mirror of
https://github.com/huggingface/text-generation-inference.git
synced 2025-09-09 11:24:53 +00:00
final
This commit is contained in:
OlivierDehaene
parent
b7c3c7dabb
commit
6e9e194f33
6
clients/python/Makefile
Normal file
6
clients/python/Makefile
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@ -0,0 +1,6 @@
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unit-tests:
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python -m pytest --cov=text_generation tests
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install:
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pip install pip --upgrade
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pip install -e .
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@ -1 +1,52 @@
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# Text Generation
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# Text Generation
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The Hugging Face Text Generation Python library provides a convenient way of interfacing with a
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`text-generation-inference` instance running on your own infrastructure or on the Hugging Face Hub.
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## Get Started
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### Install
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```shell
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pip install text-generation
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```
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### Usage
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```python
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from text_generation import InferenceAPIClient
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client = InferenceAPIClient("bigscience/bloomz")
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text = client.generate("Why is the sky blue?").generated_text
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print(text)
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# ' Rayleigh scattering'
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# Token Streaming
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text = ""
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for response in client.generate_stream("Why is the sky blue?"):
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if not response.token.special:
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text += response.token.text
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print(text)
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# ' Rayleigh scattering'
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```
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or with the asynchronous client:
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```python
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from text_generation import InferenceAPIAsyncClient
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client = InferenceAPIAsyncClient("bigscience/bloomz")
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response = await client.generate("Why is the sky blue?")
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print(response.generated_text)
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# ' Rayleigh scattering'
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# Token Streaming
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text = ""
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async for response in client.generate_stream("Why is the sky blue?"):
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if not response.token.special:
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text += response.token.text
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print(text)
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# ' Rayleigh scattering'
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```
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462
clients/python/poetry.lock
generated
462
clients/python/poetry.lock
generated
@ -9,10 +9,12 @@ python-versions = ">=3.6"
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||||
[package.dependencies]
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||||
aiosignal = ">=1.1.2"
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||||
async-timeout = ">=4.0.0a3,<5.0"
|
||||
asynctest = {version = "0.13.0", markers = "python_version < \"3.8\""}
|
||||
attrs = ">=17.3.0"
|
||||
charset-normalizer = ">=2.0,<4.0"
|
||||
frozenlist = ">=1.1.1"
|
||||
multidict = ">=4.5,<7.0"
|
||||
typing-extensions = {version = ">=3.7.4", markers = "python_version < \"3.8\""}
|
||||
yarl = ">=1.0,<2.0"
|
||||
|
||||
[package.extras]
|
||||
@ -37,6 +39,25 @@ category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.6"
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||||
|
||||
[package.dependencies]
|
||||
typing-extensions = {version = ">=3.6.5", markers = "python_version < \"3.8\""}
|
||||
|
||||
[[package]]
|
||||
name = "asynctest"
|
||||
version = "0.13.0"
|
||||
description = "Enhance the standard unittest package with features for testing asyncio libraries"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.5"
|
||||
|
||||
[[package]]
|
||||
name = "atomicwrites"
|
||||
version = "1.4.1"
|
||||
description = "Atomic file writes."
|
||||
category = "dev"
|
||||
optional = false
|
||||
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
|
||||
|
||||
[[package]]
|
||||
name = "attrs"
|
||||
version = "22.2.0"
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||||
@ -53,6 +74,14 @@ tests = ["attrs[tests-no-zope]", "zope.interface"]
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tests-no-zope = ["cloudpickle", "hypothesis", "mypy (>=0.971,<0.990)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
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||||
tests_no_zope = ["cloudpickle", "hypothesis", "mypy (>=0.971,<0.990)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
|
||||
|
||||
[[package]]
|
||||
name = "certifi"
|
||||
version = "2022.12.7"
|
||||
description = "Python package for providing Mozilla's CA Bundle."
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.6"
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||||
|
||||
[[package]]
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||||
name = "charset-normalizer"
|
||||
version = "3.1.0"
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||||
@ -61,6 +90,40 @@ category = "main"
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||||
optional = false
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||||
python-versions = ">=3.7.0"
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||||
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||||
[[package]]
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||||
name = "colorama"
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||||
version = "0.4.6"
|
||||
description = "Cross-platform colored terminal text."
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7"
|
||||
|
||||
[[package]]
|
||||
name = "coverage"
|
||||
version = "7.2.1"
|
||||
description = "Code coverage measurement for Python"
|
||||
category = "dev"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
|
||||
[package.dependencies]
|
||||
tomli = {version = "*", optional = true, markers = "python_full_version <= \"3.11.0a6\" and extra == \"toml\""}
|
||||
|
||||
[package.extras]
|
||||
toml = ["tomli"]
|
||||
|
||||
[[package]]
|
||||
name = "filelock"
|
||||
version = "3.9.0"
|
||||
description = "A platform independent file lock."
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
|
||||
[package.extras]
|
||||
docs = ["furo (>=2022.12.7)", "sphinx (>=5.3)", "sphinx-autodoc-typehints (>=1.19.5)"]
|
||||
testing = ["covdefaults (>=2.2.2)", "coverage (>=7.0.1)", "pytest (>=7.2)", "pytest-cov (>=4)", "pytest-timeout (>=2.1)"]
|
||||
|
||||
[[package]]
|
||||
name = "frozenlist"
|
||||
version = "1.3.3"
|
||||
@ -69,6 +132,34 @@ category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
|
||||
[[package]]
|
||||
name = "huggingface-hub"
|
||||
version = "0.12.1"
|
||||
description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.7.0"
|
||||
|
||||
[package.dependencies]
|
||||
filelock = "*"
|
||||
importlib-metadata = {version = "*", markers = "python_version < \"3.8\""}
|
||||
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", "black (==22.3)", "flake8 (>=3.8.3)", "flake8-bugbear", "isort (>=5.5.4)", "jedi", "mypy (==0.982)", "pytest", "pytest-cov", "pytest-env", "pytest-xdist", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3"]
|
||||
cli = ["InquirerPy (==0.3.4)"]
|
||||
dev = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "black (==22.3)", "flake8 (>=3.8.3)", "flake8-bugbear", "isort (>=5.5.4)", "jedi", "mypy (==0.982)", "pytest", "pytest-cov", "pytest-env", "pytest-xdist", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3"]
|
||||
fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
|
||||
quality = ["black (==22.3)", "flake8 (>=3.8.3)", "flake8-bugbear", "isort (>=5.5.4)", "mypy (==0.982)"]
|
||||
tensorflow = ["graphviz", "pydot", "tensorflow"]
|
||||
testing = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "isort (>=5.5.4)", "jedi", "pytest", "pytest-cov", "pytest-env", "pytest-xdist", "soundfile"]
|
||||
torch = ["torch"]
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||||
typing = ["types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3"]
|
||||
|
||||
[[package]]
|
||||
name = "idna"
|
||||
version = "3.4"
|
||||
@ -77,6 +168,31 @@ category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.5"
|
||||
|
||||
[[package]]
|
||||
name = "importlib-metadata"
|
||||
version = "6.0.0"
|
||||
description = "Read metadata from Python packages"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
|
||||
[package.dependencies]
|
||||
typing-extensions = {version = ">=3.6.4", markers = "python_version < \"3.8\""}
|
||||
zipp = ">=0.5"
|
||||
|
||||
[package.extras]
|
||||
docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
|
||||
perf = ["ipython"]
|
||||
testing = ["flake8 (<5)", "flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)", "pytest-perf (>=0.9.2)"]
|
||||
|
||||
[[package]]
|
||||
name = "iniconfig"
|
||||
version = "2.0.0"
|
||||
description = "brain-dead simple config-ini parsing"
|
||||
category = "dev"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
|
||||
[[package]]
|
||||
name = "multidict"
|
||||
version = "6.0.4"
|
||||
@ -85,6 +201,37 @@ category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
|
||||
[[package]]
|
||||
name = "packaging"
|
||||
version = "23.0"
|
||||
description = "Core utilities for Python packages"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
|
||||
[[package]]
|
||||
name = "pluggy"
|
||||
version = "1.0.0"
|
||||
description = "plugin and hook calling mechanisms for python"
|
||||
category = "dev"
|
||||
optional = false
|
||||
python-versions = ">=3.6"
|
||||
|
||||
[package.dependencies]
|
||||
importlib-metadata = {version = ">=0.12", markers = "python_version < \"3.8\""}
|
||||
|
||||
[package.extras]
|
||||
dev = ["pre-commit", "tox"]
|
||||
testing = ["pytest", "pytest-benchmark"]
|
||||
|
||||
[[package]]
|
||||
name = "py"
|
||||
version = "1.11.0"
|
||||
description = "library with cross-python path, ini-parsing, io, code, log facilities"
|
||||
category = "dev"
|
||||
optional = false
|
||||
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
|
||||
|
||||
[[package]]
|
||||
name = "pydantic"
|
||||
version = "1.10.5"
|
||||
@ -100,6 +247,117 @@ typing-extensions = ">=4.2.0"
|
||||
dotenv = ["python-dotenv (>=0.10.4)"]
|
||||
email = ["email-validator (>=1.0.3)"]
|
||||
|
||||
[[package]]
|
||||
name = "pytest"
|
||||
version = "6.2.5"
|
||||
description = "pytest: simple powerful testing with Python"
|
||||
category = "dev"
|
||||
optional = false
|
||||
python-versions = ">=3.6"
|
||||
|
||||
[package.dependencies]
|
||||
atomicwrites = {version = ">=1.0", markers = "sys_platform == \"win32\""}
|
||||
attrs = ">=19.2.0"
|
||||
colorama = {version = "*", markers = "sys_platform == \"win32\""}
|
||||
importlib-metadata = {version = ">=0.12", markers = "python_version < \"3.8\""}
|
||||
iniconfig = "*"
|
||||
packaging = "*"
|
||||
pluggy = ">=0.12,<2.0"
|
||||
py = ">=1.8.2"
|
||||
toml = "*"
|
||||
|
||||
[package.extras]
|
||||
testing = ["argcomplete", "hypothesis (>=3.56)", "mock", "nose", "requests", "xmlschema"]
|
||||
|
||||
[[package]]
|
||||
name = "pytest-asyncio"
|
||||
version = "0.17.2"
|
||||
description = "Pytest support for asyncio"
|
||||
category = "dev"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
|
||||
[package.dependencies]
|
||||
pytest = ">=6.1.0"
|
||||
typing-extensions = {version = ">=4.0", markers = "python_version < \"3.8\""}
|
||||
|
||||
[package.extras]
|
||||
testing = ["coverage (==6.2)", "flaky (>=3.5.0)", "hypothesis (>=5.7.1)", "mypy (==0.931)"]
|
||||
|
||||
[[package]]
|
||||
name = "pytest-cov"
|
||||
version = "3.0.0"
|
||||
description = "Pytest plugin for measuring coverage."
|
||||
category = "dev"
|
||||
optional = false
|
||||
python-versions = ">=3.6"
|
||||
|
||||
[package.dependencies]
|
||||
coverage = {version = ">=5.2.1", extras = ["toml"]}
|
||||
pytest = ">=4.6"
|
||||
|
||||
[package.extras]
|
||||
testing = ["fields", "hunter", "process-tests", "pytest-xdist", "six", "virtualenv"]
|
||||
|
||||
[[package]]
|
||||
name = "PyYAML"
|
||||
version = "6.0"
|
||||
description = "YAML parser and emitter for Python"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.6"
|
||||
|
||||
[[package]]
|
||||
name = "requests"
|
||||
version = "2.28.2"
|
||||
description = "Python HTTP for Humans."
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.7, <4"
|
||||
|
||||
[package.dependencies]
|
||||
certifi = ">=2017.4.17"
|
||||
charset-normalizer = ">=2,<4"
|
||||
idna = ">=2.5,<4"
|
||||
urllib3 = ">=1.21.1,<1.27"
|
||||
|
||||
[package.extras]
|
||||
socks = ["PySocks (>=1.5.6,!=1.5.7)"]
|
||||
use_chardet_on_py3 = ["chardet (>=3.0.2,<6)"]
|
||||
|
||||
[[package]]
|
||||
name = "toml"
|
||||
version = "0.10.2"
|
||||
description = "Python Library for Tom's Obvious, Minimal Language"
|
||||
category = "dev"
|
||||
optional = false
|
||||
python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*"
|
||||
|
||||
[[package]]
|
||||
name = "tomli"
|
||||
version = "2.0.1"
|
||||
description = "A lil' TOML parser"
|
||||
category = "dev"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
|
||||
[[package]]
|
||||
name = "tqdm"
|
||||
version = "4.65.0"
|
||||
description = "Fast, Extensible Progress Meter"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
|
||||
[package.dependencies]
|
||||
colorama = {version = "*", markers = "platform_system == \"Windows\""}
|
||||
|
||||
[package.extras]
|
||||
dev = ["py-make (>=0.1.0)", "twine", "wheel"]
|
||||
notebook = ["ipywidgets (>=6)"]
|
||||
slack = ["slack-sdk"]
|
||||
telegram = ["requests"]
|
||||
|
||||
[[package]]
|
||||
name = "typing-extensions"
|
||||
version = "4.5.0"
|
||||
@ -108,6 +366,19 @@ category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
|
||||
[[package]]
|
||||
name = "urllib3"
|
||||
version = "1.26.14"
|
||||
description = "HTTP library with thread-safe connection pooling, file post, and more."
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"
|
||||
|
||||
[package.extras]
|
||||
brotli = ["brotli (>=1.0.9)", "brotlicffi (>=0.8.0)", "brotlipy (>=0.6.0)"]
|
||||
secure = ["certifi", "cryptography (>=1.3.4)", "idna (>=2.0.0)", "ipaddress", "pyOpenSSL (>=0.14)", "urllib3-secure-extra"]
|
||||
socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"]
|
||||
|
||||
[[package]]
|
||||
name = "yarl"
|
||||
version = "1.8.2"
|
||||
@ -119,11 +390,24 @@ python-versions = ">=3.7"
|
||||
[package.dependencies]
|
||||
idna = ">=2.0"
|
||||
multidict = ">=4.0"
|
||||
typing-extensions = {version = ">=3.7.4", markers = "python_version < \"3.8\""}
|
||||
|
||||
[[package]]
|
||||
name = "zipp"
|
||||
version = "3.15.0"
|
||||
description = "Backport of pathlib-compatible object wrapper for zip files"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
|
||||
[package.extras]
|
||||
docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
|
||||
testing = ["big-O", "flake8 (<5)", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)"]
|
||||
|
||||
[metadata]
|
||||
lock-version = "1.1"
|
||||
python-versions = "^3.9"
|
||||
content-hash = "b1b9949a4e7006b90d2bf0189f00b0ac4ad70e3056ac98a4cc4e3949ad16f084"
|
||||
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|
||||
{file = "pluggy-1.0.0.tar.gz", hash = "sha256:4224373bacce55f955a878bf9cfa763c1e360858e330072059e10bad68531159"},
|
||||
]
|
||||
py = [
|
||||
{file = "py-1.11.0-py2.py3-none-any.whl", hash = "sha256:607c53218732647dff4acdfcd50cb62615cedf612e72d1724fb1a0cc6405b378"},
|
||||
{file = "py-1.11.0.tar.gz", hash = "sha256:51c75c4126074b472f746a24399ad32f6053d1b34b68d2fa41e558e6f4a98719"},
|
||||
]
|
||||
pydantic = [
|
||||
{file = "pydantic-1.10.5-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:5920824fe1e21cbb3e38cf0f3dd24857c8959801d1031ce1fac1d50857a03bfb"},
|
||||
{file = "pydantic-1.10.5-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:3bb99cf9655b377db1a9e47fa4479e3330ea96f4123c6c8200e482704bf1eda2"},
|
||||
@ -498,10 +878,84 @@ pydantic = [
|
||||
{file = "pydantic-1.10.5-py3-none-any.whl", hash = "sha256:7c5b94d598c90f2f46b3a983ffb46ab806a67099d118ae0da7ef21a2a4033b28"},
|
||||
{file = "pydantic-1.10.5.tar.gz", hash = "sha256:9e337ac83686645a46db0e825acceea8e02fca4062483f40e9ae178e8bd1103a"},
|
||||
]
|
||||
pytest = [
|
||||
{file = "pytest-6.2.5-py3-none-any.whl", hash = "sha256:7310f8d27bc79ced999e760ca304d69f6ba6c6649c0b60fb0e04a4a77cacc134"},
|
||||
{file = "pytest-6.2.5.tar.gz", hash = "sha256:131b36680866a76e6781d13f101efb86cf674ebb9762eb70d3082b6f29889e89"},
|
||||
]
|
||||
pytest-asyncio = [
|
||||
{file = "pytest-asyncio-0.17.2.tar.gz", hash = "sha256:6d895b02432c028e6957d25fc936494e78c6305736e785d9fee408b1efbc7ff4"},
|
||||
{file = "pytest_asyncio-0.17.2-py3-none-any.whl", hash = "sha256:e0fe5dbea40516b661ef1bcfe0bd9461c2847c4ef4bb40012324f2454fb7d56d"},
|
||||
]
|
||||
pytest-cov = [
|
||||
{file = "pytest-cov-3.0.0.tar.gz", hash = "sha256:e7f0f5b1617d2210a2cabc266dfe2f4c75a8d32fb89eafb7ad9d06f6d076d470"},
|
||||
{file = "pytest_cov-3.0.0-py3-none-any.whl", hash = "sha256:578d5d15ac4a25e5f961c938b85a05b09fdaae9deef3bb6de9a6e766622ca7a6"},
|
||||
]
|
||||
PyYAML = [
|
||||
{file = "PyYAML-6.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:d4db7c7aef085872ef65a8fd7d6d09a14ae91f691dec3e87ee5ee0539d516f53"},
|
||||
{file = "PyYAML-6.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:9df7ed3b3d2e0ecfe09e14741b857df43adb5a3ddadc919a2d94fbdf78fea53c"},
|
||||
{file = "PyYAML-6.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:77f396e6ef4c73fdc33a9157446466f1cff553d979bd00ecb64385760c6babdc"},
|
||||
{file = "PyYAML-6.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a80a78046a72361de73f8f395f1f1e49f956c6be882eed58505a15f3e430962b"},
|
||||
{file = "PyYAML-6.0-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:f84fbc98b019fef2ee9a1cb3ce93e3187a6df0b2538a651bfb890254ba9f90b5"},
|
||||
{file = "PyYAML-6.0-cp310-cp310-win32.whl", hash = "sha256:2cd5df3de48857ed0544b34e2d40e9fac445930039f3cfe4bcc592a1f836d513"},
|
||||
{file = "PyYAML-6.0-cp310-cp310-win_amd64.whl", hash = "sha256:daf496c58a8c52083df09b80c860005194014c3698698d1a57cbcfa182142a3a"},
|
||||
{file = "PyYAML-6.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:d4b0ba9512519522b118090257be113b9468d804b19d63c71dbcf4a48fa32358"},
|
||||
{file = "PyYAML-6.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:81957921f441d50af23654aa6c5e5eaf9b06aba7f0a19c18a538dc7ef291c5a1"},
|
||||
{file = "PyYAML-6.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:afa17f5bc4d1b10afd4466fd3a44dc0e245382deca5b3c353d8b757f9e3ecb8d"},
|
||||
{file = "PyYAML-6.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:dbad0e9d368bb989f4515da330b88a057617d16b6a8245084f1b05400f24609f"},
|
||||
{file = "PyYAML-6.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:432557aa2c09802be39460360ddffd48156e30721f5e8d917f01d31694216782"},
|
||||
{file = "PyYAML-6.0-cp311-cp311-win32.whl", hash = "sha256:bfaef573a63ba8923503d27530362590ff4f576c626d86a9fed95822a8255fd7"},
|
||||
{file = "PyYAML-6.0-cp311-cp311-win_amd64.whl", hash = "sha256:01b45c0191e6d66c470b6cf1b9531a771a83c1c4208272ead47a3ae4f2f603bf"},
|
||||
{file = "PyYAML-6.0-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:897b80890765f037df3403d22bab41627ca8811ae55e9a722fd0392850ec4d86"},
|
||||
{file = "PyYAML-6.0-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:50602afada6d6cbfad699b0c7bb50d5ccffa7e46a3d738092afddc1f9758427f"},
|
||||
{file = "PyYAML-6.0-cp36-cp36m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:48c346915c114f5fdb3ead70312bd042a953a8ce5c7106d5bfb1a5254e47da92"},
|
||||
{file = "PyYAML-6.0-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:98c4d36e99714e55cfbaaee6dd5badbc9a1ec339ebfc3b1f52e293aee6bb71a4"},
|
||||
{file = "PyYAML-6.0-cp36-cp36m-win32.whl", hash = "sha256:0283c35a6a9fbf047493e3a0ce8d79ef5030852c51e9d911a27badfde0605293"},
|
||||
{file = "PyYAML-6.0-cp36-cp36m-win_amd64.whl", hash = "sha256:07751360502caac1c067a8132d150cf3d61339af5691fe9e87803040dbc5db57"},
|
||||
{file = "PyYAML-6.0-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:819b3830a1543db06c4d4b865e70ded25be52a2e0631ccd2f6a47a2822f2fd7c"},
|
||||
{file = "PyYAML-6.0-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:473f9edb243cb1935ab5a084eb238d842fb8f404ed2193a915d1784b5a6b5fc0"},
|
||||
{file = "PyYAML-6.0-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:0ce82d761c532fe4ec3f87fc45688bdd3a4c1dc5e0b4a19814b9009a29baefd4"},
|
||||
{file = "PyYAML-6.0-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:231710d57adfd809ef5d34183b8ed1eeae3f76459c18fb4a0b373ad56bedcdd9"},
|
||||
{file = "PyYAML-6.0-cp37-cp37m-win32.whl", hash = "sha256:c5687b8d43cf58545ade1fe3e055f70eac7a5a1a0bf42824308d868289a95737"},
|
||||
{file = "PyYAML-6.0-cp37-cp37m-win_amd64.whl", hash = "sha256:d15a181d1ecd0d4270dc32edb46f7cb7733c7c508857278d3d378d14d606db2d"},
|
||||
{file = "PyYAML-6.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:0b4624f379dab24d3725ffde76559cff63d9ec94e1736b556dacdfebe5ab6d4b"},
|
||||
{file = "PyYAML-6.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:213c60cd50106436cc818accf5baa1aba61c0189ff610f64f4a3e8c6726218ba"},
|
||||
{file = "PyYAML-6.0-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:9fa600030013c4de8165339db93d182b9431076eb98eb40ee068700c9c813e34"},
|
||||
{file = "PyYAML-6.0-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:277a0ef2981ca40581a47093e9e2d13b3f1fbbeffae064c1d21bfceba2030287"},
|
||||
{file = "PyYAML-6.0-cp38-cp38-win32.whl", hash = "sha256:d4eccecf9adf6fbcc6861a38015c2a64f38b9d94838ac1810a9023a0609e1b78"},
|
||||
{file = "PyYAML-6.0-cp38-cp38-win_amd64.whl", hash = "sha256:1e4747bc279b4f613a09eb64bba2ba602d8a6664c6ce6396a4d0cd413a50ce07"},
|
||||
{file = "PyYAML-6.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:055d937d65826939cb044fc8c9b08889e8c743fdc6a32b33e2390f66013e449b"},
|
||||
{file = "PyYAML-6.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:e61ceaab6f49fb8bdfaa0f92c4b57bcfbea54c09277b1b4f7ac376bfb7a7c174"},
|
||||
{file = "PyYAML-6.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d67d839ede4ed1b28a4e8909735fc992a923cdb84e618544973d7dfc71540803"},
|
||||
{file = "PyYAML-6.0-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:cba8c411ef271aa037d7357a2bc8f9ee8b58b9965831d9e51baf703280dc73d3"},
|
||||
{file = "PyYAML-6.0-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:40527857252b61eacd1d9af500c3337ba8deb8fc298940291486c465c8b46ec0"},
|
||||
{file = "PyYAML-6.0-cp39-cp39-win32.whl", hash = "sha256:b5b9eccad747aabaaffbc6064800670f0c297e52c12754eb1d976c57e4f74dcb"},
|
||||
{file = "PyYAML-6.0-cp39-cp39-win_amd64.whl", hash = "sha256:b3d267842bf12586ba6c734f89d1f5b871df0273157918b0ccefa29deb05c21c"},
|
||||
{file = "PyYAML-6.0.tar.gz", hash = "sha256:68fb519c14306fec9720a2a5b45bc9f0c8d1b9c72adf45c37baedfcd949c35a2"},
|
||||
]
|
||||
requests = [
|
||||
{file = "requests-2.28.2-py3-none-any.whl", hash = "sha256:64299f4909223da747622c030b781c0d7811e359c37124b4bd368fb8c6518baa"},
|
||||
{file = "requests-2.28.2.tar.gz", hash = "sha256:98b1b2782e3c6c4904938b84c0eb932721069dfdb9134313beff7c83c2df24bf"},
|
||||
]
|
||||
toml = [
|
||||
{file = "toml-0.10.2-py2.py3-none-any.whl", hash = "sha256:806143ae5bfb6a3c6e736a764057db0e6a0e05e338b5630894a5f779cabb4f9b"},
|
||||
{file = "toml-0.10.2.tar.gz", hash = "sha256:b3bda1d108d5dd99f4a20d24d9c348e91c4db7ab1b749200bded2f839ccbe68f"},
|
||||
]
|
||||
tomli = [
|
||||
{file = "tomli-2.0.1-py3-none-any.whl", hash = "sha256:939de3e7a6161af0c887ef91b7d41a53e7c5a1ca976325f429cb46ea9bc30ecc"},
|
||||
{file = "tomli-2.0.1.tar.gz", hash = "sha256:de526c12914f0c550d15924c62d72abc48d6fe7364aa87328337a31007fe8a4f"},
|
||||
]
|
||||
tqdm = [
|
||||
{file = "tqdm-4.65.0-py3-none-any.whl", hash = "sha256:c4f53a17fe37e132815abceec022631be8ffe1b9381c2e6e30aa70edc99e9671"},
|
||||
{file = "tqdm-4.65.0.tar.gz", hash = "sha256:1871fb68a86b8fb3b59ca4cdd3dcccbc7e6d613eeed31f4c332531977b89beb5"},
|
||||
]
|
||||
typing-extensions = [
|
||||
{file = "typing_extensions-4.5.0-py3-none-any.whl", hash = "sha256:fb33085c39dd998ac16d1431ebc293a8b3eedd00fd4a32de0ff79002c19511b4"},
|
||||
{file = "typing_extensions-4.5.0.tar.gz", hash = "sha256:5cb5f4a79139d699607b3ef622a1dedafa84e115ab0024e0d9c044a9479ca7cb"},
|
||||
]
|
||||
urllib3 = [
|
||||
{file = "urllib3-1.26.14-py2.py3-none-any.whl", hash = "sha256:75edcdc2f7d85b137124a6c3c9fc3933cdeaa12ecb9a6a959f22797a0feca7e1"},
|
||||
{file = "urllib3-1.26.14.tar.gz", hash = "sha256:076907bf8fd355cde77728471316625a4d2f7e713c125f51953bb5b3eecf4f72"},
|
||||
]
|
||||
yarl = [
|
||||
{file = "yarl-1.8.2-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:bb81f753c815f6b8e2ddd2eef3c855cf7da193b82396ac013c661aaa6cc6b0a5"},
|
||||
{file = "yarl-1.8.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:47d49ac96156f0928f002e2424299b2c91d9db73e08c4cd6742923a086f1c863"},
|
||||
@ -578,3 +1032,7 @@ yarl = [
|
||||
{file = "yarl-1.8.2-cp39-cp39-win_amd64.whl", hash = "sha256:6604711362f2dbf7160df21c416f81fac0de6dbcf0b5445a2ef25478ecc4c778"},
|
||||
{file = "yarl-1.8.2.tar.gz", hash = "sha256:49d43402c6e3013ad0978602bf6bf5328535c48d192304b91b97a3c6790b1562"},
|
||||
]
|
||||
zipp = [
|
||||
{file = "zipp-3.15.0-py3-none-any.whl", hash = "sha256:48904fc76a60e542af151aded95726c1a5c34ed43ab4134b597665c86d7ad556"},
|
||||
{file = "zipp-3.15.0.tar.gz", hash = "sha256:112929ad649da941c23de50f356a2b5570c954b65150642bccdd66bf194d224b"},
|
||||
]
|
||||
|
||||
@ -1,14 +1,25 @@
|
||||
[tool.poetry]
|
||||
name = "text-generation"
|
||||
version = "0.3.2"
|
||||
description = "Text Generation Inference Python Client"
|
||||
description = "Hugging Face Text Generation Python Client"
|
||||
license = "Apache-2.0"
|
||||
authors = ["Olivier Dehaene <olivier@huggingface.co>"]
|
||||
maintainers = ["Olivier Dehaene <olivier@huggingface.co>"]
|
||||
readme = "README.md"
|
||||
homepage = "https://github.com/huggingface/text-generation-inference"
|
||||
repository = "https://github.com/huggingface/text-generation-inference"
|
||||
|
||||
|
||||
[tool.poetry.dependencies]
|
||||
python = "^3.9"
|
||||
python = "^3.7"
|
||||
pydantic = "^1.10.5"
|
||||
aiohttp = "^3.8.4"
|
||||
huggingface-hub = "^0.12.1"
|
||||
|
||||
[tool.poetry.dev-dependencies]
|
||||
pytest = "^6.2.5"
|
||||
pytest-asyncio = "^0.17.2"
|
||||
pytest-cov = "^3.0.0"
|
||||
|
||||
[build-system]
|
||||
requires = ["poetry-core"]
|
||||
|
||||
46
clients/python/tests/conftest.py
Normal file
46
clients/python/tests/conftest.py
Normal file
@ -0,0 +1,46 @@
|
||||
import pytest
|
||||
|
||||
from text_generation import __version__
|
||||
from huggingface_hub.utils import build_hf_headers
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def bloom_model():
|
||||
return "bigscience/bloom"
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def fake_model():
|
||||
return "fake/model"
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def unsupported_model():
|
||||
return "gpt2"
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def base_url():
|
||||
return "https://api-inference.huggingface.co/models"
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def bloom_url(base_url, bloom_model):
|
||||
return f"{base_url}/{bloom_model}"
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def fake_url(base_url, fake_model):
|
||||
return f"{base_url}/{fake_model}"
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def unsupported_url(base_url, unsupported_model):
|
||||
return f"{base_url}/{unsupported_model}"
|
||||
|
||||
|
||||
@pytest.fixture(scope="session")
|
||||
def hf_headers():
|
||||
return build_hf_headers(
|
||||
library_name="text-generation-tests", library_version=__version__
|
||||
)
|
||||
34
clients/python/tests/test_api_inference.py
Normal file
34
clients/python/tests/test_api_inference.py
Normal file
@ -0,0 +1,34 @@
|
||||
import pytest
|
||||
|
||||
from text_generation import (
|
||||
InferenceAPIClient,
|
||||
InferenceAPIAsyncClient,
|
||||
Client,
|
||||
AsyncClient,
|
||||
)
|
||||
from text_generation.errors import NotSupportedError
|
||||
from text_generation.api_inference import get_supported_models
|
||||
|
||||
|
||||
def test_get_supported_models():
|
||||
assert isinstance(get_supported_models(), list)
|
||||
|
||||
|
||||
def test_client(bloom_model):
|
||||
client = InferenceAPIClient(bloom_model)
|
||||
assert isinstance(client, Client)
|
||||
|
||||
|
||||
def test_client_unsupported_model(unsupported_model):
|
||||
with pytest.raises(NotSupportedError):
|
||||
InferenceAPIClient(unsupported_model)
|
||||
|
||||
|
||||
def test_async_client(bloom_model):
|
||||
client = InferenceAPIAsyncClient(bloom_model)
|
||||
assert isinstance(client, AsyncClient)
|
||||
|
||||
|
||||
def test_async_client_unsupported_model(unsupported_model):
|
||||
with pytest.raises(NotSupportedError):
|
||||
InferenceAPIAsyncClient(unsupported_model)
|
||||
127
clients/python/tests/test_client.py
Normal file
127
clients/python/tests/test_client.py
Normal file
@ -0,0 +1,127 @@
|
||||
import pytest
|
||||
|
||||
from text_generation import Client, AsyncClient
|
||||
from text_generation.errors import NotFoundError, ValidationError
|
||||
from text_generation.types import FinishReason, PrefillToken, Token
|
||||
|
||||
|
||||
def test_generate(bloom_url, hf_headers):
|
||||
client = Client(bloom_url, hf_headers)
|
||||
response = client.generate("test", max_new_tokens=1)
|
||||
|
||||
assert response.generated_text == "."
|
||||
assert response.details.finish_reason == FinishReason.Length
|
||||
assert response.details.generated_tokens == 1
|
||||
assert response.details.seed is None
|
||||
assert len(response.details.prefill) == 1
|
||||
assert response.details.prefill[0] == PrefillToken(
|
||||
id=9234, text="test", logprob=None
|
||||
)
|
||||
assert len(response.details.tokens) == 1
|
||||
assert response.details.tokens[0] == Token(
|
||||
id=17, text=".", logprob=-1.75, special=False
|
||||
)
|
||||
|
||||
|
||||
def test_generate_not_found(fake_url, hf_headers):
|
||||
client = Client(fake_url, hf_headers)
|
||||
with pytest.raises(NotFoundError):
|
||||
client.generate("test")
|
||||
|
||||
|
||||
def test_generate_validation_error(bloom_url, hf_headers):
|
||||
client = Client(bloom_url, hf_headers)
|
||||
with pytest.raises(ValidationError):
|
||||
client.generate("test", max_new_tokens=10_000)
|
||||
|
||||
|
||||
def test_generate_stream(bloom_url, hf_headers):
|
||||
client = Client(bloom_url, hf_headers)
|
||||
responses = [
|
||||
response for response in client.generate_stream("test", max_new_tokens=1)
|
||||
]
|
||||
|
||||
assert len(responses) == 1
|
||||
response = responses[0]
|
||||
|
||||
assert response.generated_text == "."
|
||||
assert response.details.finish_reason == FinishReason.Length
|
||||
assert response.details.generated_tokens == 1
|
||||
assert response.details.seed is None
|
||||
|
||||
|
||||
def test_generate_stream_not_found(fake_url, hf_headers):
|
||||
client = Client(fake_url, hf_headers)
|
||||
with pytest.raises(NotFoundError):
|
||||
list(client.generate_stream("test"))
|
||||
|
||||
|
||||
def test_generate_stream_validation_error(bloom_url, hf_headers):
|
||||
client = Client(bloom_url, hf_headers)
|
||||
with pytest.raises(ValidationError):
|
||||
list(client.generate_stream("test", max_new_tokens=10_000))
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_generate_async(bloom_url, hf_headers):
|
||||
client = AsyncClient(bloom_url, hf_headers)
|
||||
response = await client.generate("test", max_new_tokens=1)
|
||||
|
||||
assert response.generated_text == "."
|
||||
assert response.details.finish_reason == FinishReason.Length
|
||||
assert response.details.generated_tokens == 1
|
||||
assert response.details.seed is None
|
||||
assert len(response.details.prefill) == 1
|
||||
assert response.details.prefill[0] == PrefillToken(
|
||||
id=9234, text="test", logprob=None
|
||||
)
|
||||
assert len(response.details.tokens) == 1
|
||||
assert response.details.tokens[0] == Token(
|
||||
id=17, text=".", logprob=-1.75, special=False
|
||||
)
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_generate_async_not_found(fake_url, hf_headers):
|
||||
client = AsyncClient(fake_url, hf_headers)
|
||||
with pytest.raises(NotFoundError):
|
||||
await client.generate("test")
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_generate_async_validation_error(bloom_url, hf_headers):
|
||||
client = AsyncClient(bloom_url, hf_headers)
|
||||
with pytest.raises(ValidationError):
|
||||
await client.generate("test", max_new_tokens=10_000)
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_generate_stream_async(bloom_url, hf_headers):
|
||||
client = AsyncClient(bloom_url, hf_headers)
|
||||
responses = [
|
||||
response async for response in client.generate_stream("test", max_new_tokens=1)
|
||||
]
|
||||
|
||||
assert len(responses) == 1
|
||||
response = responses[0]
|
||||
|
||||
assert response.generated_text == "."
|
||||
assert response.details.finish_reason == FinishReason.Length
|
||||
assert response.details.generated_tokens == 1
|
||||
assert response.details.seed is None
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_generate_stream_async_not_found(fake_url, hf_headers):
|
||||
client = AsyncClient(fake_url, hf_headers)
|
||||
with pytest.raises(NotFoundError):
|
||||
async for _ in client.generate_stream("test"):
|
||||
pass
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_generate_stream_async_validation_error(bloom_url, hf_headers):
|
||||
client = AsyncClient(bloom_url, hf_headers)
|
||||
with pytest.raises(ValidationError):
|
||||
async for _ in client.generate_stream("test", max_new_tokens=10_000):
|
||||
pass
|
||||
64
clients/python/tests/test_errors.py
Normal file
64
clients/python/tests/test_errors.py
Normal file
@ -0,0 +1,64 @@
|
||||
from text_generation.errors import (
|
||||
parse_error,
|
||||
GenerationError,
|
||||
IncompleteGenerationError,
|
||||
OverloadedError,
|
||||
ValidationError,
|
||||
BadRequestError,
|
||||
ShardNotReadyError,
|
||||
ShardTimeoutError,
|
||||
NotFoundError,
|
||||
RateLimitExceededError,
|
||||
UnknownError,
|
||||
)
|
||||
|
||||
|
||||
def test_generation_error():
|
||||
payload = {"error_type": "generation", "error": "test"}
|
||||
assert isinstance(parse_error(400, payload), GenerationError)
|
||||
|
||||
|
||||
def test_incomplete_generation_error():
|
||||
payload = {"error_type": "incomplete_generation", "error": "test"}
|
||||
assert isinstance(parse_error(400, payload), IncompleteGenerationError)
|
||||
|
||||
|
||||
def test_overloaded_error():
|
||||
payload = {"error_type": "overloaded", "error": "test"}
|
||||
assert isinstance(parse_error(400, payload), OverloadedError)
|
||||
|
||||
|
||||
def test_validation_error():
|
||||
payload = {"error_type": "validation", "error": "test"}
|
||||
assert isinstance(parse_error(400, payload), ValidationError)
|
||||
|
||||
|
||||
def test_bad_request_error():
|
||||
payload = {"error": "test"}
|
||||
assert isinstance(parse_error(400, payload), BadRequestError)
|
||||
|
||||
|
||||
def test_shard_not_ready_error():
|
||||
payload = {"error": "test"}
|
||||
assert isinstance(parse_error(403, payload), ShardNotReadyError)
|
||||
assert isinstance(parse_error(424, payload), ShardNotReadyError)
|
||||
|
||||
|
||||
def test_shard_timeout_error():
|
||||
payload = {"error": "test"}
|
||||
assert isinstance(parse_error(504, payload), ShardTimeoutError)
|
||||
|
||||
|
||||
def test_not_found_error():
|
||||
payload = {"error": "test"}
|
||||
assert isinstance(parse_error(404, payload), NotFoundError)
|
||||
|
||||
|
||||
def test_rate_limit_exceeded_error():
|
||||
payload = {"error": "test"}
|
||||
assert isinstance(parse_error(429, payload), RateLimitExceededError)
|
||||
|
||||
|
||||
def test_unknown_error():
|
||||
payload = {"error": "test"}
|
||||
assert isinstance(parse_error(500, payload), UnknownError)
|
||||
39
clients/python/tests/test_types.py
Normal file
39
clients/python/tests/test_types.py
Normal file
@ -0,0 +1,39 @@
|
||||
import pytest
|
||||
|
||||
from text_generation.types import Parameters
|
||||
from text_generation.errors import ValidationError
|
||||
|
||||
|
||||
def test_parameters_validation():
|
||||
# Test repetition_penalty
|
||||
Parameters(repetition_penalty=1)
|
||||
with pytest.raises(ValidationError):
|
||||
Parameters(repetition_penalty=0)
|
||||
with pytest.raises(ValidationError):
|
||||
Parameters(repetition_penalty=-1)
|
||||
|
||||
# Test seed
|
||||
Parameters(seed=1)
|
||||
with pytest.raises(ValidationError):
|
||||
Parameters(seed=-1)
|
||||
|
||||
# Test temperature
|
||||
Parameters(temperature=1)
|
||||
with pytest.raises(ValidationError):
|
||||
Parameters(temperature=0)
|
||||
with pytest.raises(ValidationError):
|
||||
Parameters(temperature=-1)
|
||||
|
||||
# Test top_k
|
||||
Parameters(top_k=1)
|
||||
with pytest.raises(ValidationError):
|
||||
Parameters(top_k=0)
|
||||
with pytest.raises(ValidationError):
|
||||
Parameters(top_k=-1)
|
||||
|
||||
# Test top_p
|
||||
Parameters(top_p=1)
|
||||
with pytest.raises(ValidationError):
|
||||
Parameters(top_p=0)
|
||||
with pytest.raises(ValidationError):
|
||||
Parameters(top_p=-1)
|
||||
@ -1,2 +1,18 @@
|
||||
# Copyright 2023 The HuggingFace Team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
__version__ = "0.3.2"
|
||||
|
||||
from text_generation.client import Client, AsyncClient
|
||||
from text_generation.api_inference import APIInferenceAsyncClient
|
||||
from text_generation.api_inference import InferenceAPIClient, InferenceAPIAsyncClient
|
||||
|
||||
@ -5,8 +5,9 @@ import json
|
||||
import warnings
|
||||
|
||||
from typing import List, Optional
|
||||
from huggingface_hub.utils import build_hf_headers
|
||||
|
||||
from text_generation import Client, AsyncClient
|
||||
from text_generation import Client, AsyncClient, __version__
|
||||
from text_generation.errors import NotSupportedError
|
||||
|
||||
INFERENCE_ENDPOINT = os.environ.get(
|
||||
@ -17,6 +18,12 @@ SUPPORTED_MODELS = None
|
||||
|
||||
|
||||
def get_supported_models() -> Optional[List[str]]:
|
||||
"""
|
||||
Get the list of supported text-generation models from GitHub
|
||||
|
||||
Returns:
|
||||
Optional[List[str]]: supported models list or None if unable to get the list from GitHub
|
||||
"""
|
||||
global SUPPORTED_MODELS
|
||||
if SUPPORTED_MODELS is not None:
|
||||
return SUPPORTED_MODELS
|
||||
@ -34,31 +41,110 @@ def get_supported_models() -> Optional[List[str]]:
|
||||
return None
|
||||
|
||||
|
||||
class APIInferenceClient(Client):
|
||||
def __init__(self, model_id: str, token: Optional[str] = None, timeout: int = 10):
|
||||
class InferenceAPIClient(Client):
|
||||
"""Client to make calls to the HuggingFace Inference API.
|
||||
|
||||
Only supports a subset of the available text-generation or text2text-generation models that are served using
|
||||
text-generation-inference
|
||||
|
||||
Example:
|
||||
|
||||
```python
|
||||
>>> from text_generation import InferenceAPIClient
|
||||
|
||||
>>> client = InferenceAPIClient("bigscience/bloomz")
|
||||
>>> client.generate("Why is the sky blue?").generated_text
|
||||
' Rayleigh scattering'
|
||||
|
||||
>>> result = ""
|
||||
>>> for response in client.generate_stream("Why is the sky blue?"):
|
||||
>>> if not response.token.special:
|
||||
>>> result += response.token.text
|
||||
>>> result
|
||||
' Rayleigh scattering'
|
||||
```
|
||||
"""
|
||||
|
||||
def __init__(self, repo_id: str, token: Optional[str] = None, timeout: int = 10):
|
||||
"""
|
||||
Init headers and API information
|
||||
|
||||
Args:
|
||||
repo_id (`str`):
|
||||
Id of repository (e.g. `bigscience/bloom`).
|
||||
token (`str`, `optional`):
|
||||
The API token to use as HTTP bearer authorization. This is not
|
||||
the authentication token. You can find the token in
|
||||
https://huggingface.co/settings/token. Alternatively, you can
|
||||
find both your organizations and personal API tokens using
|
||||
`HfApi().whoami(token)`.
|
||||
timeout (`int`):
|
||||
Timeout in seconds
|
||||
"""
|
||||
|
||||
# Text Generation Inference client only supports a subset of the available hub models
|
||||
supported_models = get_supported_models()
|
||||
if supported_models is not None and model_id not in supported_models:
|
||||
raise NotSupportedError(model_id)
|
||||
if supported_models is not None and repo_id not in supported_models:
|
||||
raise NotSupportedError(repo_id)
|
||||
|
||||
headers = {}
|
||||
if token is not None:
|
||||
headers = {"Authorization": f"Bearer {token}"}
|
||||
base_url = f"{INFERENCE_ENDPOINT}/models/{model_id}"
|
||||
headers = build_hf_headers(
|
||||
token=token, library_name="text-generation", library_version=__version__
|
||||
)
|
||||
base_url = f"{INFERENCE_ENDPOINT}/models/{repo_id}"
|
||||
|
||||
super(APIInferenceClient, self).__init__(base_url, headers, timeout)
|
||||
super(InferenceAPIClient, self).__init__(base_url, headers, timeout)
|
||||
|
||||
|
||||
class APIInferenceAsyncClient(AsyncClient):
|
||||
def __init__(self, model_id: str, token: Optional[str] = None, timeout: int = 10):
|
||||
class InferenceAPIAsyncClient(AsyncClient):
|
||||
"""Aynschronous Client to make calls to the HuggingFace Inference API.
|
||||
|
||||
Only supports a subset of the available text-generation or text2text-generation models that are served using
|
||||
text-generation-inference
|
||||
|
||||
Example:
|
||||
|
||||
```python
|
||||
>>> from text_generation import InferenceAPIAsyncClient
|
||||
|
||||
>>> client = InferenceAPIAsyncClient("bigscience/bloomz")
|
||||
>>> response = await client.generate("Why is the sky blue?")
|
||||
>>> response.generated_text
|
||||
' Rayleigh scattering'
|
||||
|
||||
>>> result = ""
|
||||
>>> async for response in client.generate_stream("Why is the sky blue?"):
|
||||
>>> if not response.token.special:
|
||||
>>> result += response.token.text
|
||||
>>> result
|
||||
' Rayleigh scattering'
|
||||
```
|
||||
"""
|
||||
|
||||
def __init__(self, repo_id: str, token: Optional[str] = None, timeout: int = 10):
|
||||
"""
|
||||
Init headers and API information
|
||||
|
||||
Args:
|
||||
repo_id (`str`):
|
||||
Id of repository (e.g. `bigscience/bloom`).
|
||||
token (`str`, `optional`):
|
||||
The API token to use as HTTP bearer authorization. This is not
|
||||
the authentication token. You can find the token in
|
||||
https://huggingface.co/settings/token. Alternatively, you can
|
||||
find both your organizations and personal API tokens using
|
||||
`HfApi().whoami(token)`.
|
||||
timeout (`int`):
|
||||
Timeout in seconds
|
||||
"""
|
||||
|
||||
# Text Generation Inference client only supports a subset of the available hub models
|
||||
supported_models = get_supported_models()
|
||||
if supported_models is not None and model_id not in supported_models:
|
||||
raise NotSupportedError(model_id)
|
||||
if supported_models is not None and repo_id not in supported_models:
|
||||
raise NotSupportedError(repo_id)
|
||||
|
||||
headers = {}
|
||||
if token is not None:
|
||||
headers = {"Authorization": f"Bearer {token}"}
|
||||
base_url = f"{INFERENCE_ENDPOINT}/models/{model_id}"
|
||||
headers = build_hf_headers(
|
||||
token=token, library_name="text-generation", library_version=__version__
|
||||
)
|
||||
base_url = f"{INFERENCE_ENDPOINT}/models/{repo_id}"
|
||||
|
||||
super(APIInferenceAsyncClient, self).__init__(base_url, headers, timeout)
|
||||
super(InferenceAPIAsyncClient, self).__init__(base_url, headers, timeout)
|
||||
|
||||
@ -15,9 +15,38 @@ from text_generation.errors import parse_error
|
||||
|
||||
|
||||
class Client:
|
||||
"""Client to make calls to a text-generation-inference instance
|
||||
|
||||
Example:
|
||||
|
||||
```python
|
||||
>>> from text_generation import Client
|
||||
|
||||
>>> client = Client("https://api-inference.huggingface.co/models/bigscience/bloomz")
|
||||
>>> client.generate("Why is the sky blue?").generated_text
|
||||
' Rayleigh scattering'
|
||||
|
||||
>>> result = ""
|
||||
>>> for response in client.generate_stream("Why is the sky blue?"):
|
||||
>>> if not response.token.special:
|
||||
>>> result += response.token.text
|
||||
>>> result
|
||||
' Rayleigh scattering'
|
||||
```
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self, base_url: str, headers: Dict[str, str] = None, timeout: int = 10
|
||||
self, base_url: str, headers: Optional[Dict[str, str]] = None, timeout: int = 10
|
||||
):
|
||||
"""
|
||||
Args:
|
||||
base_url (`str`):
|
||||
text-generation-inference instance base url
|
||||
headers (`Optional[Dict[str, str]]`):
|
||||
Additional headers
|
||||
timeout (`int`):
|
||||
Timeout in seconds
|
||||
"""
|
||||
self.base_url = base_url
|
||||
self.headers = headers
|
||||
self.timeout = timeout
|
||||
@ -30,12 +59,45 @@ class Client:
|
||||
repetition_penalty: Optional[float] = None,
|
||||
return_full_text: bool = False,
|
||||
seed: Optional[int] = None,
|
||||
stop: Optional[List[str]] = None,
|
||||
stop_sequences: Optional[List[str]] = None,
|
||||
temperature: Optional[float] = None,
|
||||
top_k: Optional[int] = None,
|
||||
top_p: Optional[float] = None,
|
||||
watermark: bool = False,
|
||||
watermarking: bool = False,
|
||||
) -> Response:
|
||||
"""
|
||||
Given a prompt, generate the following text
|
||||
|
||||
Args:
|
||||
prompt (`str`):
|
||||
Input text
|
||||
do_sample (`bool`):
|
||||
Activate logits sampling
|
||||
max_new_tokens (`int`):
|
||||
Maximum number of generated tokens
|
||||
repetition_penalty (`float`):
|
||||
The parameter for repetition penalty. 1.0 means no penalty. See [this
|
||||
paper](https://arxiv.org/pdf/1909.05858.pdf) for more details.
|
||||
return_full_text (`bool`):
|
||||
Whether to prepend the prompt to the generated text
|
||||
seed (`int`):
|
||||
Random sampling seed
|
||||
stop_sequences (`List[str]`):
|
||||
Stop generating tokens if a member of `stop_sequences` is generated
|
||||
temperature (`float`):
|
||||
The value used to module the logits distribution.
|
||||
top_k (`int`):
|
||||
The number of highest probability vocabulary tokens to keep for top-k-filtering.
|
||||
top_p (`float`):
|
||||
If set to < 1, only the smallest set of most probable tokens with probabilities that add up to `top_p` or
|
||||
higher are kept for generation.
|
||||
watermarking (`bool`):
|
||||
Watermarking with [A Watermark for Large Language Models](https://arxiv.org/abs/2301.10226)
|
||||
|
||||
Returns:
|
||||
Response: generated response
|
||||
"""
|
||||
# Validate parameters
|
||||
parameters = Parameters(
|
||||
details=True,
|
||||
do_sample=do_sample,
|
||||
@ -43,11 +105,11 @@ class Client:
|
||||
repetition_penalty=repetition_penalty,
|
||||
return_full_text=return_full_text,
|
||||
seed=seed,
|
||||
stop=stop if stop is not None else [],
|
||||
stop=stop_sequences if stop_sequences is not None else [],
|
||||
temperature=temperature,
|
||||
top_k=top_k,
|
||||
top_p=top_p,
|
||||
watermark=watermark,
|
||||
watermark=watermarking,
|
||||
)
|
||||
request = Request(inputs=prompt, stream=False, parameters=parameters)
|
||||
|
||||
@ -70,12 +132,45 @@ class Client:
|
||||
repetition_penalty: Optional[float] = None,
|
||||
return_full_text: bool = False,
|
||||
seed: Optional[int] = None,
|
||||
stop: Optional[List[str]] = None,
|
||||
stop_sequences: Optional[List[str]] = None,
|
||||
temperature: Optional[float] = None,
|
||||
top_k: Optional[int] = None,
|
||||
top_p: Optional[float] = None,
|
||||
watermark: bool = False,
|
||||
watermarking: bool = False,
|
||||
) -> Iterator[StreamResponse]:
|
||||
"""
|
||||
Given a prompt, generate the following stream of tokens
|
||||
|
||||
Args:
|
||||
prompt (`str`):
|
||||
Input text
|
||||
do_sample (`bool`):
|
||||
Activate logits sampling
|
||||
max_new_tokens (`int`):
|
||||
Maximum number of generated tokens
|
||||
repetition_penalty (`float`):
|
||||
The parameter for repetition penalty. 1.0 means no penalty. See [this
|
||||
paper](https://arxiv.org/pdf/1909.05858.pdf) for more details.
|
||||
return_full_text (`bool`):
|
||||
Whether to prepend the prompt to the generated text
|
||||
seed (`int`):
|
||||
Random sampling seed
|
||||
stop_sequences (`List[str]`):
|
||||
Stop generating tokens if a member of `stop_sequences` is generated
|
||||
temperature (`float`):
|
||||
The value used to module the logits distribution.
|
||||
top_k (`int`):
|
||||
The number of highest probability vocabulary tokens to keep for top-k-filtering.
|
||||
top_p (`float`):
|
||||
If set to < 1, only the smallest set of most probable tokens with probabilities that add up to `top_p` or
|
||||
higher are kept for generation.
|
||||
watermarking (`bool`):
|
||||
Watermarking with [A Watermark for Large Language Models](https://arxiv.org/abs/2301.10226)
|
||||
|
||||
Returns:
|
||||
Iterator[StreamResponse]: stream of generated tokens
|
||||
"""
|
||||
# Validate parameters
|
||||
parameters = Parameters(
|
||||
details=True,
|
||||
do_sample=do_sample,
|
||||
@ -83,11 +178,11 @@ class Client:
|
||||
repetition_penalty=repetition_penalty,
|
||||
return_full_text=return_full_text,
|
||||
seed=seed,
|
||||
stop=stop if stop is not None else [],
|
||||
stop=stop_sequences if stop_sequences is not None else [],
|
||||
temperature=temperature,
|
||||
top_k=top_k,
|
||||
top_p=top_p,
|
||||
watermark=watermark,
|
||||
watermark=watermarking,
|
||||
)
|
||||
request = Request(inputs=prompt, stream=True, parameters=parameters)
|
||||
|
||||
@ -96,31 +191,67 @@ class Client:
|
||||
json=request.dict(),
|
||||
headers=self.headers,
|
||||
timeout=self.timeout,
|
||||
stream=True,
|
||||
stream=False,
|
||||
)
|
||||
|
||||
if resp.status_code != 200:
|
||||
raise parse_error(resp.status_code, resp.json())
|
||||
|
||||
# Parse ServerSentEvents
|
||||
for byte_payload in resp.iter_lines():
|
||||
# Skip line
|
||||
if byte_payload == b"\n":
|
||||
continue
|
||||
|
||||
payload = byte_payload.decode("utf-8")
|
||||
|
||||
# Event data
|
||||
if payload.startswith("data:"):
|
||||
# Decode payload
|
||||
json_payload = json.loads(payload.lstrip("data:").rstrip("/n"))
|
||||
# Parse payload
|
||||
try:
|
||||
response = StreamResponse(**json_payload)
|
||||
except ValidationError:
|
||||
# If we failed to parse the payload, then it is an error payload
|
||||
raise parse_error(resp.status_code, json_payload)
|
||||
yield response
|
||||
|
||||
|
||||
class AsyncClient:
|
||||
"""Asynchronous Client to make calls to a text-generation-inference instance
|
||||
|
||||
Example:
|
||||
|
||||
```python
|
||||
>>> from text_generation import AsyncClient
|
||||
|
||||
>>> client = AsyncClient("https://api-inference.huggingface.co/models/bigscience/bloomz")
|
||||
>>> response = await client.generate("Why is the sky blue?")
|
||||
>>> response.generated_text
|
||||
' Rayleigh scattering'
|
||||
|
||||
>>> result = ""
|
||||
>>> async for response in client.generate_stream("Why is the sky blue?"):
|
||||
>>> if not response.token.special:
|
||||
>>> result += response.token.text
|
||||
>>> result
|
||||
' Rayleigh scattering'
|
||||
```
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self, base_url: str, headers: Dict[str, str] = None, timeout: int = 10
|
||||
self, base_url: str, headers: Optional[Dict[str, str]] = None, timeout: int = 10
|
||||
):
|
||||
"""
|
||||
Args:
|
||||
base_url (`str`):
|
||||
text-generation-inference instance base url
|
||||
headers (`Optional[Dict[str, str]]`):
|
||||
Additional headers
|
||||
timeout (`int`):
|
||||
Timeout in seconds
|
||||
"""
|
||||
self.base_url = base_url
|
||||
self.headers = headers
|
||||
self.timeout = ClientTimeout(timeout * 60)
|
||||
@ -133,12 +264,45 @@ class AsyncClient:
|
||||
repetition_penalty: Optional[float] = None,
|
||||
return_full_text: bool = False,
|
||||
seed: Optional[int] = None,
|
||||
stop: Optional[List[str]] = None,
|
||||
stop_sequences: Optional[List[str]] = None,
|
||||
temperature: Optional[float] = None,
|
||||
top_k: Optional[int] = None,
|
||||
top_p: Optional[float] = None,
|
||||
watermark: bool = False,
|
||||
watermarking: bool = False,
|
||||
) -> Response:
|
||||
"""
|
||||
Given a prompt, generate the following text asynchronously
|
||||
|
||||
Args:
|
||||
prompt (`str`):
|
||||
Input text
|
||||
do_sample (`bool`):
|
||||
Activate logits sampling
|
||||
max_new_tokens (`int`):
|
||||
Maximum number of generated tokens
|
||||
repetition_penalty (`float`):
|
||||
The parameter for repetition penalty. 1.0 means no penalty. See [this
|
||||
paper](https://arxiv.org/pdf/1909.05858.pdf) for more details.
|
||||
return_full_text (`bool`):
|
||||
Whether to prepend the prompt to the generated text
|
||||
seed (`int`):
|
||||
Random sampling seed
|
||||
stop_sequences (`List[str]`):
|
||||
Stop generating tokens if a member of `stop_sequences` is generated
|
||||
temperature (`float`):
|
||||
The value used to module the logits distribution.
|
||||
top_k (`int`):
|
||||
The number of highest probability vocabulary tokens to keep for top-k-filtering.
|
||||
top_p (`float`):
|
||||
If set to < 1, only the smallest set of most probable tokens with probabilities that add up to `top_p` or
|
||||
higher are kept for generation.
|
||||
watermarking (`bool`):
|
||||
Watermarking with [A Watermark for Large Language Models](https://arxiv.org/abs/2301.10226)
|
||||
|
||||
Returns:
|
||||
Response: generated response
|
||||
"""
|
||||
# Validate parameters
|
||||
parameters = Parameters(
|
||||
details=True,
|
||||
do_sample=do_sample,
|
||||
@ -146,17 +310,18 @@ class AsyncClient:
|
||||
repetition_penalty=repetition_penalty,
|
||||
return_full_text=return_full_text,
|
||||
seed=seed,
|
||||
stop=stop if stop is not None else [],
|
||||
stop=stop_sequences if stop_sequences is not None else [],
|
||||
temperature=temperature,
|
||||
top_k=top_k,
|
||||
top_p=top_p,
|
||||
watermark=watermark,
|
||||
watermark=watermarking,
|
||||
)
|
||||
request = Request(inputs=prompt, stream=False, parameters=parameters)
|
||||
|
||||
async with ClientSession(headers=self.headers, timeout=self.timeout) as session:
|
||||
async with session.post(self.base_url, json=request.dict()) as resp:
|
||||
payload = await resp.json()
|
||||
|
||||
if resp.status != 200:
|
||||
raise parse_error(resp.status, payload)
|
||||
return Response(**payload[0])
|
||||
@ -169,12 +334,45 @@ class AsyncClient:
|
||||
repetition_penalty: Optional[float] = None,
|
||||
return_full_text: bool = False,
|
||||
seed: Optional[int] = None,
|
||||
stop: Optional[List[str]] = None,
|
||||
stop_sequences: Optional[List[str]] = None,
|
||||
temperature: Optional[float] = None,
|
||||
top_k: Optional[int] = None,
|
||||
top_p: Optional[float] = None,
|
||||
watermark: bool = False,
|
||||
watermarking: bool = False,
|
||||
) -> AsyncIterator[StreamResponse]:
|
||||
"""
|
||||
Given a prompt, generate the following stream of tokens asynchronously
|
||||
|
||||
Args:
|
||||
prompt (`str`):
|
||||
Input text
|
||||
do_sample (`bool`):
|
||||
Activate logits sampling
|
||||
max_new_tokens (`int`):
|
||||
Maximum number of generated tokens
|
||||
repetition_penalty (`float`):
|
||||
The parameter for repetition penalty. 1.0 means no penalty. See [this
|
||||
paper](https://arxiv.org/pdf/1909.05858.pdf) for more details.
|
||||
return_full_text (`bool`):
|
||||
Whether to prepend the prompt to the generated text
|
||||
seed (`int`):
|
||||
Random sampling seed
|
||||
stop_sequences (`List[str]`):
|
||||
Stop generating tokens if a member of `stop_sequences` is generated
|
||||
temperature (`float`):
|
||||
The value used to module the logits distribution.
|
||||
top_k (`int`):
|
||||
The number of highest probability vocabulary tokens to keep for top-k-filtering.
|
||||
top_p (`float`):
|
||||
If set to < 1, only the smallest set of most probable tokens with probabilities that add up to `top_p` or
|
||||
higher are kept for generation.
|
||||
watermarking (`bool`):
|
||||
Watermarking with [A Watermark for Large Language Models](https://arxiv.org/abs/2301.10226)
|
||||
|
||||
Returns:
|
||||
AsyncIterator[StreamResponse]: stream of generated tokens
|
||||
"""
|
||||
# Validate parameters
|
||||
parameters = Parameters(
|
||||
details=True,
|
||||
do_sample=do_sample,
|
||||
@ -182,29 +380,36 @@ class AsyncClient:
|
||||
repetition_penalty=repetition_penalty,
|
||||
return_full_text=return_full_text,
|
||||
seed=seed,
|
||||
stop=stop if stop is not None else [],
|
||||
stop=stop_sequences if stop_sequences is not None else [],
|
||||
temperature=temperature,
|
||||
top_k=top_k,
|
||||
top_p=top_p,
|
||||
watermark=watermark,
|
||||
watermark=watermarking,
|
||||
)
|
||||
request = Request(inputs=prompt, stream=True, parameters=parameters)
|
||||
|
||||
async with ClientSession(headers=self.headers, timeout=self.timeout) as session:
|
||||
async with session.post(self.base_url, json=request.dict()) as resp:
|
||||
|
||||
if resp.status != 200:
|
||||
raise parse_error(resp.status, await resp.json())
|
||||
|
||||
# Parse ServerSentEvents
|
||||
async for byte_payload in resp.content:
|
||||
# Skip line
|
||||
if byte_payload == b"\n":
|
||||
continue
|
||||
|
||||
payload = byte_payload.decode("utf-8")
|
||||
|
||||
# Event data
|
||||
if payload.startswith("data:"):
|
||||
# Decode payload
|
||||
json_payload = json.loads(payload.lstrip("data:").rstrip("/n"))
|
||||
# Parse payload
|
||||
try:
|
||||
response = StreamResponse(**json_payload)
|
||||
except ValidationError:
|
||||
# If we failed to parse the payload, then it is an error payload
|
||||
raise parse_error(resp.status, json_payload)
|
||||
yield response
|
||||
|
||||
@ -33,7 +33,7 @@ class ShardNotReadyError(Exception):
|
||||
super().__init__(message)
|
||||
|
||||
|
||||
class TimeoutError(Exception):
|
||||
class ShardTimeoutError(Exception):
|
||||
def __init__(self, message: str):
|
||||
super().__init__(message)
|
||||
|
||||
@ -64,6 +64,19 @@ class UnknownError(Exception):
|
||||
|
||||
|
||||
def parse_error(status_code: int, payload: Dict[str, str]) -> Exception:
|
||||
"""
|
||||
Parse error given an HTTP status code and a json payload
|
||||
|
||||
Args:
|
||||
status_code (`int`):
|
||||
HTTP status code
|
||||
payload (`Dict[str, str]`):
|
||||
Json payload
|
||||
|
||||
Returns:
|
||||
Exception: parsed exception
|
||||
|
||||
"""
|
||||
# Try to parse a Text Generation Inference error
|
||||
message = payload["error"]
|
||||
if "error_type" in payload:
|
||||
@ -83,7 +96,7 @@ def parse_error(status_code: int, payload: Dict[str, str]) -> Exception:
|
||||
if status_code == 403 or status_code == 424:
|
||||
return ShardNotReadyError(message)
|
||||
if status_code == 504:
|
||||
return TimeoutError(message)
|
||||
return ShardTimeoutError(message)
|
||||
if status_code == 404:
|
||||
return NotFoundError(message)
|
||||
if status_code == 429:
|
||||
|
||||
@ -10,7 +10,7 @@ class Parameters(BaseModel):
|
||||
max_new_tokens: int = 20
|
||||
repetition_penalty: Optional[float] = None
|
||||
return_full_text: bool = False
|
||||
stop: List[str]
|
||||
stop: List[str] = []
|
||||
seed: Optional[int]
|
||||
temperature: Optional[float]
|
||||
top_k: Optional[int]
|
||||
@ -20,25 +20,25 @@ class Parameters(BaseModel):
|
||||
|
||||
@validator("repetition_penalty")
|
||||
def valid_repetition_penalty(cls, v):
|
||||
if v is not None and v is v < 0:
|
||||
if v is not None and v is v <= 0:
|
||||
raise ValidationError("`repetition_penalty` must be strictly positive")
|
||||
return v
|
||||
|
||||
@validator("seed")
|
||||
def valid_seed(cls, v):
|
||||
if v is not None and v is v < 0:
|
||||
raise ValidationError("`seed` must be strictly positive")
|
||||
raise ValidationError("`seed` must be positive")
|
||||
return v
|
||||
|
||||
@validator("temperature")
|
||||
def valid_temp(cls, v):
|
||||
if v is not None and v < 0:
|
||||
if v is not None and v <= 0:
|
||||
raise ValidationError("`temperature` must be strictly positive")
|
||||
return v
|
||||
|
||||
@validator("top_k")
|
||||
def valid_top_k(cls, v):
|
||||
if v is not None and v < 0:
|
||||
if v is not None and v <= 0:
|
||||
raise ValidationError("`top_k` must be strictly positive")
|
||||
return v
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user