import gradio as gr
from huggingface_hub import hf_hub_download
from sbv2_bindings import TTSModel

bert = hf_hub_download("googlefan/sbv2_onnx_models", "deberta.onnx")
tokenizer = hf_hub_download("googlefan/sbv2_onnx_models", "tokenizer.json")


def load_and_synthesize(text: str, path: str, sdp: float = 0.0, speed: float = 1.0):
    model = TTSModel.from_path(bert, tokenizer)
    uid = "default"
    path = path.split("/")
    filename = "/".join(path[2:])
    repo_id = "/".join(path[:2])
    model.load_sbv2file_from_path(uid, hf_hub_download(repo_id, filename))
    print("All setup is done!")
    return model.synthesize(text, uid, 0, sdp, 1.0 / speed)


iface = gr.Interface(
    fn=load_and_synthesize,
    concurrency_limit=1,
    inputs=[
        gr.Textbox(lines=2, placeholder="テキスト"),
        gr.Textbox(lines=1, max_lines=1, placeholder="パス"),
        gr.Slider(minimum=0.0, maximum=1.0, step=0.01, value=0.0, label="SDP"),
        gr.Slider(minimum=0.5, maximum=2.0, step=0.1, value=1.0, label="Speed"),
    ],
    outputs="audio",
    title="SBV2音声合成",
    description="テキストとモデルのパスを入力して音声を生成します。SDPと速度を調整して音声の質を変更できます。",
    examples=[
        [
            "おはようございます。",
            "googlefan/sbv2_personal_models/tsukuyomi.sbv2",
            0.0,
            1.0,
        ],
        [
            "今日の天気は晴れです。場所によっては雨が降るでしょう。",
            "googlefan/sbv2_personal_models/iroha.sbv2",
            0.0,
            1.1,
        ],
    ],
)

iface.launch()