Reinsert diarization dependencies
This commit is contained in:
parent
48095a1dc9
commit
64123a29e0
GPG key ID:
EDBF2ED917B2EF6A
8 changed files with 105 additions and 399 deletions
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@ -31,18 +31,21 @@ COPY ./poetry.lock ./pyproject.toml ./README.md ./
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FROM staging as worker
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ARG APP_NAME=verbanote
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ARG APP_PATH=/verbanote
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ARG VERBANOTE_OUTPUT_PATH=/transcriptions
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ARG VERBANOTE_OUTPUT_PATH=/out
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ARG VERBANOTE_INPUT_PATH=/in
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ENV APP_NAME=${APP_NAME}
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ENV APP_PATH=${APP_PATH}
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ENV VERBANOTE_OUTPUT_PATH=${VERBANOTE_OUTPUT_PATH}
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ENV VERBANOTE_INPUT_PATH=${VERBANOTE_INPUT_PATH}
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RUN mkdir -p ${VERBANOTE_INPUT_PATH}
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RUN mkdir -p ${VERBANOTE_OUTPUT_PATH}
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WORKDIR ${APP_PATH}
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RUN poetry install
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# installing the large models
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# RUN poetry run ltt install --pytorch-computation-backend=cu118 torch torchvision torchaudio
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RUN poetry run ltt install --pytorch-computation-backend=cu118 torch torchvision torchaudio
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COPY ./${APP_NAME} ./${APP_NAME}
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381
poetry.lock
generated
381
poetry.lock
generated
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@ -312,17 +312,17 @@ wcwidth = ">=0.1.4"
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[[package]]
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name = "boto3"
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version = "1.28.30"
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version = "1.28.31"
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description = "The AWS SDK for Python"
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optional = false
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python-versions = ">= 3.7"
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files = [
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{file = "boto3-1.28.30-py3-none-any.whl", hash = "sha256:e095ede98d3680e65966ab71f273b7d86938f5d853773ef96f4cb646277c2a4b"},
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{file = "boto3-1.28.30.tar.gz", hash = "sha256:2b509a959966a572f15db5768a18066ce1f53022ac53fca9421c620219fa3998"},
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{file = "boto3-1.28.31-py3-none-any.whl", hash = "sha256:2761f3249fe25c3ec1a8cd6b95fca2317747503e6f1d127daf6a3d2cdeb25680"},
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{file = "boto3-1.28.31.tar.gz", hash = "sha256:dc6d72470f6d8926b8cdc10ee7708d7ccdd36d6313c7aa298bc1cf6bedb8921e"},
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]
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[package.dependencies]
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botocore = ">=1.31.30,<1.32.0"
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botocore = ">=1.31.31,<1.32.0"
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jmespath = ">=0.7.1,<2.0.0"
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s3transfer = ">=0.6.0,<0.7.0"
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@ -331,13 +331,13 @@ crt = ["botocore[crt] (>=1.21.0,<2.0a0)"]
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[[package]]
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name = "botocore"
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version = "1.31.30"
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version = "1.31.31"
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description = "Low-level, data-driven core of boto 3."
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optional = false
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python-versions = ">= 3.7"
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files = [
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{file = "botocore-1.31.30-py3-none-any.whl", hash = "sha256:269f20dcadd8dfd0c26d0e6fbceb84814ff6638ff3aafcc5324b9fb9949a7051"},
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{file = "botocore-1.31.30.tar.gz", hash = "sha256:3cf6a9d7621b897c9ff23cd02113826141b3dd3d7e90273b661efc4dc05f84e2"},
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{file = "botocore-1.31.31-py3-none-any.whl", hash = "sha256:1eef14ae98e8662e43f7cf6d993c732793def02644e2d489c5171d3b9269e900"},
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{file = "botocore-1.31.31.tar.gz", hash = "sha256:950a49c5286fe1f6d72cfbe2910b9ddbdfbb907975ddc41cf38ac9709b4d1291"},
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]
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[package.dependencies]
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@ -550,35 +550,6 @@ numpy = "*"
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[package.extras]
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cmawm = ["scipy"]
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[[package]]
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name = "cmake"
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version = "3.27.2"
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description = "CMake is an open-source, cross-platform family of tools designed to build, test and package software"
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optional = false
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python-versions = "*"
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files = [
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{file = "cmake-3.27.2-py2.py3-none-macosx_10_10_universal2.macosx_10_10_x86_64.macosx_11_0_arm64.macosx_11_0_universal2.whl", hash = "sha256:96ac856c4d6b2104408848f0005a8ab2229d4135b171ea9a03e8c33039ede420"},
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{file = "cmake-3.27.2-py2.py3-none-manylinux2010_i686.manylinux_2_12_i686.whl", hash = "sha256:11fe6129d07982721c5965fd804a4056b8c6e9c4f482ac9e0fe41bb3abc1ab5f"},
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{file = "cmake-3.27.2-py2.py3-none-musllinux_1_1_aarch64.whl", hash = "sha256:7f7438c60ccc01765b67abfb1797787c3b9459d500a804ed70a4cc181bc02204"},
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{file = "cmake-3.27.2-py2.py3-none-musllinux_1_1_i686.whl", hash = "sha256:294f008734267e0eee1574ad1b911bed137bc907ab19d60a618dab4615aa1fca"},
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{file = "cmake-3.27.2-py2.py3-none-musllinux_1_1_ppc64le.whl", hash = "sha256:197a34dc62ee149ced343545fac67e5a30b93fda65250b065726f86ce92bdada"},
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{file = "cmake-3.27.2-py2.py3-none-musllinux_1_1_s390x.whl", hash = "sha256:afb46ad883b174fb64347802ba5878423551dbd5847bb64669c39a5957c06eb7"},
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{file = "cmake-3.27.2-py2.py3-none-musllinux_1_1_x86_64.whl", hash = "sha256:83611ffd155e270a6b13bbf0cfd4e8688ebda634f448aa2e3734006c745bf33f"},
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{file = "cmake-3.27.2-py2.py3-none-win32.whl", hash = "sha256:53e12deb893da935e236f93accd47dbe2806620cd7654986234dc4487cc49652"},
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{file = "cmake-3.27.2-py2.py3-none-win_amd64.whl", hash = "sha256:611f9722c68c40352d38a6c01960ab038c3d0419e7aee3bf18f95b23031e0dfe"},
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{file = "cmake-3.27.2-py2.py3-none-win_arm64.whl", hash = "sha256:30620326b51ac2ce0d8f476747af6367a7ea21075c4d065fad9443904b07476a"},
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{file = "cmake-3.27.2.tar.gz", hash = "sha256:7cd6e2d7d5a1125f8c26c4f65214f8c942e3f276f98c16cb62ae382c35609f25"},
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]
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[package.extras]
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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"]
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[[package]]
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name = "colorama"
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version = "0.4.6"
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@ -836,45 +807,45 @@ testing = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "diff-cover (>=7.5)", "p
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[[package]]
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name = "fonttools"
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version = "4.42.0"
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version = "4.42.1"
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description = "Tools to manipulate font files"
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optional = false
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python-versions = ">=3.8"
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files = [
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{file = "fonttools-4.42.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:9c456d1f23deff64ffc8b5b098718e149279abdea4d8692dba69172fb6a0d597"},
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||||
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||||
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|
||||
{file = "fonttools-4.42.1-cp38-cp38-win_amd64.whl", hash = "sha256:acb47f6f8680de24c1ab65ebde39dd035768e2a9b571a07c7b8da95f6c8815fd"},
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||||
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||||
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||||
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||||
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||||
{file = "fonttools-4.42.1-py3-none-any.whl", hash = "sha256:9398f244e28e0596e2ee6024f808b06060109e33ed38dcc9bded452fd9bbb853"},
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||||
{file = "fonttools-4.42.1.tar.gz", hash = "sha256:c391cd5af88aacaf41dd7cfb96eeedfad297b5899a39e12f4c2c3706d0a3329d"},
|
||||
]
|
||||
|
||||
[package.extras]
|
||||
|
|
@ -1000,24 +971,6 @@ smb = ["smbprotocol"]
|
|||
ssh = ["paramiko"]
|
||||
tqdm = ["tqdm"]
|
||||
|
||||
[[package]]
|
||||
name = "gdown"
|
||||
version = "4.7.1"
|
||||
description = "Google Drive direct download of big files."
|
||||
optional = false
|
||||
python-versions = "*"
|
||||
files = [
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||||
{file = "gdown-4.7.1-py3-none-any.whl", hash = "sha256:65d495699e7c2c61af0d0e9c32748fb4f79abaf80d747a87456c7be14aac2560"},
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|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
beautifulsoup4 = "*"
|
||||
filelock = "*"
|
||||
requests = {version = "*", extras = ["socks"]}
|
||||
six = "*"
|
||||
tqdm = "*"
|
||||
|
||||
[[package]]
|
||||
name = "greenlet"
|
||||
version = "2.0.2"
|
||||
|
|
@ -1628,16 +1581,6 @@ cli = ["fire"]
|
|||
docs = ["requests (>=2.0.0)"]
|
||||
typing = ["mypy (>=1.0.0)"]
|
||||
|
||||
[[package]]
|
||||
name = "lit"
|
||||
version = "16.0.6"
|
||||
description = "A Software Testing Tool"
|
||||
optional = false
|
||||
python-versions = "*"
|
||||
files = [
|
||||
{file = "lit-16.0.6.tar.gz", hash = "sha256:84623c9c23b6b14763d637f4e63e6b721b3446ada40bf7001d8fee70b8e77a9a"},
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||||
]
|
||||
|
||||
[[package]]
|
||||
name = "llvmlite"
|
||||
version = "0.40.1"
|
||||
|
|
@ -1845,17 +1788,6 @@ files = [
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|||
{file = "mdurl-0.1.2.tar.gz", hash = "sha256:bb413d29f5eea38f31dd4754dd7377d4465116fb207585f97bf925588687c1ba"},
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||||
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|
||||
|
||||
[[package]]
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||||
name = "more-itertools"
|
||||
version = "10.1.0"
|
||||
description = "More routines for operating on iterables, beyond itertools"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
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||||
{file = "more-itertools-10.1.0.tar.gz", hash = "sha256:626c369fa0eb37bac0291bce8259b332fd59ac792fa5497b59837309cd5b114a"},
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||||
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||||
|
||||
[[package]]
|
||||
name = "mpmath"
|
||||
version = "1.3.0"
|
||||
|
|
@ -2135,33 +2067,6 @@ files = [
|
|||
antlr4-python3-runtime = "==4.9.*"
|
||||
PyYAML = ">=5.1.0"
|
||||
|
||||
[[package]]
|
||||
name = "openai-whisper"
|
||||
version = "20230314"
|
||||
description = "Robust Speech Recognition via Large-Scale Weak Supervision"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = []
|
||||
develop = false
|
||||
|
||||
[package.dependencies]
|
||||
more-itertools = "*"
|
||||
numba = "*"
|
||||
numpy = "*"
|
||||
tiktoken = "0.3.3"
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||||
torch = "*"
|
||||
tqdm = "*"
|
||||
triton = "2.0.0"
|
||||
|
||||
[package.extras]
|
||||
dev = ["black", "flake8", "isort", "pytest", "scipy"]
|
||||
|
||||
[package.source]
|
||||
type = "git"
|
||||
url = "https://github.com/openai/whisper.git"
|
||||
reference = "HEAD"
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||||
resolved_reference = "e8622f9afc4eba139bf796c210f5c01081000472"
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||||
|
||||
[[package]]
|
||||
name = "optuna"
|
||||
version = "3.3.0"
|
||||
|
|
@ -2906,18 +2811,6 @@ files = [
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|||
[package.extras]
|
||||
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||||
|
||||
[[package]]
|
||||
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|
||||
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|
||||
description = "A Python SOCKS client module. See https://github.com/Anorov/PySocks for more information."
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||||
optional = false
|
||||
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
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||||
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||||
[[package]]
|
||||
name = "python-dateutil"
|
||||
version = "2.8.2"
|
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|
|
@ -3100,103 +2993,6 @@ files = [
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{file = "regex-2023.8.8-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:96979d753b1dc3b2169003e1854dc67bfc86edf93c01e84757927f810b8c3c93"},
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{file = "regex-2023.8.8-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:f0640913d2c1044d97e30d7c41728195fc37e54d190c5385eacb52115127b882"},
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{file = "regex-2023.8.8-cp38-cp38-win32.whl", hash = "sha256:0c59122ceccb905a941fb23b087b8eafc5290bf983ebcb14d2301febcbe199c7"},
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{file = "regex-2023.8.8-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:987b9ac04d0b38ef4f89fbc035e84a7efad9cdd5f1e29024f9289182c8d99e09"},
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{file = "regex-2023.8.8-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:4b694430b3f00eb02c594ff5a16db30e054c1b9589a043fe9174584c6efa8033"},
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||||
{file = "regex-2023.8.8-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:b2aeab3895d778155054abea5238d0eb9a72e9242bd4b43f42fd911ef9a13470"},
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||||
{file = "regex-2023.8.8-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:988631b9d78b546e284478c2ec15c8a85960e262e247b35ca5eaf7ee22f6050a"},
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{file = "regex-2023.8.8-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:9691a549c19c22d26a4f3b948071e93517bdf86e41b81d8c6ac8a964bb71e5a6"},
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||||
{file = "regex-2023.8.8-cp39-cp39-win32.whl", hash = "sha256:6ab2ed84bf0137927846b37e882745a827458689eb969028af8032b1b3dac78e"},
|
||||
{file = "regex-2023.8.8-cp39-cp39-win_amd64.whl", hash = "sha256:5543c055d8ec7801901e1193a51570643d6a6ab8751b1f7dd9af71af467538bb"},
|
||||
{file = "regex-2023.8.8.tar.gz", hash = "sha256:fcbdc5f2b0f1cd0f6a56cdb46fe41d2cce1e644e3b68832f3eeebc5fb0f7712e"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "requests"
|
||||
version = "2.31.0"
|
||||
|
|
@ -3212,7 +3008,6 @@ files = [
|
|||
certifi = ">=2017.4.17"
|
||||
charset-normalizer = ">=2,<4"
|
||||
idna = ">=2.5,<4"
|
||||
PySocks = {version = ">=1.5.6,<1.5.7 || >1.5.7", optional = true, markers = "extra == \"socks\""}
|
||||
urllib3 = ">=1.21.1,<3"
|
||||
|
||||
[package.extras]
|
||||
|
|
@ -3808,19 +3603,19 @@ widechars = ["wcwidth"]
|
|||
|
||||
[[package]]
|
||||
name = "tensorboardx"
|
||||
version = "2.6.2"
|
||||
version = "2.6.2.2"
|
||||
description = "TensorBoardX lets you watch Tensors Flow without Tensorflow"
|
||||
optional = false
|
||||
python-versions = "*"
|
||||
files = [
|
||||
{file = "tensorboardX-2.6.2-py2.py3-none-any.whl", hash = "sha256:951260a78c63dc97a89b1e6756c2bfc4c7dfd70782382e5b8b3a65e396a14149"},
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||||
{file = "tensorboardX-2.6.2.tar.gz", hash = "sha256:836cd33d751353494a6ac76aaeaa616a039e6594e1273467e7db99991624e31e"},
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||||
{file = "tensorboardX-2.6.2.2-py2.py3-none-any.whl", hash = "sha256:160025acbf759ede23fd3526ae9d9bfbfd8b68eb16c38a010ebe326dc6395db8"},
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||||
{file = "tensorboardX-2.6.2.2.tar.gz", hash = "sha256:c6476d7cd0d529b0b72f4acadb1269f9ed8b22f441e87a84f2a3b940bb87b666"},
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||||
]
|
||||
|
||||
[package.dependencies]
|
||||
numpy = "*"
|
||||
packaging = "*"
|
||||
protobuf = "*"
|
||||
protobuf = ">=3.20"
|
||||
|
||||
[[package]]
|
||||
name = "threadpoolctl"
|
||||
|
|
@ -3833,51 +3628,6 @@ files = [
|
|||
{file = "threadpoolctl-3.2.0.tar.gz", hash = "sha256:c96a0ba3bdddeaca37dc4cc7344aafad41cdb8c313f74fdfe387a867bba93355"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "tiktoken"
|
||||
version = "0.3.3"
|
||||
description = "tiktoken is a fast BPE tokeniser for use with OpenAI's models"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "tiktoken-0.3.3-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:d1f37fa75ba70c1bc7806641e8ccea1fba667d23e6341a1591ea333914c226a9"},
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{file = "tiktoken-0.3.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:3d7296c38392a943c2ccc0b61323086b8550cef08dcf6855de9949890dbc1fd3"},
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{file = "tiktoken-0.3.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3c84491965e139a905280ac28b74baaa13445b3678e07f96767089ad1ef5ee7b"},
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{file = "tiktoken-0.3.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:65970d77ea85ce6c7fce45131da9258cd58a802ffb29ead8f5552e331c025b2b"},
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||||
{file = "tiktoken-0.3.3-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:4db2c40f79f8f7a21a9fdbf1c6dee32dea77b0d7402355dc584a3083251d2e15"},
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{file = "tiktoken-0.3.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6674e4e37ab225020135cd66a392589623d5164c6456ba28cc27505abed10d9e"},
|
||||
{file = "tiktoken-0.3.3-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:4a0c1357f6191211c544f935d5aa3cb9d7abd118c8f3c7124196d5ecd029b4af"},
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||||
{file = "tiktoken-0.3.3-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:2e948d167fc3b04483cbc33426766fd742e7cefe5346cd62b0cbd7279ef59539"},
|
||||
{file = "tiktoken-0.3.3-cp311-cp311-win_amd64.whl", hash = "sha256:5dca434c8680b987eacde2dbc449e9ea4526574dbf9f3d8938665f638095be82"},
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||||
{file = "tiktoken-0.3.3-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:984758ebc07cd8c557345697c234f1f221bd730b388f4340dd08dffa50213a01"},
|
||||
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|
||||
{file = "tiktoken-0.3.3-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:210f8602228e4c5d706deeb389da5a152b214966a5aa558eec87b57a1969ced5"},
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||||
{file = "tiktoken-0.3.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:dd783564f80d4dc44ff0a64b13756ded8390ed2548549aefadbe156af9188307"},
|
||||
{file = "tiktoken-0.3.3-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:03f64bde9b4eb8338bf49c8532bfb4c3578f6a9a6979fc176d939f9e6f68b408"},
|
||||
{file = "tiktoken-0.3.3-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:1ac369367b6f5e5bd80e8f9a7766ac2a9c65eda2aa856d5f3c556d924ff82986"},
|
||||
{file = "tiktoken-0.3.3-cp38-cp38-win_amd64.whl", hash = "sha256:94600798891f78db780e5aa9321456cf355e54a4719fbd554147a628de1f163f"},
|
||||
{file = "tiktoken-0.3.3-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:e59db6fca8d5ccea302fe2888917364446d6f4201a25272a1a1c44975c65406a"},
|
||||
{file = "tiktoken-0.3.3-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:19340d8ba4d6fd729b2e3a096a547ded85f71012843008f97475f9db484869ee"},
|
||||
{file = "tiktoken-0.3.3-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:542686cbc9225540e3a10f472f82fa2e1bebafce2233a211dee8459e95821cfd"},
|
||||
{file = "tiktoken-0.3.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3a43612b2a09f4787c050163a216bf51123851859e9ab128ad03d2729826cde9"},
|
||||
{file = "tiktoken-0.3.3-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:a11674f0275fa75fb59941b703650998bd4acb295adbd16fc8af17051aaed19d"},
|
||||
{file = "tiktoken-0.3.3-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:65fc0a449630bab28c30b4adec257442a4706d79cffc2337c1d9df3e91825cdd"},
|
||||
{file = "tiktoken-0.3.3-cp39-cp39-win_amd64.whl", hash = "sha256:0b9a7a9a8b781a50ee9289e85e28771d7e113cc0c656eadfb6fc6d3a106ff9bb"},
|
||||
{file = "tiktoken-0.3.3.tar.gz", hash = "sha256:97b58b7bfda945791ec855e53d166e8ec20c6378942b93851a6c919ddf9d0496"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
regex = ">=2022.1.18"
|
||||
requests = ">=2.26.0"
|
||||
|
||||
[package.extras]
|
||||
blobfile = ["blobfile (>=2)"]
|
||||
|
||||
[[package]]
|
||||
name = "tomli"
|
||||
version = "2.0.1"
|
||||
|
|
@ -4076,43 +3826,6 @@ files = [
|
|||
docs = ["myst-parser", "pydata-sphinx-theme", "sphinx"]
|
||||
test = ["argcomplete (>=2.0)", "pre-commit", "pytest", "pytest-mock"]
|
||||
|
||||
[[package]]
|
||||
name = "triton"
|
||||
version = "2.0.0"
|
||||
description = "A language and compiler for custom Deep Learning operations"
|
||||
optional = false
|
||||
python-versions = "*"
|
||||
files = [
|
||||
{file = "triton-2.0.0-1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:38806ee9663f4b0f7cd64790e96c579374089e58f49aac4a6608121aa55e2505"},
|
||||
{file = "triton-2.0.0-1-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:226941c7b8595219ddef59a1fdb821e8c744289a132415ddd584facedeb475b1"},
|
||||
{file = "triton-2.0.0-1-cp36-cp36m-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:4c9fc8c89874bc48eb7e7b2107a9b8d2c0bf139778637be5bfccb09191685cfd"},
|
||||
{file = "triton-2.0.0-1-cp37-cp37m-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:d2684b6a60b9f174f447f36f933e9a45f31db96cb723723ecd2dcfd1c57b778b"},
|
||||
{file = "triton-2.0.0-1-cp38-cp38-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:9d4978298b74fcf59a75fe71e535c092b023088933b2f1df933ec32615e4beef"},
|
||||
{file = "triton-2.0.0-1-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:74f118c12b437fb2ca25e1a04759173b517582fcf4c7be11913316c764213656"},
|
||||
{file = "triton-2.0.0-1-pp37-pypy37_pp73-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:9618815a8da1d9157514f08f855d9e9ff92e329cd81c0305003eb9ec25cc5add"},
|
||||
{file = "triton-2.0.0-1-pp38-pypy38_pp73-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:1aca3303629cd3136375b82cb9921727f804e47ebee27b2677fef23005c3851a"},
|
||||
{file = "triton-2.0.0-1-pp39-pypy39_pp73-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:e3e13aa8b527c9b642e3a9defcc0fbd8ffbe1c80d8ac8c15a01692478dc64d8a"},
|
||||
{file = "triton-2.0.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8f05a7e64e4ca0565535e3d5d3405d7e49f9d308505bb7773d21fb26a4c008c2"},
|
||||
{file = "triton-2.0.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bb4b99ca3c6844066e516658541d876c28a5f6e3a852286bbc97ad57134827fd"},
|
||||
{file = "triton-2.0.0-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:47b4d70dc92fb40af553b4460492c31dc7d3a114a979ffb7a5cdedb7eb546c08"},
|
||||
{file = "triton-2.0.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:fedce6a381901b1547e0e7e1f2546e4f65dca6d91e2d8a7305a2d1f5551895be"},
|
||||
{file = "triton-2.0.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:75834f27926eab6c7f00ce73aaf1ab5bfb9bec6eb57ab7c0bfc0a23fac803b4c"},
|
||||
{file = "triton-2.0.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0117722f8c2b579cd429e0bee80f7731ae05f63fe8e9414acd9a679885fcbf42"},
|
||||
{file = "triton-2.0.0-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bcd9be5d0c2e45d2b7e6ddc6da20112b6862d69741576f9c3dbaf941d745ecae"},
|
||||
{file = "triton-2.0.0-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:42a0d2c3fc2eab4ba71384f2e785fbfd47aa41ae05fa58bf12cb31dcbd0aeceb"},
|
||||
{file = "triton-2.0.0-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:52c47b72c72693198163ece9d90a721299e4fb3b8e24fd13141e384ad952724f"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
cmake = "*"
|
||||
filelock = "*"
|
||||
lit = "*"
|
||||
torch = "*"
|
||||
|
||||
[package.extras]
|
||||
tests = ["autopep8", "flake8", "isort", "numpy", "pytest", "scipy (>=1.7.1)"]
|
||||
tutorials = ["matplotlib", "pandas", "tabulate"]
|
||||
|
||||
[[package]]
|
||||
name = "typer"
|
||||
version = "0.9.0"
|
||||
|
|
@ -4544,4 +4257,4 @@ multidict = ">=4.0"
|
|||
[metadata]
|
||||
lock-version = "2.0"
|
||||
python-versions = "^3.11"
|
||||
content-hash = "a978218afe88e07486717a7841980f9826e1d5ae2b5238dbe361db3d5cab81b1"
|
||||
content-hash = "abe4e81cd59988f91e16746d9cc05c4d4f49c53957a682d03356ce2270950661"
|
||||
|
|
|
|||
|
|
@ -13,6 +13,9 @@ static-ffmpeg = "^2.5"
|
|||
runpod = "^1.1.3"
|
||||
pydub = "^0.25.1"
|
||||
#light-the-torch = "^0.7.5"
|
||||
light-the-torch = "^0.7.5"
|
||||
hmmlearn = {git = "https://github.com/hmmlearn/hmmlearn.git"}
|
||||
pyannote-audio = {git = "https://github.com/pyannote/pyannote-audio.git", rev = "develop"}
|
||||
#openai-whisper = { git = "https://github.com/openai/whisper.git" }
|
||||
#hmmlearn = {git = "https://github.com/hmmlearn/hmmlearn.git"}
|
||||
#pyannote-audio = {git = "https://github.com/pyannote/pyannote-audio.git", rev = "develop"}
|
||||
|
|
|
|||
|
|
@ -1,4 +1,5 @@
|
|||
from pathlib import Path
|
||||
import logging
|
||||
import requests
|
||||
import subprocess
|
||||
|
||||
|
|
@ -6,11 +7,13 @@ import subprocess
|
|||
def download_from_url(url: str, input_path: Path) -> Path:
|
||||
resp = requests.get(url)
|
||||
if not resp.ok:
|
||||
logging.error(f"Created error code: {resp.status_code}")
|
||||
raise requests.exceptions.HTTPError()
|
||||
# TODO think about implementing a naming scheme based on url path
|
||||
fname = Path.joinpath(input_path, "inputfile")
|
||||
with open(fname, mode="wb") as file:
|
||||
file.write(resp.content)
|
||||
logging.info(f"Downloaded input file: {fname}")
|
||||
return fname
|
||||
|
||||
|
||||
|
|
@ -41,4 +44,5 @@ def convert_to_wav(file: Path, output_path: Path) -> Path:
|
|||
fn,
|
||||
]
|
||||
)
|
||||
logging.info(f"Converted {file} to wav format: {fn}")
|
||||
return fn
|
||||
|
|
|
|||
|
|
@ -1,8 +1,8 @@
|
|||
import locale
|
||||
from pathlib import Path
|
||||
# from whisper import Whisper
|
||||
# from pyannote.audio import Pipeline
|
||||
# import torch
|
||||
from pyannote.audio import Pipeline
|
||||
import torch
|
||||
import static_ffmpeg
|
||||
import file_operations
|
||||
|
||||
|
|
@ -18,14 +18,14 @@ def audiofile(url: str, input_path: Path) -> Path:
|
|||
file.unlink()
|
||||
return file_wav
|
||||
|
||||
#
|
||||
# def diarization(access_token: str | None) -> Pipeline:
|
||||
# pipeline = Pipeline.from_pretrained(
|
||||
# "pyannote/speaker-diarization", use_auth_token=access_token
|
||||
# )
|
||||
# device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
|
||||
# return pipeline.to(device)
|
||||
#
|
||||
|
||||
def diarization(access_token: str | None) -> Pipeline:
|
||||
pipeline = Pipeline.from_pretrained(
|
||||
"pyannote/speaker-diarization", use_auth_token=access_token
|
||||
)
|
||||
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
|
||||
return pipeline.to(device)
|
||||
|
||||
#
|
||||
# def whisper() -> Whisper:
|
||||
# # LOAD MODEL INTO VRAM
|
||||
|
|
|
|||
|
|
@ -1,24 +0,0 @@
|
|||
## SETTINGS FOR LATER
|
||||
from pathlib import Path
|
||||
|
||||
# @markdown Enter the URL of the YouTube video, or the path to the video/audio file you want to transcribe, give the output path, etc. and run the cell. HTML file embeds the video for YouTube, and audio for media files.
|
||||
|
||||
Source = "Youtube" # @param ['Youtube', 'File (Google Drive)']
|
||||
# @markdown ---
|
||||
# @markdown #### **Youtube video**
|
||||
video_url = "https://youtu.be/hpZFJctBUHQ" # @param {type:"string"}
|
||||
# store_audio = True #@param {type:"boolean"}
|
||||
# @markdown ---
|
||||
# @markdown #### **Google Drive video or audio path (mp4, wav, mp3)**
|
||||
video_path = "/content/drive/MyDrive/Customer_Service.mp3" # @param {type:"string"}
|
||||
# @markdown ---
|
||||
output_path = "/content/transcript/" # @param {type:"string"}
|
||||
output_path = str(Path(output_path))
|
||||
# @markdown ---
|
||||
# @markdown #### **Title for transcription of media file**
|
||||
audio_title = "Sample Order Taking" # @param {type:"string"}
|
||||
# @markdown ---
|
||||
# @markdown #### Copy a token from your [Hugging Face tokens page](https://huggingface.co/settings/tokens) and paste it below.
|
||||
access_token = "hf_" # @param {type:"string"}
|
||||
# @markdown ---
|
||||
# @markdown **Run this cell again if you change the video.**
|
||||
|
|
@ -4,7 +4,7 @@ import json
|
|||
from pathlib import Path
|
||||
from pyannote.audio import Pipeline
|
||||
from pydub import AudioSegment
|
||||
from whisper import Whisper
|
||||
# from whisper import Whisper
|
||||
|
||||
MILLISECONDS_TO_SPACE = 2000
|
||||
|
||||
|
|
@ -12,8 +12,8 @@ MILLISECONDS_TO_SPACE = 2000
|
|||
def diarize(audiofile: Path, pipeline: Pipeline, output_path: Path) -> Path:
|
||||
audiofile_prepended = _add_audio_silence(audiofile)
|
||||
|
||||
DEMO_FILE = {"uri": "blabla", "audio": audiofile_prepended}
|
||||
dz = pipeline(DEMO_FILE)
|
||||
DIARIZE_FILE = {"uri": "not-important", "audio": audiofile_prepended}
|
||||
dz = pipeline(DIARIZE_FILE)
|
||||
|
||||
out_file = Path.joinpath(output_path, "diarization.txt")
|
||||
with open(out_file, "w") as text_file:
|
||||
|
|
@ -25,22 +25,22 @@ def diarize(audiofile: Path, pipeline: Pipeline, output_path: Path) -> Path:
|
|||
return out_file
|
||||
|
||||
|
||||
def transcribe(
|
||||
model: Whisper,
|
||||
diarized_groups: list,
|
||||
output_path: Path,
|
||||
lang: str = "en",
|
||||
word_timestamps: bool = True,
|
||||
):
|
||||
for i in range(len(diarized_groups)):
|
||||
f = {Path.joinpath(output_path, str(i))}
|
||||
audio_f = f"{f}.wav"
|
||||
json_f = f"{f}.json"
|
||||
result = model.transcribe(
|
||||
audio=audio_f, language=lang, word_timestamps=word_timestamps
|
||||
)
|
||||
with open(json_f, "w") as outfile:
|
||||
json.dump(result, outfile, indent=4)
|
||||
# def transcribe(
|
||||
# model: Whisper,
|
||||
# diarized_groups: list,
|
||||
# output_path: Path,
|
||||
# lang: str = "en",
|
||||
# word_timestamps: bool = True,
|
||||
# ):
|
||||
# for i in range(len(diarized_groups)):
|
||||
# f = {Path.joinpath(output_path, str(i))}
|
||||
# audio_f = f"{f}.wav"
|
||||
# json_f = f"{f}.json"
|
||||
# result = model.transcribe(
|
||||
# audio=audio_f, language=lang, word_timestamps=word_timestamps
|
||||
# )
|
||||
# with open(json_f, "w") as outfile:
|
||||
# json.dump(result, outfile, indent=4)
|
||||
|
||||
|
||||
def save_diarized_audio_files(
|
||||
|
|
|
|||
|
|
@ -1,22 +1,26 @@
|
|||
import logging
|
||||
from pathlib import Path
|
||||
import runpod
|
||||
from runpod.serverless import os
|
||||
import loaders
|
||||
# import process
|
||||
import file_operations
|
||||
|
||||
import process
|
||||
|
||||
output_path:Path = Path(os.environ.get("VERBANOTE_OUTPUT_PATH", "/in"))
|
||||
input_path:Path = Path(os.environ.get("VERBANOTE_INPUT_PATH", "/out"))
|
||||
logging.basicConfig(level=logging.DEBUG)
|
||||
|
||||
input_path: Path = Path(os.environ.get("VERBANOTE_INPUT_PATH", "/in"))
|
||||
output_path: Path = Path(os.environ.get("VERBANOTE_OUTPUT_PATH", "/out"))
|
||||
|
||||
access_token: str = os.environ.get("VERBANOTE_HF_TOKEN", "")
|
||||
|
||||
loaders.prep()
|
||||
# diarize_pipeline = loaders.diarization(access_token)
|
||||
diarize_pipeline = loaders.diarization(access_token)
|
||||
# whisper_model = loaders.whisper()
|
||||
|
||||
|
||||
def handler(job):
|
||||
input:dict = job["input"]
|
||||
input: dict = job["input"]
|
||||
url: str | None = input.get("url")
|
||||
|
||||
if not url:
|
||||
|
|
@ -27,10 +31,11 @@ def handler(job):
|
|||
except Exception:
|
||||
return {"error": "audiofile import failed"}
|
||||
|
||||
# diarized = process.diarize(audiofile, diarize_pipeline, output_path)
|
||||
# diarized_groups = process.save_diarized_audio_files(
|
||||
# diarized, audiofile, output_path
|
||||
# )
|
||||
diarized = process.diarize(audiofile, diarize_pipeline, output_path)
|
||||
diarized_groups = process.save_diarized_audio_files(
|
||||
diarized, audiofile, output_path
|
||||
)
|
||||
uploaded_file: str = file_operations.upload_to_oxo(file=diarized, expires=1)
|
||||
# process.transcribe(
|
||||
# model=whisper_model, diarized_groups=diarized_groups, output_path=output_path
|
||||
# )
|
||||
|
|
@ -39,9 +44,11 @@ def handler(job):
|
|||
"speaker_timings": "s3-address-to-speakers",
|
||||
"transcription_text": "s3-address-to-transcription",
|
||||
"transcription_page": "web-address-to-deployment",
|
||||
"audiofile_path": str(audiofile)
|
||||
"audiofile_path": str(audiofile),
|
||||
"audio_url": uploaded_file,
|
||||
}
|
||||
|
||||
|
||||
# speakers = {
|
||||
# # speaker, textboxcolor, speaker color
|
||||
# "SPEAKER_00": ("SPEAKER00", "white", "darkgreen"),
|
||||
|
|
|
|||
Loading…
Reference in a new issue