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from __future__ import annotations | |
from typing import TYPE_CHECKING, Literal | |
from pydantic import BaseModel, ConfigDict, Field | |
from faster_whisper_server import utils | |
if TYPE_CHECKING: | |
from faster_whisper.transcribe import Segment, TranscriptionInfo, Word | |
from faster_whisper_server.core import Transcription | |
# https://platform.openai.com/docs/api-reference/audio/json-object | |
class TranscriptionJsonResponse(BaseModel): | |
text: str | |
def from_segments(cls, segments: list[Segment]) -> TranscriptionJsonResponse: | |
return cls(text=utils.segments_text(segments)) | |
def from_transcription(cls, transcription: Transcription) -> TranscriptionJsonResponse: | |
return cls(text=transcription.text) | |
class WordObject(BaseModel): | |
start: float | |
end: float | |
word: str | |
probability: float | |
def from_word(cls, word: Word) -> WordObject: | |
return cls( | |
start=word.start, | |
end=word.end, | |
word=word.word, | |
probability=word.probability, | |
) | |
class SegmentObject(BaseModel): | |
id: int | |
seek: int | |
start: float | |
end: float | |
text: str | |
tokens: list[int] | |
temperature: float | |
avg_logprob: float | |
compression_ratio: float | |
no_speech_prob: float | |
def from_segment(cls, segment: Segment) -> SegmentObject: | |
return cls( | |
id=segment.id, | |
seek=segment.seek, | |
start=segment.start, | |
end=segment.end, | |
text=segment.text, | |
tokens=segment.tokens, | |
temperature=segment.temperature, | |
avg_logprob=segment.avg_logprob, | |
compression_ratio=segment.compression_ratio, | |
no_speech_prob=segment.no_speech_prob, | |
) | |
# 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[WordObject] | |
segments: list[SegmentObject] | |
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=([WordObject.from_word(word) for word in segment.words] if isinstance(segment.words, list) else []), | |
segments=[SegmentObject.from_segment(segment)], | |
) | |
def from_segments( | |
cls, segments: list[Segment], transcription_info: TranscriptionInfo | |
) -> TranscriptionVerboseJsonResponse: | |
return cls( | |
language=transcription_info.language, | |
duration=transcription_info.duration, | |
text=utils.segments_text(segments), | |
segments=[SegmentObject.from_segment(segment) for segment in segments], | |
words=[WordObject.from_word(word) for word in utils.words_from_segments(segments)], | |
) | |
def from_transcription(cls, transcription: Transcription) -> TranscriptionVerboseJsonResponse: | |
return cls( | |
language="english", # FIX: hardcoded | |
duration=transcription.duration, | |
text=transcription.text, | |
words=[ | |
WordObject( | |
start=word.start, | |
end=word.end, | |
word=word.text, | |
probability=word.probability, | |
) | |
for word in transcription.words | |
], | |
segments=[], # FIX: hardcoded | |
) | |
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.""" | |
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", | |
}, | |
] | |
}, | |
) | |