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Reinsert whisper model transcribing

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Marty Oehme 2023-08-23 13:22:55 +02:00
parent 3246469be2
commit 30fd269cd9
Signed by: Marty
GPG key ID: EDBF2ED917B2EF6A
6 changed files with 483 additions and 177 deletions
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Dockerfile
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@ -53,7 +53,7 @@ RUN mkdir -p ${VERBANOTE_OUTPUT_PATH}
RUN rm "${VIRTUAL_ENV}/bin/python" RUN rm "${VIRTUAL_ENV}/bin/python"
RUN ln -s "/opt/conda/bin/python" "${VIRTUAL_ENV}/bin/python" RUN ln -s "/opt/conda/bin/python" "${VIRTUAL_ENV}/bin/python"
RUN which python RUN which python
RUN ltt install --pytorch-computation-backend=cu117 torch torchvision torchaudio RUN ltt install --pytorch-computation-backend=cu117 torch==1.13.1 torchvision==0.14.1 torchaudio==0.13.1
COPY ./${APP_NAME} ./${APP_NAME} COPY ./${APP_NAME} ./${APP_NAME}

552
poetry.lock generated
View file

@ -185,6 +185,7 @@ files = [
] ]
[package.dependencies] [package.dependencies]
exceptiongroup = {version = "*", markers = "python_version < \"3.11\""}
idna = ">=2.8" idna = ">=2.8"
sniffio = ">=1.1" sniffio = ">=1.1"
@ -550,6 +551,35 @@ numpy = "*"
[package.extras] [package.extras]
cmawm = ["scipy"] cmawm = ["scipy"]
[[package]]
name = "cmake"
version = "3.27.2"
description = "CMake is an open-source, cross-platform family of tools designed to build, test and package software"
optional = false
python-versions = "*"
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{file = "cmake-3.27.2-py2.py3-none-win32.whl", hash = "sha256:53e12deb893da935e236f93accd47dbe2806620cd7654986234dc4487cc49652"},
{file = "cmake-3.27.2-py2.py3-none-win_amd64.whl", hash = "sha256:611f9722c68c40352d38a6c01960ab038c3d0419e7aee3bf18f95b23031e0dfe"},
{file = "cmake-3.27.2-py2.py3-none-win_arm64.whl", hash = "sha256:30620326b51ac2ce0d8f476747af6367a7ea21075c4d065fad9443904b07476a"},
{file = "cmake-3.27.2.tar.gz", hash = "sha256:7cd6e2d7d5a1125f8c26c4f65214f8c942e3f276f98c16cb62ae382c35609f25"},
]
[package.extras]
test = ["coverage (>=4.2)", "flake8 (>=3.0.4)", "path.py (>=11.5.0)", "pytest (>=3.0.3)", "pytest-cov (>=2.4.0)", "pytest-runner (>=2.9)", "pytest-virtualenv (>=1.7.0)", "scikit-build (>=0.10.0)", "setuptools (>=28.0.0)", "virtualenv (>=15.0.3)", "wheel"]
[[package]] [[package]]
name = "colorama" name = "colorama"
version = "0.4.6" version = "0.4.6"
@ -638,13 +668,13 @@ test-no-images = ["pytest", "pytest-cov", "wurlitzer"]
[[package]] [[package]]
name = "croniter" name = "croniter"
version = "1.3.15" version = "1.4.1"
description = "croniter provides iteration for datetime object with cron like format" description = "croniter provides iteration for datetime object with cron like format"
optional = false optional = false
python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
files = [ files = [
{file = "croniter-1.3.15-py2.py3-none-any.whl", hash = "sha256:f17f877be1d93b9e3191151584a19d8b367b017ab0febc8c5472b9300da61c4c"}, {file = "croniter-1.4.1-py2.py3-none-any.whl", hash = "sha256:9595da48af37ea06ec3a9f899738f1b2c1c13da3c38cea606ef7cd03ea421128"},
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] ]
[package.dependencies] [package.dependencies]
@ -760,6 +790,20 @@ files = [
dnspython = ">=2.0.0" dnspython = ">=2.0.0"
idna = ">=2.0.0" idna = ">=2.0.0"
[[package]]
name = "exceptiongroup"
version = "1.1.3"
description = "Backport of PEP 654 (exception groups)"
optional = false
python-versions = ">=3.7"
files = [
{file = "exceptiongroup-1.1.3-py3-none-any.whl", hash = "sha256:343280667a4585d195ca1cf9cef84a4e178c4b6cf2274caef9859782b567d5e3"},
{file = "exceptiongroup-1.1.3.tar.gz", hash = "sha256:097acd85d473d75af5bb98e41b61ff7fe35efe6675e4f9370ec6ec5126d160e9"},
]
[package.extras]
test = ["pytest (>=6)"]
[[package]] [[package]]
name = "fastapi" name = "fastapi"
version = "0.101.1" version = "0.101.1"
@ -1463,35 +1507,36 @@ pip = ">=22.3,<23.3"
[[package]] [[package]]
name = "lightning" name = "lightning"
version = "2.0.4" version = "2.0.7"
description = "Use Lightning Apps to build everything from production-ready, multi-cloud ML systems to simple research demos." description = "The Deep Learning framework to train, deploy, and ship AI products Lightning fast."
optional = false optional = false
python-versions = ">=3.8" python-versions = ">=3.8"
files = [ files = [
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{file = "lightning-2.0.4.tar.gz", hash = "sha256:f5f5ed75a657caa8931051590ed000d46bf1b8311ae89bb17a961c3f299dbf33"}, {file = "lightning-2.0.7.tar.gz", hash = "sha256:f05acd4ba846505d40125b4f9f0bda0804b2b0356e2ad2fd4e4bf7d1c61c8cc6"},
] ]
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arrow = ">=1.2.0,<3.0" arrow = ">=1.2.0,<3.0"
backoff = ">=2.2.1,<4.0"
beautifulsoup4 = ">=4.8.0,<6.0" beautifulsoup4 = ">=4.8.0,<6.0"
click = "<10.0" click = "<10.0"
croniter = ">=1.3.0,<1.4.0" croniter = ">=1.3.0,<1.5.0"
dateutils = "<2.0" dateutils = "<2.0"
deepdiff = ">=5.7.0,<8.0" deepdiff = ">=5.7.0,<8.0"
fastapi = ">=0.92.0,<2.0" fastapi = ">=0.92.0,<2.0"
fsspec = [ fsspec = [
{version = ">=2022.5.0,<2024.0"}, {version = ">=2022.5.0,<2025.0"},
{version = ">2021.06.0,<2025.0", extras = ["http"]}, {version = ">2021.06.0,<2025.0", extras = ["http"]},
] ]
inquirer = ">=2.10.0,<5.0" inquirer = ">=2.10.0,<5.0"
Jinja2 = "<5.0" Jinja2 = "<5.0"
lightning-cloud = ">=0.5.34" lightning-cloud = ">=0.5.37"
lightning-utilities = ">=0.7.0,<2.0" lightning-utilities = ">=0.7.0,<2.0"
numpy = ">=1.17.2,<3.0" numpy = ">=1.17.2,<3.0"
packaging = ">=17.1,<25.0" packaging = ">=17.1,<25.0"
psutil = "<7.0" psutil = "<7.0"
pydantic = ">=1.7.4,<4.0" pydantic = ">=1.7.4,<2.2.0"
python-multipart = ">=0.0.5,<2.0" python-multipart = ">=0.0.5,<2.0"
pytorch-lightning = "*" pytorch-lightning = "*"
PyYAML = ">=5.4,<8.0" PyYAML = ">=5.4,<8.0"
@ -1507,35 +1552,35 @@ typing-extensions = ">=4.0.0,<6.0"
urllib3 = "<4.0" urllib3 = "<4.0"
uvicorn = "<2.0" uvicorn = "<2.0"
websocket-client = "<3.0" websocket-client = "<3.0"
websockets = "<12.0" websockets = "<13.0"
[package.extras] [package.extras]
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typing-extensions = {version = ">=4.0", markers = "python_version < \"3.11\""}
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optional = ["python-socks", "wsaccel"] optional = ["python-socks", "wsaccel"]
test = ["websockets"] test = ["websockets"]
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[metadata] [metadata]
lock-version = "2.0" lock-version = "2.0"
python-versions = "^3.11" python-versions = "^3.10"
content-hash = "abe4e81cd59988f91e16746d9cc05c4d4f49c53957a682d03356ce2270950661" content-hash = "78450781b9a79630d7889c4c7561068d194f35d1ed5f90455ad2eb4fc4a937a2"

2
pyproject.toml
View file

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light-the-torch = "^0.7.5" light-the-torch = "^0.7.5"
hmmlearn = {git = "https://github.com/hmmlearn/hmmlearn.git"} hmmlearn = {git = "https://github.com/hmmlearn/hmmlearn.git"}
pyannote-audio = {git = "https://github.com/pyannote/pyannote-audio.git", rev = "develop"} pyannote-audio = {git = "https://github.com/pyannote/pyannote-audio.git", rev = "develop"}
#openai-whisper = { git = "https://github.com/openai/whisper.git" } openai-whisper = { git = "https://github.com/openai/whisper.git" }
[build-system] [build-system]
requires = ["poetry-core"] requires = ["poetry-core"]

13
verbanote/loaders.py
View file

@ -1,11 +1,12 @@
import locale import locale
from pathlib import Path from pathlib import Path
# from whisper import Whisper from whisper import Whisper, load_model
from pyannote.audio import Pipeline from pyannote.audio import Pipeline
import torch import torch
import static_ffmpeg import static_ffmpeg
import file_operations import file_operations
def prep() -> None: def prep() -> None:
locale.getpreferredencoding = lambda: "UTF-8" locale.getpreferredencoding = lambda: "UTF-8"
# download and add ffmpeg to env # download and add ffmpeg to env
@ -26,8 +27,8 @@ def diarization(access_token: str | None) -> Pipeline:
device = torch.device("cuda" if torch.cuda.is_available() else "cpu") device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
return pipeline.to(device) return pipeline.to(device)
#
# def whisper() -> Whisper: def whispermodel() -> Whisper:
# # LOAD MODEL INTO VRAM # LOAD MODEL INTO VRAM
# device = torch.device("cuda" if torch.cuda.is_available() else "cpu") device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
# return whisper.load_model("large", device=device) return load_model("large", device=device)

65
verbanote/process.py
View file

@ -4,7 +4,7 @@ import json
from pathlib import Path from pathlib import Path
from pyannote.audio import Pipeline from pyannote.audio import Pipeline
from pydub import AudioSegment from pydub import AudioSegment
# from whisper import Whisper from whisper import Whisper
MILLISECONDS_TO_SPACE = 2000 MILLISECONDS_TO_SPACE = 2000
@ -25,22 +25,53 @@ def diarize(audiofile: Path, pipeline: Pipeline, output_path: Path) -> Path:
return out_file return out_file
# def transcribe( def transcribe(
# model: Whisper, model: Whisper,
# diarized_groups: list, diarized_groups: list,
# output_path: Path, output_path: Path,
# lang: str = "en", lang: str = "en",
# word_timestamps: bool = True, word_timestamps: bool = True,
# ): ) -> None:
# for i in range(len(diarized_groups)): for i in range(len(diarized_groups)):
# f = {Path.joinpath(output_path, str(i))} f = {Path.joinpath(output_path, str(i))}
# audio_f = f"{f}.wav" audio_f = f"{f}.wav"
# json_f = f"{f}.json" json_f = f"{f}.json"
# result = model.transcribe( result = model.transcribe(
# audio=audio_f, language=lang, word_timestamps=word_timestamps audio=audio_f, language=lang, word_timestamps=word_timestamps
# ) )
# with open(json_f, "w") as outfile: with open(json_f, "w") as outfile:
# json.dump(result, outfile, indent=4) json.dump(result, outfile, indent=4)
# TODO clean up this mess
def output_txt(diarized_groups: list, transcription_path: Path) -> str:
txt = list("")
gidx = -1
for g in diarized_groups:
shift = re.findall(r"[0-9]+:[0-9]+:[0-9]+\.[0-9]+", string=g[0])[0]
shift = (
_millisec(shift) - MILLISECONDS_TO_SPACE
) # the start time in the original video
shift = max(shift, 0)
gidx += 1
with open(f"{Path.joinpath(transcription_path, str(gidx))}.json") as f:
captions = json.load(f)["segments"]
if captions:
speaker = g[0].split()[-1]
for c in captions:
txt.append(f"[{speaker}] {c['text']}\n")
txt.append("\n")
output = "".join(txt)
with open(
Path.joinpath(transcription_path, "capspeaker.txt"), "w", encoding="utf-8"
) as file:
file.write(output)
return output
def save_diarized_audio_files( def save_diarized_audio_files(

26
verbanote/rp_handler.py
View file

@ -16,12 +16,14 @@ access_token: str = os.environ.get("VERBANOTE_HF_TOKEN", "")
loaders.prep() loaders.prep()
diarize_pipeline = loaders.diarization(access_token) diarize_pipeline = loaders.diarization(access_token)
# whisper_model = loaders.whisper() whisper_model = loaders.whispermodel()
def handler(job): def handler(job):
input: dict = job["input"] input: dict = job["input"]
url: str | None = input.get("url") url: str | None = input.get("url")
lang: str | None = input.get("lang")
word_timestamps: str | None = input.get("word_timestamps")
if not url: if not url:
return {"error": "no file link provided"} return {"error": "no file link provided"}
@ -35,17 +37,21 @@ def handler(job):
diarized_groups = process.save_diarized_audio_files( diarized_groups = process.save_diarized_audio_files(
diarized, audiofile, output_path diarized, audiofile, output_path
) )
uploaded_file: str = file_operations.upload_to_oxo(file=diarized, expires=1) uploaded_diarization: str = file_operations.upload_to_oxo(file=diarized, expires=1)
# process.transcribe( process.transcribe(
# model=whisper_model, diarized_groups=diarized_groups, output_path=output_path model=whisper_model,
# ) diarized_groups=diarized_groups,
output_path=output_path,
lang=lang or "fr",
word_timestamps=word_timestamps or True,
)
transcription = process.output_txt(diarized_groups, output_path)
return { return {
"speaker_timings": "s3-address-to-speakers", "audiofile": str(audiofile),
"transcription_text": "s3-address-to-transcription", "diarization_url": uploaded_diarization,
"transcription_page": "web-address-to-deployment", "diarization": diarized_groups,
"audiofile_path": str(audiofile), "transcription_text": transcription,
"audio_url": uploaded_file,
} }