"""Hugging Face configuration for Gnani Prisma v2.5 (STT) and Gnani Timbre v2.0 (TTS).

This config stores defaults for STT and TTS inference via Gnani's hosted API.
No model weights are shipped — all inference happens server-side.
"""

from transformers import PretrainedConfig


class GnaniVachanaConfig(PretrainedConfig):
    """Configuration for the Gnani Prisma v2.5 (STT) and Gnani Timbre v2.0 (TTS) hosted speech API.

    This is a thin wrapper around :class:`~transformers.PretrainedConfig` that
    stores language, voice, and audio-format defaults.  The actual model weights
    live on Gnani's servers; nothing is downloaded locally.

    Parameters
    ----------
    default_language_code : str
        BCP-47 language code used when none is specified at inference time.
    default_format : str
        STT output format (``"verbatim"`` or ``"formatted"``).
    default_voice : str
        Timbre v2.0 TTS voice ID used when none is specified.
    default_sample_rate : int
        TTS output sample rate in Hz.
    default_container : str
        TTS audio container format.
    default_encoding : str
        TTS audio encoding.
    use_streaming : bool
        If ``True``, pipeline will use WebSocket / SSE streaming clients
        instead of one-shot REST clients.
    **kwargs
        Forwarded to :class:`~transformers.PretrainedConfig`.
    """

    model_type = "gnani-vachana"

    def __init__(
        self,
        default_language_code: str = "hi-IN",
        default_format: str = "verbatim",
        default_voice: str = "Pranav",
        default_sample_rate: int = 22050,
        default_container: str = "wav",
        default_encoding: str = "linear_pcm",
        use_streaming: bool = False,
        **kwargs,
    ):
        super().__init__(**kwargs)
        self.default_language_code = default_language_code
        self.default_format = default_format
        self.default_voice = default_voice
        self.default_sample_rate = default_sample_rate
        self.default_container = default_container
        self.default_encoding = default_encoding
        self.use_streaming = use_streaming