import enum

from pydantic import BaseModel, Field
from pydantic_settings import BaseSettings, SettingsConfigDict

SAMPLES_PER_SECOND = 16000
BYTES_PER_SAMPLE = 2
BYTES_PER_SECOND = SAMPLES_PER_SECOND * BYTES_PER_SAMPLE
# 2 BYTES = 16 BITS = 1 SAMPLE
# 1 SECOND OF AUDIO = 32000 BYTES = 16000 SAMPLES


# TODO: confirm names
class Model(enum.StrEnum):
    TINY_EN = "tiny.en"
    TINY = "tiny"
    BASE_EN = "base.en"
    BASE = "base"
    SMALL_EN = "small.en"
    SMALL = "small"
    MEDIUM_EN = "medium.en"
    MEDIUM = "medium"
    LARGE = "large"
    LARGE_V1 = "large-v1"
    LARGE_V2 = "large-v2"
    LARGE_V3 = "large-v3"
    DISTIL_SMALL_EN = "distil-small.en"
    DISTIL_MEDIUM_EN = "distil-medium.en"
    DISTIL_LARGE_V2 = "distil-large-v2"
    DISTIL_LARGE_V3 = "distil-large-v3"


class Device(enum.StrEnum):
    CPU = "cpu"
    CUDA = "cuda"
    AUTO = "auto"


# https://github.com/OpenNMT/CTranslate2/blob/master/docs/quantization.md
class Quantization(enum.StrEnum):
    INT8 = "int8"
    INT8_FLOAT16 = "int8_float16"
    INT8_BFLOAT16 = "int8_bfloat16"
    INT8_FLOAT32 = "int8_float32"
    INT16 = "int16"
    FLOAT16 = "float16"
    BFLOAT16 = "bfloat16"
    FLOAT32 = "float32"
    DEFAULT = "default"


class Language(enum.StrEnum):
    AF = "af"
    AM = "am"
    AR = "ar"
    AS = "as"
    AZ = "az"
    BA = "ba"
    BE = "be"
    BG = "bg"
    BN = "bn"
    BO = "bo"
    BR = "br"
    BS = "bs"
    CA = "ca"
    CS = "cs"
    CY = "cy"
    DA = "da"
    DE = "de"
    EL = "el"
    EN = "en"
    ES = "es"
    ET = "et"
    EU = "eu"
    FA = "fa"
    FI = "fi"
    FO = "fo"
    FR = "fr"
    GL = "gl"
    GU = "gu"
    HA = "ha"
    HAW = "haw"
    HE = "he"
    HI = "hi"
    HR = "hr"
    HT = "ht"
    HU = "hu"
    HY = "hy"
    ID = "id"
    IS = "is"
    IT = "it"
    JA = "ja"
    JW = "jw"
    KA = "ka"
    KK = "kk"
    KM = "km"
    KN = "kn"
    KO = "ko"
    LA = "la"
    LB = "lb"
    LN = "ln"
    LO = "lo"
    LT = "lt"
    LV = "lv"
    MG = "mg"
    MI = "mi"
    MK = "mk"
    ML = "ml"
    MN = "mn"
    MR = "mr"
    MS = "ms"
    MT = "mt"
    MY = "my"
    NE = "ne"
    NL = "nl"
    NN = "nn"
    NO = "no"
    OC = "oc"
    PA = "pa"
    PL = "pl"
    PS = "ps"
    PT = "pt"
    RO = "ro"
    RU = "ru"
    SA = "sa"
    SD = "sd"
    SI = "si"
    SK = "sk"
    SL = "sl"
    SN = "sn"
    SO = "so"
    SQ = "sq"
    SR = "sr"
    SU = "su"
    SV = "sv"
    SW = "sw"
    TA = "ta"
    TE = "te"
    TG = "tg"
    TH = "th"
    TK = "tk"
    TL = "tl"
    TR = "tr"
    TT = "tt"
    UK = "uk"
    UR = "ur"
    UZ = "uz"
    VI = "vi"
    YI = "yi"
    YO = "yo"
    YUE = "yue"
    ZH = "zh"


class WhisperConfig(BaseModel):
    model: Model = Field(default=Model.DISTIL_SMALL_EN)
    inference_device: Device = Field(default=Device.AUTO)
    compute_type: Quantization = Field(default=Quantization.DEFAULT)


class Config(BaseSettings):
    model_config = SettingsConfigDict(env_nested_delimiter="_")

    log_level: str = "info"
    whisper: WhisperConfig = WhisperConfig()
    """
    Max duration to for the next audio chunk before finilizing the transcription and closing the connection.
    """
    max_no_data_seconds: float = 1.0
    min_duration: float = 1.0
    word_timestamp_error_margin: float = 0.2
    inactivity_window_seconds: float = 3.0
    max_inactivity_seconds: float = 1.5


config = Config()