from __future__ import annotations from typing import TYPE_CHECKING, Literal from pydantic import BaseModel, ConfigDict, Field from faster_whisper_server.core import Segment, Transcription, Word, segments_to_text if TYPE_CHECKING: from faster_whisper.transcribe import TranscriptionInfo # https://platform.openai.com/docs/api-reference/audio/json-object class TranscriptionJsonResponse(BaseModel): text: str @classmethod def from_segments(cls, segments: list[Segment]) -> TranscriptionJsonResponse: return cls(text=segments_to_text(segments)) @classmethod def from_transcription(cls, transcription: Transcription) -> TranscriptionJsonResponse: return cls(text=transcription.text) # https://platform.openai.com/docs/api-reference/audio/verbose-json-object class TranscriptionVerboseJsonResponse(BaseModel): task: str = "transcribe" language: str duration: float text: str words: list[Word] | None segments: list[Segment] @classmethod def from_segment(cls, segment: Segment, transcription_info: TranscriptionInfo) -> TranscriptionVerboseJsonResponse: return cls( language=transcription_info.language, duration=segment.end - segment.start, text=segment.text, words=segment.words if transcription_info.transcription_options.word_timestamps else None, segments=[segment], ) @classmethod def from_segments( cls, segments: list[Segment], transcription_info: TranscriptionInfo ) -> TranscriptionVerboseJsonResponse: return cls( language=transcription_info.language, duration=transcription_info.duration, text=segments_to_text(segments), segments=segments, words=Word.from_segments(segments) if transcription_info.transcription_options.word_timestamps else None, ) @classmethod def from_transcription(cls, transcription: Transcription) -> TranscriptionVerboseJsonResponse: return cls( language="english", # FIX: hardcoded duration=transcription.duration, text=transcription.text, words=transcription.words, segments=[], # FIX: hardcoded ) class ModelListResponse(BaseModel): data: list[ModelObject] object: Literal["list"] = "list" class ModelObject(BaseModel): id: str """The model identifier, which can be referenced in the API endpoints.""" created: int """The Unix timestamp (in seconds) when the model was created.""" object_: Literal["model"] = Field(serialization_alias="object") """The object type, which is always "model".""" owned_by: str """The organization that owns the model.""" language: list[str] = Field(default_factory=list) """List of ISO 639-3 supported by the model. It's possible that the list will be empty. This field is not a part of the OpenAI API spec and is added for convenience.""" # noqa: E501 model_config = ConfigDict( populate_by_name=True, json_schema_extra={ "examples": [ { "id": "Systran/faster-whisper-large-v3", "created": 1700732060, "object": "model", "owned_by": "Systran", }, { "id": "Systran/faster-distil-whisper-large-v3", "created": 1711378296, "object": "model", "owned_by": "Systran", }, { "id": "bofenghuang/whisper-large-v2-cv11-french-ct2", "created": 1687968011, "object": "model", "owned_by": "bofenghuang", }, ] }, ) TimestampGranularities = list[Literal["segment", "word"]] DEFAULT_TIMESTAMP_GRANULARITIES: TimestampGranularities = ["segment"] TIMESTAMP_GRANULARITIES_COMBINATIONS: list[TimestampGranularities] = [ [], # should be treated as ["segment"]. https://platform.openai.com/docs/api-reference/audio/createTranscription#audio-createtranscription-timestamp_granularities ["segment"], ["word"], ["word", "segment"], ["segment", "word"], # same as ["word", "segment"] but order is different ]