70 lines
1.9 KiB
Python
70 lines
1.9 KiB
Python
from enum import Enum
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from typing import Optional
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from vocode.streaming.input_device.base_input_device import (
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BaseInputDevice,
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)
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from .audio_encoding import AudioEncoding
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from .model import BaseModel, TypedModel
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class TranscriberType(str, Enum):
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BASE = "transcriber_base"
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DEEPGRAM = "transcriber_deepgram"
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GOOGLE = "transcriber_google"
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ASSEMBLY_AI = "transcriber_assembly_ai"
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class EndpointingType(str, Enum):
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BASE = "endpointing_base"
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TIME_BASED = "endpointing_time_based"
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PUNCTUATION_BASED = "endpointing_punctuation_based"
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class EndpointingConfig(TypedModel, type=EndpointingType.BASE):
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pass
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class TimeEndpointingConfig(EndpointingConfig, type=EndpointingType.TIME_BASED):
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time_cutoff_seconds: float = 0.4
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class PunctuationEndpointingConfig(
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EndpointingConfig, type=EndpointingType.PUNCTUATION_BASED
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):
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time_cutoff_seconds: float = 0.4
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class TranscriberConfig(TypedModel, type=TranscriberType.BASE):
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sampling_rate: int
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audio_encoding: AudioEncoding
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chunk_size: int
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endpointing_config: Optional[EndpointingConfig] = None
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@classmethod
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def from_input_device(
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cls,
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input_device: BaseInputDevice,
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endpointing_config: Optional[EndpointingConfig] = None,
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):
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return cls(
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sampling_rate=input_device.sampling_rate,
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audio_encoding=input_device.audio_encoding,
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chunk_size=input_device.chunk_size,
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endpointing_config=endpointing_config,
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)
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class DeepgramTranscriberConfig(TranscriberConfig, type=TranscriberType.DEEPGRAM):
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model: Optional[str] = None
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should_warmup_model: bool = False
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version: Optional[str] = None
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class GoogleTranscriberConfig(TranscriberConfig, type=TranscriberType.GOOGLE):
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model: Optional[str] = None
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should_warmup_model: bool = False
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class AssemblyAITranscriberConfig(TranscriberConfig, type=TranscriberType.ASSEMBLY_AI):
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should_warmup_model: bool = False
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