class Tool:
    def __init__(self):
        pass

    def __call__(self, text: str) -> str:
        return f"Generated speech for: {text}"

from generator import load_csm_1b
import torchaudio

class SesameTTS(Tool):
    def __init__(self):
        self.generator = load_csm_1b(device="cpu")

    def __call__(self, text: str) -> str:
        audio = self.generator.generate(
            text=text,
            speaker=0,
            context=[],
            max_audio_length_ms=10000,
        )
        path = "output.wav"
        torchaudio.save(path, audio.unsqueeze(0).cpu(), self.generator.sample_rate)
        return path