, maximum=500, value=210, step=1, label="Top K"),
+        gr.Slider(minimum=1, maximum=1000, value=750, step=1, label="Max New Tokens")
+    ],
+    outputs=gr.Audio(type="filepath", label="Generated Audio"),
+    title="Pheme TTS Demo",
+    description="Enter text and select a voice to generate speech.",
+)
+
+voice_list = ["male_voice"]  # 利用可能な声のリストに置き換えてください
+
+args = parse_arguments()
+client = PhemeClient(args)
+
+iface.launch(share=True)