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feat: add spam detection

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Maxim Slipenko 2024-10-08 19:10:54 +03:00
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commit b4eac59f80
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@ -609,6 +609,22 @@ typer = ">=0.12.3"
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@ -988,6 +1077,8 @@ dash-extensions = "^1.0.18"
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ruff = ["ruff (==0.5.1)"]
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sentencepiece = ["protobuf", "sentencepiece (>=0.1.91,!=0.1.92)"]
serving = ["fastapi", "pydantic", "starlette", "uvicorn"]
sigopt = ["sigopt"]
sklearn = ["scikit-learn"]
speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"]
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tf-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
tiktoken = ["blobfile", "tiktoken"]
timm = ["timm (<=0.9.16)"]
tokenizers = ["tokenizers (>=0.20,<0.21)"]
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torch-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"]
torch-vision = ["Pillow (>=10.0.1,<=15.0)", "torchvision"]
torchhub = ["filelock", "huggingface-hub (>=0.23.2,<1.0)", "importlib-metadata", "numpy (>=1.17)", "packaging (>=20.0)", "protobuf", "regex (!=2019.12.17)", "requests", "sentencepiece (>=0.1.91,!=0.1.92)", "tokenizers (>=0.20,<0.21)", "torch", "tqdm (>=4.27)"]
video = ["av (==9.2.0)", "decord (==0.6.0)"]
vision = ["Pillow (>=10.0.1,<=15.0)"]
[[package]] [[package]]
name = "typer" name = "typer"
version = "0.12.3" version = "0.12.3"
@ -2217,4 +2899,4 @@ test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools",
[metadata] [metadata]
lock-version = "2.0" lock-version = "2.0"
python-versions = ">=3.10,<3.13" python-versions = ">=3.10,<3.13"
content-hash = "d9a8013e760cfe29900565540b9638ba421dc0f63ae288e785f42d62de17e88c" content-hash = "7f6109c0854917f9ab1a856123c5b73171bbb3ad779f871adc825f2437a0247f"

5
src/altlinux/pyproject.toml
View File

@ -15,3 +15,8 @@ karkas-blocks = { path = "../karkas_blocks", develop = true }
[build-system] [build-system]
requires = ["poetry-core"] requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api" build-backend = "poetry.core.masonry.api"
[[tool.poetry.source]]
name = "pytorch-cpu"
url = "https://download.pytorch.org/whl/cpu"
priority = "explicit"

684
src/gnomik/poetry.lock generated
View File

@ -712,6 +712,22 @@ uvicorn = {version = ">=0.15.0", extras = ["standard"]}
[package.extras] [package.extras]
standard = ["uvicorn[standard] (>=0.15.0)"] standard = ["uvicorn[standard] (>=0.15.0)"]
[[package]]
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version = "3.16.1"
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python-versions = ">=3.8"
files = [
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typing = ["typing-extensions (>=4.12.2)"]
[[package]] [[package]]
name = "flask" name = "flask"
version = "3.0.3" version = "3.0.3"
@ -835,6 +851,45 @@ files = [
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] ]
[[package]]
name = "fsspec"
version = "2024.9.0"
description = "File-system specification"
optional = false
python-versions = ">=3.8"
files = [
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[package.extras]
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adl = ["adlfs"]
arrow = ["pyarrow (>=1)"]
dask = ["dask", "distributed"]
dev = ["pre-commit", "ruff"]
doc = ["numpydoc", "sphinx", "sphinx-design", "sphinx-rtd-theme", "yarl"]
dropbox = ["dropbox", "dropboxdrivefs", "requests"]
full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "dask", "distributed", "dropbox", "dropboxdrivefs", "fusepy", "gcsfs", "libarchive-c", "ocifs", "panel", "paramiko", "pyarrow (>=1)", "pygit2", "requests", "s3fs", "smbprotocol", "tqdm"]
fuse = ["fusepy"]
gcs = ["gcsfs"]
git = ["pygit2"]
github = ["requests"]
gs = ["gcsfs"]
gui = ["panel"]
hdfs = ["pyarrow (>=1)"]
http = ["aiohttp (!=4.0.0a0,!=4.0.0a1)"]
libarchive = ["libarchive-c"]
oci = ["ocifs"]
s3 = ["s3fs"]
sftp = ["paramiko"]
smb = ["smbprotocol"]
ssh = ["paramiko"]
test = ["aiohttp (!=4.0.0a0,!=4.0.0a1)", "numpy", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "requests"]
test-downstream = ["aiobotocore (>=2.5.4,<3.0.0)", "dask-expr", "dask[dataframe,test]", "moto[server] (>4,<5)", "pytest-timeout", "xarray"]
test-full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "cloudpickle", "dask", "distributed", "dropbox", "dropboxdrivefs", "fastparquet", "fusepy", "gcsfs", "jinja2", "kerchunk", "libarchive-c", "lz4", "notebook", "numpy", "ocifs", "pandas", "panel", "paramiko", "pyarrow", "pyarrow (>=1)", "pyftpdlib", "pygit2", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "python-snappy", "requests", "smbprotocol", "tqdm", "urllib3", "zarr", "zstandard"]
tqdm = ["tqdm"]
[[package]] [[package]]
name = "h11" name = "h11"
version = "0.14.0" version = "0.14.0"
@ -965,6 +1020,40 @@ cli = ["click (==8.*)", "pygments (==2.*)", "rich (>=10,<14)"]
http2 = ["h2 (>=3,<5)"] http2 = ["h2 (>=3,<5)"]
socks = ["socksio (==1.*)"] socks = ["socksio (==1.*)"]
[[package]]
name = "huggingface-hub"
version = "0.25.1"
description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
optional = false
python-versions = ">=3.8.0"
files = [
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[package.dependencies]
filelock = "*"
fsspec = ">=2023.5.0"
packaging = ">=20.9"
pyyaml = ">=5.1"
requests = "*"
tqdm = ">=4.42.1"
typing-extensions = ">=3.7.4.3"
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all = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "fastapi", "gradio", "jedi", "minijinja (>=1.0)", "mypy (==1.5.1)", "numpy", "pytest (>=8.1.1,<8.2.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "ruff (>=0.5.0)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
cli = ["InquirerPy (==0.3.4)"]
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fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
hf-transfer = ["hf-transfer (>=0.1.4)"]
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quality = ["mypy (==1.5.1)", "ruff (>=0.5.0)"]
tensorflow = ["graphviz", "pydot", "tensorflow"]
tensorflow-testing = ["keras (<3.0)", "tensorflow"]
testing = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "fastapi", "gradio", "jedi", "minijinja (>=1.0)", "numpy", "pytest (>=8.1.1,<8.2.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "soundfile", "urllib3 (<2.0)"]
torch = ["safetensors[torch]", "torch"]
typing = ["types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)"]
[[package]] [[package]]
name = "hypercorn" name = "hypercorn"
version = "0.17.3" version = "0.17.3"
@ -1102,6 +1191,8 @@ dash-extensions = "^1.0.18"
karkas-core = {path = "../karkas_core", develop = true} karkas-core = {path = "../karkas_core", develop = true}
peewee = "^3.17.6" peewee = "^3.17.6"
pyyaml = "^6.0.1" pyyaml = "^6.0.1"
torch = "^2.0"
transformers = "^4.45.2"
[package.source] [package.source]
type = "directory" type = "directory"
@ -1297,6 +1388,23 @@ files = [
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[[package]]
name = "mpmath"
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python-versions = "*"
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docs = ["sphinx"]
gmpy = ["gmpy2 (>=2.1.0a4)"]
tests = ["pytest (>=4.6)"]
[[package]] [[package]]
name = "multidict" name = "multidict"
version = "6.0.5" version = "6.0.5"
@ -1418,6 +1526,86 @@ files = [
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] ]
[[package]]
name = "networkx"
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description = "Python package for creating and manipulating graphs and networks"
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test = ["pytest (>=7.2)", "pytest-cov (>=4.0)"]
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name = "numpy"
version = "2.1.2"
description = "Fundamental package for array computing in Python"
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]
[package.dependencies]
huggingface-hub = ">=0.16.4,<1.0"
[package.extras]
dev = ["tokenizers[testing]"]
docs = ["setuptools-rust", "sphinx", "sphinx-rtd-theme"]
testing = ["black (==22.3)", "datasets", "numpy", "pytest", "requests", "ruff"]
[[package]] [[package]]
name = "tomli" name = "tomli"
version = "2.0.1" version = "2.0.1"
@ -1972,6 +2529,131 @@ files = [
{file = "tomli-2.0.1.tar.gz", hash = "sha256:de526c12914f0c550d15924c62d72abc48d6fe7364aa87328337a31007fe8a4f"}, {file = "tomli-2.0.1.tar.gz", hash = "sha256:de526c12914f0c550d15924c62d72abc48d6fe7364aa87328337a31007fe8a4f"},
] ]
[[package]]
name = "torch"
version = "2.4.1+cpu"
description = "Tensors and Dynamic neural networks in Python with strong GPU acceleration"
optional = false
python-versions = ">=3.8.0"
files = [
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]
[package.dependencies]
filelock = "*"
fsspec = "*"
jinja2 = "*"
networkx = "*"
sympy = "*"
typing-extensions = ">=4.8.0"
[package.extras]
opt-einsum = ["opt-einsum (>=3.3)"]
optree = ["optree (>=0.11.0)"]
[package.source]
type = "legacy"
url = "https://download.pytorch.org/whl/cpu"
reference = "pytorch-cpu"
[[package]]
name = "tqdm"
version = "4.66.5"
description = "Fast, Extensible Progress Meter"
optional = false
python-versions = ">=3.7"
files = [
{file = "tqdm-4.66.5-py3-none-any.whl", hash = "sha256:90279a3770753eafc9194a0364852159802111925aa30eb3f9d85b0e805ac7cd"},
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]
[package.dependencies]
colorama = {version = "*", markers = "platform_system == \"Windows\""}
[package.extras]
dev = ["pytest (>=6)", "pytest-cov", "pytest-timeout", "pytest-xdist"]
notebook = ["ipywidgets (>=6)"]
slack = ["slack-sdk"]
telegram = ["requests"]
[[package]]
name = "transformers"
version = "4.45.2"
description = "State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow"
optional = false
python-versions = ">=3.8.0"
files = [
{file = "transformers-4.45.2-py3-none-any.whl", hash = "sha256:c551b33660cfc815bae1f9f097ecfd1e65be623f13c6ee0dda372bd881460210"},
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]
[package.dependencies]
filelock = "*"
huggingface-hub = ">=0.23.2,<1.0"
numpy = ">=1.17"
packaging = ">=20.0"
pyyaml = ">=5.1"
regex = "!=2019.12.17"
requests = "*"
safetensors = ">=0.4.1"
tokenizers = ">=0.20,<0.21"
tqdm = ">=4.27"
[package.extras]
accelerate = ["accelerate (>=0.26.0)"]
agents = ["Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.26.0)", "datasets (!=2.5.0)", "diffusers", "opencv-python", "sentencepiece (>=0.1.91,!=0.1.92)", "torch"]
all = ["Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.26.0)", "av (==9.2.0)", "codecarbon (==1.2.0)", "decord (==0.6.0)", "flax (>=0.4.1,<=0.7.0)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1,<0.14.0)", "librosa", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "phonemizer", "protobuf", "pyctcdecode (>=0.4.0)", "ray[tune] (>=2.7.0)", "scipy (<1.13.0)", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timm (<=0.9.16)", "tokenizers (>=0.20,<0.21)", "torch", "torchaudio", "torchvision"]
audio = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
benchmark = ["optimum-benchmark (>=0.3.0)"]
codecarbon = ["codecarbon (==1.2.0)"]
deepspeed = ["accelerate (>=0.26.0)", "deepspeed (>=0.9.3)"]
deepspeed-testing = ["GitPython (<3.1.19)", "accelerate (>=0.26.0)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "deepspeed (>=0.9.3)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "nltk (<=3.8.1)", "optuna", "parameterized", "protobuf", "psutil", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "timeout-decorator"]
dev = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.26.0)", "av (==9.2.0)", "beautifulsoup4", "codecarbon (==1.2.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "decord (==0.6.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "flax (>=0.4.1,<=0.7.0)", "fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1,<0.14.0)", "libcst", "librosa", "nltk (<=3.8.1)", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rich", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "scipy (<1.13.0)", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "tensorboard", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timeout-decorator", "timm (<=0.9.16)", "tokenizers (>=0.20,<0.21)", "torch", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"]
dev-tensorflow = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "isort (>=5.5.4)", "kenlm", "keras-nlp (>=0.3.1,<0.14.0)", "libcst", "librosa", "nltk (<=3.8.1)", "onnxconverter-common", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "rich", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timeout-decorator", "tokenizers (>=0.20,<0.21)", "urllib3 (<2.0.0)"]
dev-torch = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.26.0)", "beautifulsoup4", "codecarbon (==1.2.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "kenlm", "libcst", "librosa", "nltk (<=3.8.1)", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rich", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "tensorboard", "timeout-decorator", "timm (<=0.9.16)", "tokenizers (>=0.20,<0.21)", "torch", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"]
flax = ["flax (>=0.4.1,<=0.7.0)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "optax (>=0.0.8,<=0.1.4)", "scipy (<1.13.0)"]
flax-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
ftfy = ["ftfy"]
integrations = ["optuna", "ray[tune] (>=2.7.0)", "sigopt"]
ja = ["fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "rhoknp (>=1.1.0,<1.3.1)", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)"]
modelcreation = ["cookiecutter (==1.7.3)"]
natten = ["natten (>=0.14.6,<0.15.0)"]
onnx = ["onnxconverter-common", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "tf2onnx"]
onnxruntime = ["onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)"]
optuna = ["optuna"]
quality = ["GitPython (<3.1.19)", "datasets (!=2.5.0)", "isort (>=5.5.4)", "libcst", "rich", "ruff (==0.5.1)", "urllib3 (<2.0.0)"]
ray = ["ray[tune] (>=2.7.0)"]
retrieval = ["datasets (!=2.5.0)", "faiss-cpu"]
ruff = ["ruff (==0.5.1)"]
sagemaker = ["sagemaker (>=2.31.0)"]
sentencepiece = ["protobuf", "sentencepiece (>=0.1.91,!=0.1.92)"]
serving = ["fastapi", "pydantic", "starlette", "uvicorn"]
sigopt = ["sigopt"]
sklearn = ["scikit-learn"]
speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"]
testing = ["GitPython (<3.1.19)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "nltk (<=3.8.1)", "parameterized", "psutil", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "timeout-decorator"]
tf = ["keras-nlp (>=0.3.1,<0.14.0)", "onnxconverter-common", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx"]
tf-cpu = ["keras (>2.9,<2.16)", "keras-nlp (>=0.3.1,<0.14.0)", "onnxconverter-common", "tensorflow-cpu (>2.9,<2.16)", "tensorflow-probability (<0.24)", "tensorflow-text (<2.16)", "tf2onnx"]
tf-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
tiktoken = ["blobfile", "tiktoken"]
timm = ["timm (<=0.9.16)"]
tokenizers = ["tokenizers (>=0.20,<0.21)"]
torch = ["accelerate (>=0.26.0)", "torch"]
torch-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"]
torch-vision = ["Pillow (>=10.0.1,<=15.0)", "torchvision"]
torchhub = ["filelock", "huggingface-hub (>=0.23.2,<1.0)", "importlib-metadata", "numpy (>=1.17)", "packaging (>=20.0)", "protobuf", "regex (!=2019.12.17)", "requests", "sentencepiece (>=0.1.91,!=0.1.92)", "tokenizers (>=0.20,<0.21)", "torch", "tqdm (>=4.27)"]
video = ["av (==9.2.0)", "decord (==0.6.0)"]
vision = ["Pillow (>=10.0.1,<=15.0)"]
[[package]] [[package]]
name = "typer" name = "typer"
version = "0.12.4" version = "0.12.4"
@ -2434,4 +3116,4 @@ test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools",
[metadata] [metadata]
lock-version = "2.0" lock-version = "2.0"
python-versions = ">=3.10,<3.13" python-versions = ">=3.10,<3.13"
content-hash = "3b9ac09252888d4a9c90b7e5189783f155a8934a84a6f0ee440ca3eecbe28616" content-hash = "8a15338b9083a814a02c722029363e8e9d0865e91834d64ab602152e19a72890"

5
src/gnomik/pyproject.toml
View File

@ -14,3 +14,8 @@ karkas-piccolo = { path = "../karkas_piccolo", develop = true }
[build-system] [build-system]
requires = ["poetry-core"] requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api" build-backend = "poetry.core.masonry.api"
[[tool.poetry.source]]
name = "pytorch-cpu"
url = "https://download.pytorch.org/whl/cpu"
priority = "explicit"

2
src/karkas_blocks/karkas_blocks/standard/spam/__init__.py
View File

@ -1 +1 @@
from .main import module_init from .main import module_init, module_late_init

4
src/karkas_blocks/karkas_blocks/standard/spam/db/piccolo_app.py
View File

@ -2,14 +2,14 @@ import os
from karkas_piccolo.conf.apps import AppConfig from karkas_piccolo.conf.apps import AppConfig
from .tables import SpamLog from .tables import SpamLog, VerifiedUsers
CURRENT_DIRECTORY = os.path.dirname(os.path.abspath(__file__)) CURRENT_DIRECTORY = os.path.dirname(os.path.abspath(__file__))
APP_CONFIG = AppConfig( APP_CONFIG = AppConfig(
app_name="standard.spam", app_name="standard.spam",
migrations_folder_path=os.path.join(CURRENT_DIRECTORY, "piccolo_migrations"), migrations_folder_path=os.path.join(CURRENT_DIRECTORY, "piccolo_migrations"),
table_classes=[SpamLog], table_classes=[SpamLog, VerifiedUsers],
migration_dependencies=[], migration_dependencies=[],
commands=[], commands=[],
) )

64
src/karkas_blocks/karkas_blocks/standard/spam/db/piccolo_migrations/standardspam_2024_10_08t18_31_17_058814.py Normal file
View File

@ -0,0 +1,64 @@
from piccolo.apps.migrations.auto.migration_manager import MigrationManager
from piccolo.columns.column_types import Boolean, Text
from piccolo.columns.indexes import IndexMethod
ID = "2024-10-08T18:31:17:058814"
VERSION = "1.20.0"
DESCRIPTION = ""
async def forwards():
manager = MigrationManager(
migration_id=ID, app_name="standard.spam", description=DESCRIPTION
)
manager.add_table(
class_name="VerifiedUsers",
tablename="verified_users",
schema=None,
columns=None,
)
manager.add_column(
table_class_name="VerifiedUsers",
tablename="verified_users",
column_name="key",
db_column_name="key",
column_class_name="Text",
column_class=Text,
params={
"default": "",
"null": False,
"primary_key": True,
"unique": False,
"index": False,
"index_method": IndexMethod.btree,
"choices": None,
"db_column_name": None,
"secret": False,
},
schema=None,
)
manager.add_column(
table_class_name="VerifiedUsers",
tablename="verified_users",
column_name="verified",
db_column_name="verified",
column_class_name="Boolean",
column_class=Boolean,
params={
"default": False,
"null": False,
"primary_key": False,
"unique": False,
"index": False,
"index_method": IndexMethod.btree,
"choices": None,
"db_column_name": None,
"secret": False,
},
schema=None,
)
return manager

8
src/karkas_blocks/karkas_blocks/standard/spam/db/tables.py
View File

@ -1,4 +1,4 @@
from piccolo.columns import JSON, Date, Text from piccolo.columns import JSON, Boolean, Date, Text
from piccolo.table import Table from piccolo.table import Table
@ -6,3 +6,9 @@ class SpamLog(Table):
message_text = Text(null=True) message_text = Text(null=True)
attachments = JSON() attachments = JSON()
created_at = Date() created_at = Date()
class VerifiedUsers(Table):
# Key format: `{message_chat_id}-{message_id}`
key = Text(primary_key=True)
verified = Boolean()

3
src/karkas_blocks/karkas_blocks/standard/spam/info.json
View File

@ -7,7 +7,8 @@
"privileged": true, "privileged": true,
"dependencies": { "dependencies": {
"required": { "required": {
"standard.config": "^1.0.0" "standard.config": "^1.0.0",
"standard.database": "^1.0.0"
}, },
"optional": { "optional": {
"standard.command_helper": "^1.0.0", "standard.command_helper": "^1.0.0",

204
src/karkas_blocks/karkas_blocks/standard/spam/main.py
View File

@ -1,11 +1,22 @@
from typing import TYPE_CHECKING, Type from typing import TYPE_CHECKING, Any, Awaitable, Callable, Dict, Type
from aiogram import Bot, Router from aiogram import BaseMiddleware, Bot, Router
from aiogram.filters import Command from aiogram.filters import JOIN_TRANSITION, ChatMemberUpdatedFilter, Command
from karkas_core.modules_system.public_api import get_module, register_router from karkas_core.modules_system.public_api import (
get_module,
log,
register_outer_chat_member_middleware,
register_outer_message_middleware,
register_router,
)
from .db.tables import SpamLog if TYPE_CHECKING:
from karkas_blocks.standard.config import IConfig
from aiogram.types import ChatMemberUpdated, Message, TelegramObject
from karkas_blocks.standard.filters import SimpleAdminFilter as ISimpleAdminFilter
from .db.tables import SpamLog, VerifiedUsers
try: try:
register_command = get_module("standard.command_helper", "register_command") register_command = get_module("standard.command_helper", "register_command")
@ -14,23 +25,9 @@ except Exception:
COMMAND_HELPER_MODULE_LOADED = False COMMAND_HELPER_MODULE_LOADED = False
pass pass
if TYPE_CHECKING:
from aiogram.types import Message
from karkas_blocks.standard.filters import SimpleAdminFilter as ISimpleAdminFilter async def delete_spam(spam_message: "Message", bot: "Bot"):
chat_id = spam_message.chat.id
async def spam(message: "Message", bot: "Bot"):
if not message.reply_to_message:
return
if message.reply_to_message.from_user.id in (message.from_user.id, bot.id):
return
spam_message = message.reply_to_message
chat_id = message.chat.id
message.reply_to_message.media_group_id
attachments = { attachments = {
"version": 1, "version": 1,
@ -52,11 +49,6 @@ async def spam(message: "Message", bot: "Bot"):
message_id=spam_message.message_id, message_id=spam_message.message_id,
) )
await bot.delete_message(
chat_id=chat_id,
message_id=message.message_id,
)
await bot.ban_chat_member( await bot.ban_chat_member(
chat_id=chat_id, chat_id=chat_id,
user_id=spam_message.from_user.id, user_id=spam_message.from_user.id,
@ -65,18 +57,172 @@ async def spam(message: "Message", bot: "Bot"):
await SpamLog.insert(spam_log) await SpamLog.insert(spam_log)
async def delete_spam_by_request(message: "Message", bot: "Bot"):
if not message.reply_to_message:
return
if message.reply_to_message.from_user.id in (message.from_user.id, bot.id):
return
await delete_spam(message.reply_to_message)
await bot.delete_message(
chat_id=message.chat.id,
message_id=message.message_id,
)
config: "IConfig" = get_module("standard.config", "config")
try:
get_user_stats = get_module("standard.statistics", "get_user_stats")
import torch
import torch.nn.functional as F
from transformers import AutoModelForSequenceClassification, AutoTokenizer
USER_STATS_AVAILABLE = True
except Exception:
log("User stats not available, so Spam detection not will work")
USER_STATS_AVAILABLE = False
pass
tokenizer = None
model = None
def spam_detection_init():
if not USER_STATS_AVAILABLE:
return
# Загрузка модели и токенизатора
model_path = config.get("spam::spam_detection::model")
global tokenizer, model
tokenizer = AutoTokenizer.from_pretrained(model_path)
model = AutoModelForSequenceClassification.from_pretrained(model_path)
def spam_predict(text):
if not USER_STATS_AVAILABLE:
return
# Токенизация текста
inputs = tokenizer(text, return_tensors="pt", truncation=True, max_length=256)
# Отключаем градиенты для ускорения и экономии памяти
with torch.no_grad():
outputs = model(**inputs)
logits = outputs.logits
# Преобразование логитов в вероятности с помощью softmax
probabilities = F.softmax(logits, dim=1)
# Находим индекс класса с максимальной вероятностью
predicted_class = torch.argmax(probabilities, dim=1).item()
# Извлекаем вероятность предсказанного класса
confidence = probabilities[0, predicted_class].item()
# Возвращаем предсказанную метку и уверенность
return (predicted_class == 1, confidence)
class SpamDetectionMiddleware(BaseMiddleware):
async def __call__(
self,
handler: Callable[["TelegramObject", Dict[str, Any]], Awaitable[Any]],
event: "Message",
data: Dict[str, Any],
) -> Any:
if USER_STATS_AVAILABLE and event.text:
stats = await get_user_stats(event.chat.id, event.from_user.id)
verified_users_row = (
await VerifiedUsers.select(VerifiedUsers.verified)
.where(
VerifiedUsers.key == f"{event.chat.id}-{event.from_user.id}",
)
.first()
)
if verified_users_row:
if not verified_users_row["verified"]:
if event.text:
is_spam, confidence = spam_predict(event.text)
log(f"{event.text} is {is_spam} with confidence {confidence}")
if is_spam:
if confidence >= config.get(
"spam::spam_detection::confidence"
):
await delete_spam(event, event.bot)
return
if stats["messages_count"] > config.get(
"spam::spam_detection::check_messages_count"
):
await VerifiedUsers.update(
{VerifiedUsers.verified: True}
).where(
VerifiedUsers.key
== f"{event.chat.id}-{event.from_user.id}",
)
result = await handler(event, data)
return result
joinFilter = ChatMemberUpdatedFilter(JOIN_TRANSITION)
class ChatMemberMiddleware(BaseMiddleware):
async def __call__(
self,
handler: Callable[["TelegramObject", Dict[str, Any]], Awaitable[Any]],
event: "ChatMemberUpdated",
data: Dict[str, Any],
) -> Any:
if await joinFilter(event):
await VerifiedUsers.insert(
VerifiedUsers(
key=f"{event.chat.id}-{event.new_chat_member.user.id}",
verified=False,
)
)
result = await handler(event, data)
return result
def module_init(): def module_init():
config.register("spam::spam_detection::enabled", "boolean", default_value=True)
config.register(
"spam::spam_detection::check_messages_count", "int", default_value=5
)
config.register("spam::spam_detection::confidence", "float", default_value=0.9)
config.register(
"spam::spam_detection::model", "string", default_value="RUSpam/spam_deberta_v4"
)
register_outer_message_middleware(SpamDetectionMiddleware())
register_outer_chat_member_middleware(ChatMemberMiddleware())
register_app_config = get_module("standard.database", "register_app_config") register_app_config = get_module("standard.database", "register_app_config")
SimpleAdminFilter: "Type[ISimpleAdminFilter]" = get_module( SimpleAdminFilter: "Type[ISimpleAdminFilter]" = get_module(
"standard.filters", "SimpleAdminFilter" "standard.filters", "SimpleAdminFilter"
) )
from .db import APP_CONFIG from .db import APP_CONFIG
register_app_config(APP_CONFIG) register_app_config(APP_CONFIG)
router = Router() router = Router()
router.message.register(spam, SimpleAdminFilter(), Command("spam")) router.message.register(
delete_spam_by_request, SimpleAdminFilter(), Command("spam")
)
register_router(router) register_router(router)
@ -87,3 +233,7 @@ def module_init():
long_description="Удалить спам и забанить пользователя. " long_description="Удалить спам и забанить пользователя. "
"Собирает обезличенные данные для дальнейшего создания алгоритма", "Собирает обезличенные данные для дальнейшего создания алгоритма",
) )
def module_late_init():
spam_detection_init()

2
src/karkas_blocks/karkas_blocks/standard/statistics/__init__.py
View File

@ -5,7 +5,7 @@ from karkas_core.modules_system.public_api import (
register_outer_message_middleware, register_outer_message_middleware,
) )
from .main import StatisticsMiddleware from .main import StatisticsMiddleware, get_user_stats
if TYPE_CHECKING: if TYPE_CHECKING:
from karkas_blocks.standard.config import IConfig from karkas_blocks.standard.config import IConfig

146
src/karkas_blocks/karkas_blocks/standard/statistics/db/piccolo_migrations/standardstatistics_2024_08_20t16_28_38_371951.py → src/karkas_blocks/karkas_blocks/standard/statistics/db/piccolo_migrations/standardstatistics_2024_10_08t16_38_25_584922.py
View File

@ -1,9 +1,9 @@
from piccolo.apps.migrations.auto.migration_manager import MigrationManager from piccolo.apps.migrations.auto.migration_manager import MigrationManager
from piccolo.columns.column_types import Date, Integer, Text from piccolo.columns.column_types import Integer, Text, Timestamptz
from piccolo.columns.defaults.date import DateNow from piccolo.columns.defaults.timestamptz import TimestamptzNow
from piccolo.columns.indexes import IndexMethod from piccolo.columns.indexes import IndexMethod
ID = "2024-08-20T16:28:38:371951" ID = "2024-10-08T16:38:25:584922"
VERSION = "1.16.0" VERSION = "1.16.0"
DESCRIPTION = "" DESCRIPTION = ""
@ -13,18 +13,81 @@ async def forwards():
migration_id=ID, app_name="standard.statistics", description=DESCRIPTION migration_id=ID, app_name="standard.statistics", description=DESCRIPTION
) )
manager.add_table(
class_name="Messages", tablename="messages", schema=None, columns=None
)
manager.add_table( manager.add_table(
class_name="ChatStats", tablename="chat_stats", schema=None, columns=None class_name="ChatStats", tablename="chat_stats", schema=None, columns=None
) )
manager.add_table(
class_name="Messages", tablename="messages", schema=None, columns=None
)
manager.add_table( manager.add_table(
class_name="UserStats", tablename="user_stats", schema=None, columns=None class_name="UserStats", tablename="user_stats", schema=None, columns=None
) )
manager.add_column(
table_class_name="ChatStats",
tablename="chat_stats",
column_name="chat_id",
db_column_name="chat_id",
column_class_name="Integer",
column_class=Integer,
params={
"default": 0,
"null": False,
"primary_key": True,
"unique": False,
"index": False,
"index_method": IndexMethod.btree,
"choices": None,
"db_column_name": None,
"secret": False,
},
schema=None,
)
manager.add_column(
table_class_name="ChatStats",
tablename="chat_stats",
column_name="date",
db_column_name="date",
column_class_name="Timestamptz",
column_class=Timestamptz,
params={
"default": TimestamptzNow(),
"null": False,
"primary_key": False,
"unique": False,
"index": False,
"index_method": IndexMethod.btree,
"choices": None,
"db_column_name": None,
"secret": False,
},
schema=None,
)
manager.add_column(
table_class_name="ChatStats",
tablename="chat_stats",
column_name="messages_count",
db_column_name="messages_count",
column_class_name="Integer",
column_class=Integer,
params={
"default": 0,
"null": False,
"primary_key": False,
"unique": False,
"index": False,
"index_method": IndexMethod.btree,
"choices": None,
"db_column_name": None,
"secret": False,
},
schema=None,
)
manager.add_column( manager.add_column(
table_class_name="Messages", table_class_name="Messages",
tablename="messages", tablename="messages",
@ -151,69 +214,6 @@ async def forwards():
schema=None, schema=None,
) )
manager.add_column(
table_class_name="ChatStats",
tablename="chat_stats",
column_name="chat_id",
db_column_name="chat_id",
column_class_name="Integer",
column_class=Integer,
params={
"default": 0,
"null": False,
"primary_key": True,
"unique": False,
"index": False,
"index_method": IndexMethod.btree,
"choices": None,
"db_column_name": None,
"secret": False,
},
schema=None,
)
manager.add_column(
table_class_name="ChatStats",
tablename="chat_stats",
column_name="date",
db_column_name="date",
column_class_name="Date",
column_class=Date,
params={
"default": DateNow(),
"null": False,
"primary_key": False,
"unique": False,
"index": False,
"index_method": IndexMethod.btree,
"choices": None,
"db_column_name": None,
"secret": False,
},
schema=None,
)
manager.add_column(
table_class_name="ChatStats",
tablename="chat_stats",
column_name="messages_count",
db_column_name="messages_count",
column_class_name="Integer",
column_class=Integer,
params={
"default": 0,
"null": False,
"primary_key": False,
"unique": False,
"index": False,
"index_method": IndexMethod.btree,
"choices": None,
"db_column_name": None,
"secret": False,
},
schema=None,
)
manager.add_column( manager.add_column(
table_class_name="UserStats", table_class_name="UserStats",
tablename="user_stats", tablename="user_stats",
@ -282,10 +282,10 @@ async def forwards():
tablename="user_stats", tablename="user_stats",
column_name="date", column_name="date",
db_column_name="date", db_column_name="date",
column_class_name="Date", column_class_name="Timestamptz",
column_class=Date, column_class=Timestamptz,
params={ params={
"default": DateNow(), "default": TimestamptzNow(),
"null": False, "null": False,
"primary_key": False, "primary_key": False,
"unique": False, "unique": False,

6
src/karkas_blocks/karkas_blocks/standard/statistics/db/tables.py
View File

@ -1,10 +1,10 @@
from piccolo.columns import Date, Integer, Text from piccolo.columns import Integer, Text, Timestamptz
from piccolo.table import Table from piccolo.table import Table
class ChatStats(Table): class ChatStats(Table):
chat_id = Integer(primary_key=True) chat_id = Integer(primary_key=True)
date = Date() date = Timestamptz()
messages_count = Integer(default=0) messages_count = Integer(default=0)
@ -29,5 +29,5 @@ class UserStats(Table):
chat_id = Integer() chat_id = Integer()
user_id = Integer() user_id = Integer()
date = Date() date = Timestamptz()
messages_count = Integer(default=0) messages_count = Integer(default=0)

1769
src/karkas_blocks/poetry.lock generated
View File

File diff suppressed because it is too large Load Diff

8
src/karkas_blocks/pyproject.toml
View File

@ -17,9 +17,17 @@ dash = "^2.17.1"
dash-extensions = "^1.0.18" dash-extensions = "^1.0.18"
dash-bootstrap-components = "^1.6.0" dash-bootstrap-components = "^1.6.0"
torch = { version = "^2.0", source="pytorch-cpu" }
transformers = "^4.45.2"
[tool.poetry-monorepo.deps] [tool.poetry-monorepo.deps]
enabled = true enabled = true
[build-system] [build-system]
requires = ["poetry-core"] requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api" build-backend = "poetry.core.masonry.api"
[[tool.poetry.source]]
name = "pytorch-cpu"
url = "https://download.pytorch.org/whl/cpu"
priority = "explicit"

3
src/karkas_core/karkas_core/main.py
View File

@ -43,6 +43,9 @@ class Karkas:
for middleware in singleton.storage["_outer_message_middlewares"]: for middleware in singleton.storage["_outer_message_middlewares"]:
singleton.dp.message.outer_middleware.register(middleware) singleton.dp.message.outer_middleware.register(middleware)
for middleware in singleton.storage["_outer_chat_member_middlewares"]:
singleton.dp.chat_member.outer_middleware.register(middleware)
await singleton.modules_manager.late_init() await singleton.modules_manager.late_init()
except Exception: except Exception:

1
src/karkas_core/karkas_core/modules_system/public_api/__init__.py
View File

@ -5,6 +5,7 @@ from .public_api import (
get_fsm_context, get_fsm_context,
get_metainfo, get_metainfo,
get_module, get_module,
register_outer_chat_member_middleware,
register_outer_message_middleware, register_outer_message_middleware,
register_router, register_router,
set_chat_menu_button, set_chat_menu_button,

5
src/karkas_core/karkas_core/modules_system/public_api/public_api.py
View File

@ -28,6 +28,11 @@ def register_outer_message_middleware(middleware: "BaseMiddleware"):
app.storage["_outer_message_middlewares"].append(middleware) app.storage["_outer_message_middlewares"].append(middleware)
def register_outer_chat_member_middleware(middleware: "BaseMiddleware"):
app = Singleton()
app.storage["_outer_chat_member_middlewares"].append(middleware)
def get_metainfo(): def get_metainfo():
app = Singleton() app = Singleton()
return app.storage["metainfo"].copy() return app.storage["metainfo"].copy()

1
src/karkas_core/karkas_core/singleton.py
View File

@ -26,5 +26,6 @@ class Singleton(metaclass=SingletonMeta):
"_fsm_storage": MemoryStorage(), "_fsm_storage": MemoryStorage(),
"_routers": [], "_routers": [],
"_outer_message_middlewares": [], "_outer_message_middlewares": [],
"_outer_chat_member_middlewares": [],
"metainfo": {}, "metainfo": {},
} }

684
src/karkas_core/poetry.lock generated
View File

@ -609,6 +609,22 @@ typer = ">=0.12.3"
[package.extras] [package.extras]
standard = ["fastapi", "uvicorn[standard] (>=0.15.0)"] standard = ["fastapi", "uvicorn[standard] (>=0.15.0)"]
[[package]]
name = "filelock"
version = "3.16.1"
description = "A platform independent file lock."
optional = false
python-versions = ">=3.8"
files = [
{file = "filelock-3.16.1-py3-none-any.whl", hash = "sha256:2082e5703d51fbf98ea75855d9d5527e33d8ff23099bec374a134febee6946b0"},
{file = "filelock-3.16.1.tar.gz", hash = "sha256:c249fbfcd5db47e5e2d6d62198e565475ee65e4831e2561c8e313fa7eb961435"},
]
[package.extras]
docs = ["furo (>=2024.8.6)", "sphinx (>=8.0.2)", "sphinx-autodoc-typehints (>=2.4.1)"]
testing = ["covdefaults (>=2.3)", "coverage (>=7.6.1)", "diff-cover (>=9.2)", "pytest (>=8.3.3)", "pytest-asyncio (>=0.24)", "pytest-cov (>=5)", "pytest-mock (>=3.14)", "pytest-timeout (>=2.3.1)", "virtualenv (>=20.26.4)"]
typing = ["typing-extensions (>=4.12.2)"]
[[package]] [[package]]
name = "flask" name = "flask"
version = "3.0.3" version = "3.0.3"
@ -732,6 +748,45 @@ files = [
{file = "frozenlist-1.4.1.tar.gz", hash = "sha256:c037a86e8513059a2613aaba4d817bb90b9d9b6b69aace3ce9c877e8c8ed402b"}, {file = "frozenlist-1.4.1.tar.gz", hash = "sha256:c037a86e8513059a2613aaba4d817bb90b9d9b6b69aace3ce9c877e8c8ed402b"},
] ]
[[package]]
name = "fsspec"
version = "2024.9.0"
description = "File-system specification"
optional = false
python-versions = ">=3.8"
files = [
{file = "fsspec-2024.9.0-py3-none-any.whl", hash = "sha256:a0947d552d8a6efa72cc2c730b12c41d043509156966cca4fb157b0f2a0c574b"},
{file = "fsspec-2024.9.0.tar.gz", hash = "sha256:4b0afb90c2f21832df142f292649035d80b421f60a9e1c027802e5a0da2b04e8"},
]
[package.extras]
abfs = ["adlfs"]
adl = ["adlfs"]
arrow = ["pyarrow (>=1)"]
dask = ["dask", "distributed"]
dev = ["pre-commit", "ruff"]
doc = ["numpydoc", "sphinx", "sphinx-design", "sphinx-rtd-theme", "yarl"]
dropbox = ["dropbox", "dropboxdrivefs", "requests"]
full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "dask", "distributed", "dropbox", "dropboxdrivefs", "fusepy", "gcsfs", "libarchive-c", "ocifs", "panel", "paramiko", "pyarrow (>=1)", "pygit2", "requests", "s3fs", "smbprotocol", "tqdm"]
fuse = ["fusepy"]
gcs = ["gcsfs"]
git = ["pygit2"]
github = ["requests"]
gs = ["gcsfs"]
gui = ["panel"]
hdfs = ["pyarrow (>=1)"]
http = ["aiohttp (!=4.0.0a0,!=4.0.0a1)"]
libarchive = ["libarchive-c"]
oci = ["ocifs"]
s3 = ["s3fs"]
sftp = ["paramiko"]
smb = ["smbprotocol"]
ssh = ["paramiko"]
test = ["aiohttp (!=4.0.0a0,!=4.0.0a1)", "numpy", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "requests"]
test-downstream = ["aiobotocore (>=2.5.4,<3.0.0)", "dask-expr", "dask[dataframe,test]", "moto[server] (>4,<5)", "pytest-timeout", "xarray"]
test-full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "cloudpickle", "dask", "distributed", "dropbox", "dropboxdrivefs", "fastparquet", "fusepy", "gcsfs", "jinja2", "kerchunk", "libarchive-c", "lz4", "notebook", "numpy", "ocifs", "pandas", "panel", "paramiko", "pyarrow", "pyarrow (>=1)", "pyftpdlib", "pygit2", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "python-snappy", "requests", "smbprotocol", "tqdm", "urllib3", "zarr", "zstandard"]
tqdm = ["tqdm"]
[[package]] [[package]]
name = "h11" name = "h11"
version = "0.14.0" version = "0.14.0"
@ -862,6 +917,40 @@ cli = ["click (==8.*)", "pygments (==2.*)", "rich (>=10,<14)"]
http2 = ["h2 (>=3,<5)"] http2 = ["h2 (>=3,<5)"]
socks = ["socksio (==1.*)"] socks = ["socksio (==1.*)"]
[[package]]
name = "huggingface-hub"
version = "0.25.1"
description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
optional = false
python-versions = ">=3.8.0"
files = [
{file = "huggingface_hub-0.25.1-py3-none-any.whl", hash = "sha256:a5158ded931b3188f54ea9028097312cb0acd50bffaaa2612014c3c526b44972"},
{file = "huggingface_hub-0.25.1.tar.gz", hash = "sha256:9ff7cb327343211fbd06e2b149b8f362fd1e389454f3f14c6db75a4999ee20ff"},
]
[package.dependencies]
filelock = "*"
fsspec = ">=2023.5.0"
packaging = ">=20.9"
pyyaml = ">=5.1"
requests = "*"
tqdm = ">=4.42.1"
typing-extensions = ">=3.7.4.3"
[package.extras]
all = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "fastapi", "gradio", "jedi", "minijinja (>=1.0)", "mypy (==1.5.1)", "numpy", "pytest (>=8.1.1,<8.2.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "ruff (>=0.5.0)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
cli = ["InquirerPy (==0.3.4)"]
dev = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "fastapi", "gradio", "jedi", "minijinja (>=1.0)", "mypy (==1.5.1)", "numpy", "pytest (>=8.1.1,<8.2.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "ruff (>=0.5.0)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
hf-transfer = ["hf-transfer (>=0.1.4)"]
inference = ["aiohttp", "minijinja (>=1.0)"]
quality = ["mypy (==1.5.1)", "ruff (>=0.5.0)"]
tensorflow = ["graphviz", "pydot", "tensorflow"]
tensorflow-testing = ["keras (<3.0)", "tensorflow"]
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5
src/karkas_core/pyproject.toml
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@ -24,3 +24,8 @@ webhook = ["fastapi", "hypercorn"]
[build-system] [build-system]
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build-backend = "poetry.core.masonry.api" build-backend = "poetry.core.masonry.api"
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priority = "explicit"

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5
src/karkas_lite/pyproject.toml
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@ -13,6 +13,11 @@ karkas-core = { extras=["webhook"], path = "../karkas_core", develop = true }
karkas-blocks = { path = "../karkas_blocks", develop = true } karkas-blocks = { path = "../karkas_blocks", develop = true }
karkas-piccolo = { path = "../karkas_piccolo", develop = true } karkas-piccolo = { path = "../karkas_piccolo", develop = true }
[[tool.poetry.source]]
name = "pytorch-cpu"
url = "https://download.pytorch.org/whl/cpu"
priority = "explicit"
[build-system] [build-system]
requires = ["poetry-core"] requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api" build-backend = "poetry.core.masonry.api"

2
src/karkas_piccolo/poetry.lock generated
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@ -1128,4 +1128,4 @@ multidict = ">=4.0"
[metadata] [metadata]
lock-version = "2.0" lock-version = "2.0"
python-versions = ">=3.10,<3.13" python-versions = ">=3.10,<3.13"
content-hash = "09dcede77970a369ffb693aa2ae315754a89f17aa8c73487b16b18c962396b58" content-hash = "477a00af04692ed173b408edb826b827a41a2733e9920eb7571d42de5d06c1dc"

5
src/karkas_piccolo/pyproject.toml
View File

@ -17,3 +17,8 @@ karkas-core = { path = "../karkas_core", develop = true }
[build-system] [build-system]
requires = ["poetry-core"] requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api" build-backend = "poetry.core.masonry.api"
[[tool.poetry.source]]
name = "pytorch-cpu"
url = "https://download.pytorch.org/whl/cpu"
priority = "explicit"