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Configuration error
Configuration error
Fedir Zadniprovskyi
commited on
Commit
·
323aa51
1
Parent(s):
2a79f48
feat: handle srt and vtt response formats
Browse files- faster_whisper_server/config.py +2 -29
- faster_whisper_server/core.py +56 -0
- faster_whisper_server/main.py +26 -8
- pyproject.toml +1 -1
- requirements-all.txt +6 -2
- requirements-dev.txt +7 -3
- requirements.txt +3 -3
- tests/conftest.py +2 -0
- tests/sse_test.py +38 -0
faster_whisper_server/config.py
CHANGED
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@@ -15,35 +15,8 @@ class ResponseFormat(enum.StrEnum):
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TEXT = "text"
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JSON = "json"
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VERBOSE_JSON = "verbose_json"
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# VTT = "vtt" # TODO
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# 1
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# 00:00:00,000 --> 00:00:09,220
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# In his video on Large Language Models or LLMs, OpenAI co-founder and YouTuber Andrej Karpathy
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#
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# 2
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# 00:00:09,220 --> 00:00:12,280
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# likened LLMs to operating systems.
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#
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# 3
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# 00:00:12,280 --> 00:00:13,280
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# Karpathy said,
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#
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# SRT = "srt" # TODO
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# WEBVTT
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#
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# 00:00:00.000 --> 00:00:09.220
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# In his video on Large Language Models or LLMs, OpenAI co-founder and YouTuber Andrej Karpathy
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#
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# 00:00:09.220 --> 00:00:12.280
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# likened LLMs to operating systems.
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#
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# 00:00:12.280 --> 00:00:13.280
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# Karpathy said,
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#
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# 00:00:13.280 --> 00:00:19.799
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# I see a lot of equivalence between this new LLM OS and operating systems of today.
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class Device(enum.StrEnum):
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TEXT = "text"
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JSON = "json"
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VERBOSE_JSON = "verbose_json"
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SRT = "srt"
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VTT = "vtt"
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class Device(enum.StrEnum):
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faster_whisper_server/core.py
CHANGED
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@@ -172,6 +172,62 @@ def segments_to_text(segments: Iterable[Segment]) -> str:
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return "".join(segment.text for segment in segments).strip()
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def canonicalize_word(text: str) -> str:
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text = text.lower()
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# Remove non-alphabetic characters using regular expression
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return "".join(segment.text for segment in segments).strip()
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def srt_format_timestamp(ts: float) -> str:
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hours = ts // 3600
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minutes = (ts % 3600) // 60
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seconds = ts % 60
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milliseconds = (ts * 1000) % 1000
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return f"{int(hours):02d}:{int(minutes):02d}:{int(seconds):02d},{int(milliseconds):03d}"
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def test_srt_format_timestamp() -> None:
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assert srt_format_timestamp(0.0) == "00:00:00,000"
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assert srt_format_timestamp(1.0) == "00:00:01,000"
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assert srt_format_timestamp(1.234) == "00:00:01,234"
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assert srt_format_timestamp(60.0) == "00:01:00,000"
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assert srt_format_timestamp(61.0) == "00:01:01,000"
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assert srt_format_timestamp(61.234) == "00:01:01,234"
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assert srt_format_timestamp(3600.0) == "01:00:00,000"
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assert srt_format_timestamp(3601.0) == "01:00:01,000"
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assert srt_format_timestamp(3601.234) == "01:00:01,234"
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assert srt_format_timestamp(23423.4234) == "06:30:23,423"
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def vtt_format_timestamp(ts: float) -> str:
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hours = ts // 3600
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minutes = (ts % 3600) // 60
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seconds = ts % 60
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milliseconds = (ts * 1000) % 1000
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return f"{int(hours):02d}:{int(minutes):02d}:{int(seconds):02d}.{int(milliseconds):03d}"
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def test_vtt_format_timestamp() -> None:
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assert vtt_format_timestamp(0.0) == "00:00:00.000"
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assert vtt_format_timestamp(1.0) == "00:00:01.000"
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assert vtt_format_timestamp(1.234) == "00:00:01.234"
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assert vtt_format_timestamp(60.0) == "00:01:00.000"
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assert vtt_format_timestamp(61.0) == "00:01:01.000"
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assert vtt_format_timestamp(61.234) == "00:01:01.234"
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assert vtt_format_timestamp(3600.0) == "01:00:00.000"
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assert vtt_format_timestamp(3601.0) == "01:00:01.000"
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assert vtt_format_timestamp(3601.234) == "01:00:01.234"
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assert vtt_format_timestamp(23423.4234) == "06:30:23.423"
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def segments_to_vtt(segment: Segment, i: int) -> str:
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start = segment.start if i > 0 else 0.0
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result = f"{vtt_format_timestamp(start)} --> {vtt_format_timestamp(segment.end)}\n{segment.text}\n\n"
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if i == 0:
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return f"WEBVTT\n\n{result}"
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else:
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return result
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def segments_to_srt(segment: Segment, i: int) -> str:
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return f"{i + 1}\n{srt_format_timestamp(segment.start)} --> {srt_format_timestamp(segment.end)}\n{segment.text}\n\n"
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def canonicalize_word(text: str) -> str:
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text = text.lower()
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# Remove non-alphabetic characters using regular expression
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faster_whisper_server/main.py
CHANGED
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@@ -33,7 +33,7 @@ from faster_whisper_server.config import (
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Task,
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config,
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)
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from faster_whisper_server.core import Segment, segments_to_text
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from faster_whisper_server.logger import logger
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from faster_whisper_server.server_models import (
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ModelListResponse,
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@@ -154,14 +154,28 @@ def segments_to_response(
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segments: Iterable[Segment],
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transcription_info: TranscriptionInfo,
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response_format: ResponseFormat,
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) ->
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segments = list(segments)
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if response_format == ResponseFormat.TEXT: # noqa: RET503
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return segments_to_text(segments)
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elif response_format == ResponseFormat.JSON:
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return
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elif response_format == ResponseFormat.VERBOSE_JSON:
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-
return
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def format_as_sse(data: str) -> str:
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@@ -174,13 +188,17 @@ def segments_to_streaming_response(
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response_format: ResponseFormat,
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) -> StreamingResponse:
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def segment_responses() -> Generator[str, None, None]:
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for segment in segments:
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if response_format == ResponseFormat.TEXT:
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data = segment.text
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elif response_format == ResponseFormat.JSON:
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data = TranscriptionJsonResponse.from_segments([segment]).model_dump_json()
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elif response_format == ResponseFormat.VERBOSE_JSON:
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data = TranscriptionVerboseJsonResponse.from_segment(segment, transcription_info).model_dump_json()
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yield format_as_sse(data)
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return StreamingResponse(segment_responses(), media_type="text/event-stream")
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@@ -211,7 +229,7 @@ def translate_file(
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response_format: Annotated[ResponseFormat, Form()] = config.default_response_format,
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temperature: Annotated[float, Form()] = 0.0,
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stream: Annotated[bool, Form()] = False,
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) ->
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whisper = load_model(model)
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segments, transcription_info = whisper.transcribe(
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file.file,
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@@ -247,7 +265,7 @@ def transcribe_file(
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] = ["segment"],
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stream: Annotated[bool, Form()] = False,
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hotwords: Annotated[str | None, Form()] = None,
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) ->
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whisper = load_model(model)
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segments, transcription_info = whisper.transcribe(
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file.file,
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Task,
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config,
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)
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from faster_whisper_server.core import Segment, segments_to_srt, segments_to_text, segments_to_vtt
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from faster_whisper_server.logger import logger
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from faster_whisper_server.server_models import (
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ModelListResponse,
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segments: Iterable[Segment],
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transcription_info: TranscriptionInfo,
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response_format: ResponseFormat,
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) -> Response:
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segments = list(segments)
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if response_format == ResponseFormat.TEXT: # noqa: RET503
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return Response(segments_to_text(segments), media_type="text/plain")
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elif response_format == ResponseFormat.JSON:
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return Response(
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TranscriptionJsonResponse.from_segments(segments).model_dump_json(),
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media_type="application/json",
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)
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elif response_format == ResponseFormat.VERBOSE_JSON:
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return Response(
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TranscriptionVerboseJsonResponse.from_segments(segments, transcription_info).model_dump_json(),
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media_type="application/json",
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)
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elif response_format == ResponseFormat.VTT:
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return Response(
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"".join(segments_to_vtt(segment, i) for i, segment in enumerate(segments)), media_type="text/vtt"
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)
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elif response_format == ResponseFormat.SRT:
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return Response(
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"".join(segments_to_srt(segment, i) for i, segment in enumerate(segments)), media_type="text/plain"
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)
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def format_as_sse(data: str) -> str:
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response_format: ResponseFormat,
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) -> StreamingResponse:
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def segment_responses() -> Generator[str, None, None]:
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for i, segment in enumerate(segments):
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if response_format == ResponseFormat.TEXT:
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data = segment.text
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elif response_format == ResponseFormat.JSON:
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data = TranscriptionJsonResponse.from_segments([segment]).model_dump_json()
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elif response_format == ResponseFormat.VERBOSE_JSON:
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data = TranscriptionVerboseJsonResponse.from_segment(segment, transcription_info).model_dump_json()
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elif response_format == ResponseFormat.VTT:
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data = segments_to_vtt(segment, i)
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elif response_format == ResponseFormat.SRT:
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data = segments_to_srt(segment, i)
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yield format_as_sse(data)
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return StreamingResponse(segment_responses(), media_type="text/event-stream")
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response_format: Annotated[ResponseFormat, Form()] = config.default_response_format,
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temperature: Annotated[float, Form()] = 0.0,
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stream: Annotated[bool, Form()] = False,
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) -> Response | StreamingResponse:
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whisper = load_model(model)
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segments, transcription_info = whisper.transcribe(
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file.file,
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] = ["segment"],
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stream: Annotated[bool, Form()] = False,
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hotwords: Annotated[str | None, Form()] = None,
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) -> Response | StreamingResponse:
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whisper = load_model(model)
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segments, transcription_info = whisper.transcribe(
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file.file,
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pyproject.toml
CHANGED
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@@ -18,7 +18,7 @@ dependencies = [
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]
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[project.optional-dependencies]
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dev = ["ruff==0.5.3", "pytest", "basedpyright==1.13.0", "pytest-xdist"]
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other = ["youtube-dl @ git+https://github.com/ytdl-org/youtube-dl.git@37cea84f775129ad715b9bcd617251c831fcc980", "aider-chat==0.39.0"]
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]
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[project.optional-dependencies]
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dev = ["ruff==0.5.3", "pytest", "webvtt-py", "srt", "basedpyright==1.13.0", "pytest-xdist"]
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other = ["youtube-dl @ git+https://github.com/ytdl-org/youtube-dl.git@37cea84f775129ad715b9bcd617251c831fcc980", "aider-chat==0.39.0"]
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requirements-all.txt
CHANGED
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@@ -496,7 +496,7 @@ scipy==1.13.1
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# via aider-chat
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semantic-version==2.10.0
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# via gradio
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-
setuptools==71.0.
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# via ctranslate2
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shellingham==1.5.4
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# via typer
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@@ -524,11 +524,13 @@ soupsieve==2.5
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# via
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# aider-chat
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# beautifulsoup4
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starlette==0.37.2
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# via fastapi
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streamlit==1.35.0
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# via aider-chat
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-
sympy==1.13.
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# via onnxruntime
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tenacity==8.3.0
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# via
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@@ -623,6 +625,8 @@ websockets==11.0.3
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# via
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# gradio-client
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# uvicorn
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yarl==1.9.4
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# via
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# aider-chat
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# via aider-chat
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semantic-version==2.10.0
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# via gradio
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+
setuptools==71.0.4
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# via ctranslate2
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shellingham==1.5.4
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# via typer
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# via
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# aider-chat
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# beautifulsoup4
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srt==3.5.3
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# via faster-whisper-server (pyproject.toml)
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starlette==0.37.2
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# via fastapi
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streamlit==1.35.0
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# via aider-chat
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+
sympy==1.13.1
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# via onnxruntime
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tenacity==8.3.0
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# via
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# via
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# gradio-client
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# uvicorn
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+
webvtt-py==0.5.1
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# via faster-whisper-server (pyproject.toml)
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yarl==1.9.4
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# via
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# aider-chat
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requirements-dev.txt
CHANGED
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@@ -146,7 +146,7 @@ numpy==1.26.4
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# pandas
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onnxruntime==1.18.1
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# via faster-whisper
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-
openai==1.
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# via faster-whisper-server (pyproject.toml)
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orjson==3.10.6
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# via gradio
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@@ -235,7 +235,7 @@ ruff==0.5.3
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# gradio
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semantic-version==2.10.0
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# via gradio
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-
setuptools==71.0.
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# via ctranslate2
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shellingham==1.5.4
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# via typer
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@@ -248,9 +248,11 @@ sniffio==1.3.1
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# openai
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soundfile==0.12.1
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# via faster-whisper-server (pyproject.toml)
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|
|
|
|
| 251 |
starlette==0.37.2
|
| 252 |
# via fastapi
|
| 253 |
-
sympy==1.13.
|
| 254 |
# via onnxruntime
|
| 255 |
tokenizers==0.19.1
|
| 256 |
# via faster-whisper
|
|
@@ -295,3 +297,5 @@ websockets==11.0.3
|
|
| 295 |
# via
|
| 296 |
# gradio-client
|
| 297 |
# uvicorn
|
|
|
|
|
|
|
|
|
| 146 |
# pandas
|
| 147 |
onnxruntime==1.18.1
|
| 148 |
# via faster-whisper
|
| 149 |
+
openai==1.36.0
|
| 150 |
# via faster-whisper-server (pyproject.toml)
|
| 151 |
orjson==3.10.6
|
| 152 |
# via gradio
|
|
|
|
| 235 |
# gradio
|
| 236 |
semantic-version==2.10.0
|
| 237 |
# via gradio
|
| 238 |
+
setuptools==71.0.4
|
| 239 |
# via ctranslate2
|
| 240 |
shellingham==1.5.4
|
| 241 |
# via typer
|
|
|
|
| 248 |
# openai
|
| 249 |
soundfile==0.12.1
|
| 250 |
# via faster-whisper-server (pyproject.toml)
|
| 251 |
+
srt==3.5.3
|
| 252 |
+
# via faster-whisper-server (pyproject.toml)
|
| 253 |
starlette==0.37.2
|
| 254 |
# via fastapi
|
| 255 |
+
sympy==1.13.1
|
| 256 |
# via onnxruntime
|
| 257 |
tokenizers==0.19.1
|
| 258 |
# via faster-whisper
|
|
|
|
| 297 |
# via
|
| 298 |
# gradio-client
|
| 299 |
# uvicorn
|
| 300 |
+
webvtt-py==0.5.1
|
| 301 |
+
# via faster-whisper-server (pyproject.toml)
|
requirements.txt
CHANGED
|
@@ -138,7 +138,7 @@ numpy==1.26.4
|
|
| 138 |
# pandas
|
| 139 |
onnxruntime==1.18.1
|
| 140 |
# via faster-whisper
|
| 141 |
-
openai==1.
|
| 142 |
# via faster-whisper-server (pyproject.toml)
|
| 143 |
orjson==3.10.6
|
| 144 |
# via gradio
|
|
@@ -216,7 +216,7 @@ ruff==0.5.3
|
|
| 216 |
# via gradio
|
| 217 |
semantic-version==2.10.0
|
| 218 |
# via gradio
|
| 219 |
-
setuptools==71.0.
|
| 220 |
# via ctranslate2
|
| 221 |
shellingham==1.5.4
|
| 222 |
# via typer
|
|
@@ -231,7 +231,7 @@ soundfile==0.12.1
|
|
| 231 |
# via faster-whisper-server (pyproject.toml)
|
| 232 |
starlette==0.37.2
|
| 233 |
# via fastapi
|
| 234 |
-
sympy==1.13.
|
| 235 |
# via onnxruntime
|
| 236 |
tokenizers==0.19.1
|
| 237 |
# via faster-whisper
|
|
|
|
| 138 |
# pandas
|
| 139 |
onnxruntime==1.18.1
|
| 140 |
# via faster-whisper
|
| 141 |
+
openai==1.36.0
|
| 142 |
# via faster-whisper-server (pyproject.toml)
|
| 143 |
orjson==3.10.6
|
| 144 |
# via gradio
|
|
|
|
| 216 |
# via gradio
|
| 217 |
semantic-version==2.10.0
|
| 218 |
# via gradio
|
| 219 |
+
setuptools==71.0.4
|
| 220 |
# via ctranslate2
|
| 221 |
shellingham==1.5.4
|
| 222 |
# via typer
|
|
|
|
| 231 |
# via faster-whisper-server (pyproject.toml)
|
| 232 |
starlette==0.37.2
|
| 233 |
# via fastapi
|
| 234 |
+
sympy==1.13.1
|
| 235 |
# via onnxruntime
|
| 236 |
tokenizers==0.19.1
|
| 237 |
# via faster-whisper
|
tests/conftest.py
CHANGED
|
@@ -1,10 +1,12 @@
|
|
| 1 |
from collections.abc import Generator
|
| 2 |
import logging
|
|
|
|
| 3 |
|
| 4 |
from fastapi.testclient import TestClient
|
| 5 |
from openai import OpenAI
|
| 6 |
import pytest
|
| 7 |
|
|
|
|
| 8 |
from faster_whisper_server.main import app
|
| 9 |
|
| 10 |
disable_loggers = ["multipart.multipart", "faster_whisper"]
|
|
|
|
| 1 |
from collections.abc import Generator
|
| 2 |
import logging
|
| 3 |
+
import os
|
| 4 |
|
| 5 |
from fastapi.testclient import TestClient
|
| 6 |
from openai import OpenAI
|
| 7 |
import pytest
|
| 8 |
|
| 9 |
+
os.environ["WHISPER__MODEL"] = "Systran/faster-whisper-tiny.en"
|
| 10 |
from faster_whisper_server.main import app
|
| 11 |
|
| 12 |
disable_loggers = ["multipart.multipart", "faster_whisper"]
|
tests/sse_test.py
CHANGED
|
@@ -4,6 +4,9 @@ import os
|
|
| 4 |
from fastapi.testclient import TestClient
|
| 5 |
from httpx_sse import connect_sse
|
| 6 |
import pytest
|
|
|
|
|
|
|
|
|
|
| 7 |
|
| 8 |
from faster_whisper_server.server_models import (
|
| 9 |
TranscriptionJsonResponse,
|
|
@@ -61,3 +64,38 @@ def test_streaming_transcription_verbose_json(client: TestClient, file_path: str
|
|
| 61 |
with connect_sse(client, "POST", endpoint, **kwargs) as event_source:
|
| 62 |
for event in event_source.iter_sse():
|
| 63 |
TranscriptionVerboseJsonResponse(**json.loads(event.data))
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 4 |
from fastapi.testclient import TestClient
|
| 5 |
from httpx_sse import connect_sse
|
| 6 |
import pytest
|
| 7 |
+
import srt
|
| 8 |
+
import webvtt
|
| 9 |
+
import webvtt.vtt
|
| 10 |
|
| 11 |
from faster_whisper_server.server_models import (
|
| 12 |
TranscriptionJsonResponse,
|
|
|
|
| 64 |
with connect_sse(client, "POST", endpoint, **kwargs) as event_source:
|
| 65 |
for event in event_source.iter_sse():
|
| 66 |
TranscriptionVerboseJsonResponse(**json.loads(event.data))
|
| 67 |
+
|
| 68 |
+
|
| 69 |
+
def test_transcription_vtt(client: TestClient) -> None:
|
| 70 |
+
with open("audio.wav", "rb") as f:
|
| 71 |
+
data = f.read()
|
| 72 |
+
kwargs = {
|
| 73 |
+
"files": {"file": ("audio.wav", data, "audio/wav")},
|
| 74 |
+
"data": {"response_format": "vtt", "stream": False},
|
| 75 |
+
}
|
| 76 |
+
response = client.post("/v1/audio/transcriptions", **kwargs)
|
| 77 |
+
assert response.status_code == 200
|
| 78 |
+
assert response.headers["content-type"] == "text/vtt; charset=utf-8"
|
| 79 |
+
text = response.text
|
| 80 |
+
webvtt.from_string(text)
|
| 81 |
+
text = text.replace("WEBVTT", "YO")
|
| 82 |
+
with pytest.raises(webvtt.vtt.MalformedFileError):
|
| 83 |
+
webvtt.from_string(text)
|
| 84 |
+
|
| 85 |
+
|
| 86 |
+
def test_transcription_srt(client: TestClient) -> None:
|
| 87 |
+
with open("audio.wav", "rb") as f:
|
| 88 |
+
data = f.read()
|
| 89 |
+
kwargs = {
|
| 90 |
+
"files": {"file": ("audio.wav", data, "audio/wav")},
|
| 91 |
+
"data": {"response_format": "srt", "stream": False},
|
| 92 |
+
}
|
| 93 |
+
response = client.post("/v1/audio/transcriptions", **kwargs)
|
| 94 |
+
assert response.status_code == 200
|
| 95 |
+
assert "text/plain" in response.headers["content-type"]
|
| 96 |
+
|
| 97 |
+
text = response.text
|
| 98 |
+
list(srt.parse(text))
|
| 99 |
+
text = text.replace("1", "YO")
|
| 100 |
+
with pytest.raises(srt.SRTParseError):
|
| 101 |
+
list(srt.parse(text))
|