Spaces:
Running
on
CPU Upgrade
Running
on
CPU Upgrade
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
@@ -15,35 +15,8 @@ class ResponseFormat(enum.StrEnum):
|
|
15 |
TEXT = "text"
|
16 |
JSON = "json"
|
17 |
VERBOSE_JSON = "verbose_json"
|
18 |
-
|
19 |
-
|
20 |
-
# VTT = "vtt" # TODO
|
21 |
-
# 1
|
22 |
-
# 00:00:00,000 --> 00:00:09,220
|
23 |
-
# In his video on Large Language Models or LLMs, OpenAI co-founder and YouTuber Andrej Karpathy
|
24 |
-
#
|
25 |
-
# 2
|
26 |
-
# 00:00:09,220 --> 00:00:12,280
|
27 |
-
# likened LLMs to operating systems.
|
28 |
-
#
|
29 |
-
# 3
|
30 |
-
# 00:00:12,280 --> 00:00:13,280
|
31 |
-
# Karpathy said,
|
32 |
-
#
|
33 |
-
# SRT = "srt" # TODO
|
34 |
-
# WEBVTT
|
35 |
-
#
|
36 |
-
# 00:00:00.000 --> 00:00:09.220
|
37 |
-
# In his video on Large Language Models or LLMs, OpenAI co-founder and YouTuber Andrej Karpathy
|
38 |
-
#
|
39 |
-
# 00:00:09.220 --> 00:00:12.280
|
40 |
-
# likened LLMs to operating systems.
|
41 |
-
#
|
42 |
-
# 00:00:12.280 --> 00:00:13.280
|
43 |
-
# Karpathy said,
|
44 |
-
#
|
45 |
-
# 00:00:13.280 --> 00:00:19.799
|
46 |
-
# I see a lot of equivalence between this new LLM OS and operating systems of today.
|
47 |
|
48 |
|
49 |
class Device(enum.StrEnum):
|
|
|
15 |
TEXT = "text"
|
16 |
JSON = "json"
|
17 |
VERBOSE_JSON = "verbose_json"
|
18 |
+
SRT = "srt"
|
19 |
+
VTT = "vtt"
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
20 |
|
21 |
|
22 |
class Device(enum.StrEnum):
|
faster_whisper_server/core.py
CHANGED
@@ -172,6 +172,62 @@ def segments_to_text(segments: Iterable[Segment]) -> str:
|
|
172 |
return "".join(segment.text for segment in segments).strip()
|
173 |
|
174 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
175 |
def canonicalize_word(text: str) -> str:
|
176 |
text = text.lower()
|
177 |
# Remove non-alphabetic characters using regular expression
|
|
|
172 |
return "".join(segment.text for segment in segments).strip()
|
173 |
|
174 |
|
175 |
+
def srt_format_timestamp(ts: float) -> str:
|
176 |
+
hours = ts // 3600
|
177 |
+
minutes = (ts % 3600) // 60
|
178 |
+
seconds = ts % 60
|
179 |
+
milliseconds = (ts * 1000) % 1000
|
180 |
+
return f"{int(hours):02d}:{int(minutes):02d}:{int(seconds):02d},{int(milliseconds):03d}"
|
181 |
+
|
182 |
+
|
183 |
+
def test_srt_format_timestamp() -> None:
|
184 |
+
assert srt_format_timestamp(0.0) == "00:00:00,000"
|
185 |
+
assert srt_format_timestamp(1.0) == "00:00:01,000"
|
186 |
+
assert srt_format_timestamp(1.234) == "00:00:01,234"
|
187 |
+
assert srt_format_timestamp(60.0) == "00:01:00,000"
|
188 |
+
assert srt_format_timestamp(61.0) == "00:01:01,000"
|
189 |
+
assert srt_format_timestamp(61.234) == "00:01:01,234"
|
190 |
+
assert srt_format_timestamp(3600.0) == "01:00:00,000"
|
191 |
+
assert srt_format_timestamp(3601.0) == "01:00:01,000"
|
192 |
+
assert srt_format_timestamp(3601.234) == "01:00:01,234"
|
193 |
+
assert srt_format_timestamp(23423.4234) == "06:30:23,423"
|
194 |
+
|
195 |
+
|
196 |
+
def vtt_format_timestamp(ts: float) -> str:
|
197 |
+
hours = ts // 3600
|
198 |
+
minutes = (ts % 3600) // 60
|
199 |
+
seconds = ts % 60
|
200 |
+
milliseconds = (ts * 1000) % 1000
|
201 |
+
return f"{int(hours):02d}:{int(minutes):02d}:{int(seconds):02d}.{int(milliseconds):03d}"
|
202 |
+
|
203 |
+
|
204 |
+
def test_vtt_format_timestamp() -> None:
|
205 |
+
assert vtt_format_timestamp(0.0) == "00:00:00.000"
|
206 |
+
assert vtt_format_timestamp(1.0) == "00:00:01.000"
|
207 |
+
assert vtt_format_timestamp(1.234) == "00:00:01.234"
|
208 |
+
assert vtt_format_timestamp(60.0) == "00:01:00.000"
|
209 |
+
assert vtt_format_timestamp(61.0) == "00:01:01.000"
|
210 |
+
assert vtt_format_timestamp(61.234) == "00:01:01.234"
|
211 |
+
assert vtt_format_timestamp(3600.0) == "01:00:00.000"
|
212 |
+
assert vtt_format_timestamp(3601.0) == "01:00:01.000"
|
213 |
+
assert vtt_format_timestamp(3601.234) == "01:00:01.234"
|
214 |
+
assert vtt_format_timestamp(23423.4234) == "06:30:23.423"
|
215 |
+
|
216 |
+
|
217 |
+
def segments_to_vtt(segment: Segment, i: int) -> str:
|
218 |
+
start = segment.start if i > 0 else 0.0
|
219 |
+
result = f"{vtt_format_timestamp(start)} --> {vtt_format_timestamp(segment.end)}\n{segment.text}\n\n"
|
220 |
+
|
221 |
+
if i == 0:
|
222 |
+
return f"WEBVTT\n\n{result}"
|
223 |
+
else:
|
224 |
+
return result
|
225 |
+
|
226 |
+
|
227 |
+
def segments_to_srt(segment: Segment, i: int) -> str:
|
228 |
+
return f"{i + 1}\n{srt_format_timestamp(segment.start)} --> {srt_format_timestamp(segment.end)}\n{segment.text}\n\n"
|
229 |
+
|
230 |
+
|
231 |
def canonicalize_word(text: str) -> str:
|
232 |
text = text.lower()
|
233 |
# Remove non-alphabetic characters using regular expression
|
faster_whisper_server/main.py
CHANGED
@@ -33,7 +33,7 @@ from faster_whisper_server.config import (
|
|
33 |
Task,
|
34 |
config,
|
35 |
)
|
36 |
-
from faster_whisper_server.core import Segment, segments_to_text
|
37 |
from faster_whisper_server.logger import logger
|
38 |
from faster_whisper_server.server_models import (
|
39 |
ModelListResponse,
|
@@ -154,14 +154,28 @@ def segments_to_response(
|
|
154 |
segments: Iterable[Segment],
|
155 |
transcription_info: TranscriptionInfo,
|
156 |
response_format: ResponseFormat,
|
157 |
-
) ->
|
158 |
segments = list(segments)
|
159 |
if response_format == ResponseFormat.TEXT: # noqa: RET503
|
160 |
-
return segments_to_text(segments)
|
161 |
elif response_format == ResponseFormat.JSON:
|
162 |
-
return
|
|
|
|
|
|
|
163 |
elif response_format == ResponseFormat.VERBOSE_JSON:
|
164 |
-
return
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
165 |
|
166 |
|
167 |
def format_as_sse(data: str) -> str:
|
@@ -174,13 +188,17 @@ def segments_to_streaming_response(
|
|
174 |
response_format: ResponseFormat,
|
175 |
) -> StreamingResponse:
|
176 |
def segment_responses() -> Generator[str, None, None]:
|
177 |
-
for segment in segments:
|
178 |
if response_format == ResponseFormat.TEXT:
|
179 |
data = segment.text
|
180 |
elif response_format == ResponseFormat.JSON:
|
181 |
data = TranscriptionJsonResponse.from_segments([segment]).model_dump_json()
|
182 |
elif response_format == ResponseFormat.VERBOSE_JSON:
|
183 |
data = TranscriptionVerboseJsonResponse.from_segment(segment, transcription_info).model_dump_json()
|
|
|
|
|
|
|
|
|
184 |
yield format_as_sse(data)
|
185 |
|
186 |
return StreamingResponse(segment_responses(), media_type="text/event-stream")
|
@@ -211,7 +229,7 @@ def translate_file(
|
|
211 |
response_format: Annotated[ResponseFormat, Form()] = config.default_response_format,
|
212 |
temperature: Annotated[float, Form()] = 0.0,
|
213 |
stream: Annotated[bool, Form()] = False,
|
214 |
-
) ->
|
215 |
whisper = load_model(model)
|
216 |
segments, transcription_info = whisper.transcribe(
|
217 |
file.file,
|
@@ -247,7 +265,7 @@ def transcribe_file(
|
|
247 |
] = ["segment"],
|
248 |
stream: Annotated[bool, Form()] = False,
|
249 |
hotwords: Annotated[str | None, Form()] = None,
|
250 |
-
) ->
|
251 |
whisper = load_model(model)
|
252 |
segments, transcription_info = whisper.transcribe(
|
253 |
file.file,
|
|
|
33 |
Task,
|
34 |
config,
|
35 |
)
|
36 |
+
from faster_whisper_server.core import Segment, segments_to_srt, segments_to_text, segments_to_vtt
|
37 |
from faster_whisper_server.logger import logger
|
38 |
from faster_whisper_server.server_models import (
|
39 |
ModelListResponse,
|
|
|
154 |
segments: Iterable[Segment],
|
155 |
transcription_info: TranscriptionInfo,
|
156 |
response_format: ResponseFormat,
|
157 |
+
) -> Response:
|
158 |
segments = list(segments)
|
159 |
if response_format == ResponseFormat.TEXT: # noqa: RET503
|
160 |
+
return Response(segments_to_text(segments), media_type="text/plain")
|
161 |
elif response_format == ResponseFormat.JSON:
|
162 |
+
return Response(
|
163 |
+
TranscriptionJsonResponse.from_segments(segments).model_dump_json(),
|
164 |
+
media_type="application/json",
|
165 |
+
)
|
166 |
elif response_format == ResponseFormat.VERBOSE_JSON:
|
167 |
+
return Response(
|
168 |
+
TranscriptionVerboseJsonResponse.from_segments(segments, transcription_info).model_dump_json(),
|
169 |
+
media_type="application/json",
|
170 |
+
)
|
171 |
+
elif response_format == ResponseFormat.VTT:
|
172 |
+
return Response(
|
173 |
+
"".join(segments_to_vtt(segment, i) for i, segment in enumerate(segments)), media_type="text/vtt"
|
174 |
+
)
|
175 |
+
elif response_format == ResponseFormat.SRT:
|
176 |
+
return Response(
|
177 |
+
"".join(segments_to_srt(segment, i) for i, segment in enumerate(segments)), media_type="text/plain"
|
178 |
+
)
|
179 |
|
180 |
|
181 |
def format_as_sse(data: str) -> str:
|
|
|
188 |
response_format: ResponseFormat,
|
189 |
) -> StreamingResponse:
|
190 |
def segment_responses() -> Generator[str, None, None]:
|
191 |
+
for i, segment in enumerate(segments):
|
192 |
if response_format == ResponseFormat.TEXT:
|
193 |
data = segment.text
|
194 |
elif response_format == ResponseFormat.JSON:
|
195 |
data = TranscriptionJsonResponse.from_segments([segment]).model_dump_json()
|
196 |
elif response_format == ResponseFormat.VERBOSE_JSON:
|
197 |
data = TranscriptionVerboseJsonResponse.from_segment(segment, transcription_info).model_dump_json()
|
198 |
+
elif response_format == ResponseFormat.VTT:
|
199 |
+
data = segments_to_vtt(segment, i)
|
200 |
+
elif response_format == ResponseFormat.SRT:
|
201 |
+
data = segments_to_srt(segment, i)
|
202 |
yield format_as_sse(data)
|
203 |
|
204 |
return StreamingResponse(segment_responses(), media_type="text/event-stream")
|
|
|
229 |
response_format: Annotated[ResponseFormat, Form()] = config.default_response_format,
|
230 |
temperature: Annotated[float, Form()] = 0.0,
|
231 |
stream: Annotated[bool, Form()] = False,
|
232 |
+
) -> Response | StreamingResponse:
|
233 |
whisper = load_model(model)
|
234 |
segments, transcription_info = whisper.transcribe(
|
235 |
file.file,
|
|
|
265 |
] = ["segment"],
|
266 |
stream: Annotated[bool, Form()] = False,
|
267 |
hotwords: Annotated[str | None, Form()] = None,
|
268 |
+
) -> Response | StreamingResponse:
|
269 |
whisper = load_model(model)
|
270 |
segments, transcription_info = whisper.transcribe(
|
271 |
file.file,
|
pyproject.toml
CHANGED
@@ -18,7 +18,7 @@ dependencies = [
|
|
18 |
]
|
19 |
|
20 |
[project.optional-dependencies]
|
21 |
-
dev = ["ruff==0.5.3", "pytest", "basedpyright==1.13.0", "pytest-xdist"]
|
22 |
|
23 |
other = ["youtube-dl @ git+https://github.com/ytdl-org/youtube-dl.git@37cea84f775129ad715b9bcd617251c831fcc980", "aider-chat==0.39.0"]
|
24 |
|
|
|
18 |
]
|
19 |
|
20 |
[project.optional-dependencies]
|
21 |
+
dev = ["ruff==0.5.3", "pytest", "webvtt-py", "srt", "basedpyright==1.13.0", "pytest-xdist"]
|
22 |
|
23 |
other = ["youtube-dl @ git+https://github.com/ytdl-org/youtube-dl.git@37cea84f775129ad715b9bcd617251c831fcc980", "aider-chat==0.39.0"]
|
24 |
|
requirements-all.txt
CHANGED
@@ -496,7 +496,7 @@ scipy==1.13.1
|
|
496 |
# via aider-chat
|
497 |
semantic-version==2.10.0
|
498 |
# via gradio
|
499 |
-
setuptools==71.0.
|
500 |
# via ctranslate2
|
501 |
shellingham==1.5.4
|
502 |
# via typer
|
@@ -524,11 +524,13 @@ soupsieve==2.5
|
|
524 |
# via
|
525 |
# aider-chat
|
526 |
# beautifulsoup4
|
|
|
|
|
527 |
starlette==0.37.2
|
528 |
# via fastapi
|
529 |
streamlit==1.35.0
|
530 |
# via aider-chat
|
531 |
-
sympy==1.13.
|
532 |
# via onnxruntime
|
533 |
tenacity==8.3.0
|
534 |
# via
|
@@ -623,6 +625,8 @@ websockets==11.0.3
|
|
623 |
# via
|
624 |
# gradio-client
|
625 |
# uvicorn
|
|
|
|
|
626 |
yarl==1.9.4
|
627 |
# via
|
628 |
# aider-chat
|
|
|
496 |
# via aider-chat
|
497 |
semantic-version==2.10.0
|
498 |
# via gradio
|
499 |
+
setuptools==71.0.4
|
500 |
# via ctranslate2
|
501 |
shellingham==1.5.4
|
502 |
# via typer
|
|
|
524 |
# via
|
525 |
# aider-chat
|
526 |
# beautifulsoup4
|
527 |
+
srt==3.5.3
|
528 |
+
# via faster-whisper-server (pyproject.toml)
|
529 |
starlette==0.37.2
|
530 |
# via fastapi
|
531 |
streamlit==1.35.0
|
532 |
# via aider-chat
|
533 |
+
sympy==1.13.1
|
534 |
# via onnxruntime
|
535 |
tenacity==8.3.0
|
536 |
# via
|
|
|
625 |
# via
|
626 |
# gradio-client
|
627 |
# uvicorn
|
628 |
+
webvtt-py==0.5.1
|
629 |
+
# via faster-whisper-server (pyproject.toml)
|
630 |
yarl==1.9.4
|
631 |
# via
|
632 |
# aider-chat
|
requirements-dev.txt
CHANGED
@@ -146,7 +146,7 @@ numpy==1.26.4
|
|
146 |
# pandas
|
147 |
onnxruntime==1.18.1
|
148 |
# via faster-whisper
|
149 |
-
openai==1.
|
150 |
# via faster-whisper-server (pyproject.toml)
|
151 |
orjson==3.10.6
|
152 |
# via gradio
|
@@ -235,7 +235,7 @@ ruff==0.5.3
|
|
235 |
# gradio
|
236 |
semantic-version==2.10.0
|
237 |
# via gradio
|
238 |
-
setuptools==71.0.
|
239 |
# via ctranslate2
|
240 |
shellingham==1.5.4
|
241 |
# via typer
|
@@ -248,9 +248,11 @@ sniffio==1.3.1
|
|
248 |
# openai
|
249 |
soundfile==0.12.1
|
250 |
# via faster-whisper-server (pyproject.toml)
|
|
|
|
|
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))
|