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release 0.1.2 (#266)

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Adil Hafeez 2024-11-12 23:56:33 -08:00 • committed by GitHub
parent 31749bfc74
commit d1dd8710a4
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10 changed files with 4090 additions and 502 deletions
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2
.github/workflows/e2e_tests.yml vendored
View file

@ -18,7 +18,7 @@ jobs:
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: "3.10"
python-version: "3.12"
- name: Install Poetry
run: |

2
.github/workflows/model-server-tests.yml vendored
View file

@ -21,7 +21,7 @@ jobs:
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: "3.10" # Adjust to your Python version
python-version: "3.12"
# Step 3: Install Poetry
- name: Install Poetry

3
api_llm_gateway.rest
View file

@ -14,7 +14,8 @@ Authorization: Bearer {{access_key}}
"content": "hello"
}
],
"model": "gpt-4o-mini"
"model": "gpt-4o-mini",
"stream": true
}
### openai request (streaming)

3933
arch/tools/poetry.lock generated
View file

File diff suppressed because it is too large Load diff

8
arch/tools/pyproject.toml
View file

@ -1,6 +1,6 @@
[tool.poetry]
name = "archgw"
version = "0.1.0"
version = "0.1.2"
description = "Python-based CLI tool to manage Arch Gateway."
authors = ["Katanemo Labs, Inc."]
packages = [
@ -15,14 +15,14 @@ include = [
]
[tool.poetry.dependencies]
python = "^3.10"
python = ">=3.12"
pyyaml = "^6.0.2"
pydantic = "^2.9.2"
click = "^8.1.7"
jinja2 = "^3.1.4"
jsonschema = "^4.23.0"
setuptools = "75.3.0"
archgw_modelserver = "0.1.1"
setuptools = "75.4.0"
archgw_modelserver = "0.1.2"
huggingface_hub = "^0.26.0"
[tool.poetry.scripts]

18
model_server/app/tests/test_loaders_cpu.py
View file

@ -33,15 +33,15 @@ def test_get_embedding_model(mock_tokenizer, mock_automodel, mock_ort_model, moc
# Assertions
assert embedding_model["model_name"] == "katanemo/bge-large-en-v1.5"
assert mock_tokenizer.called_once_with(
mock_tokenizer.assert_called_once_with(
"katanemo/bge-large-en-v1.5", trust_remote_code=True
)
if glb.DEVICE != "cuda":
assert mock_ort_model.called_once_with(
mock_ort_model.assert_called_once_with(
"katanemo/bge-large-en-v1.5", file_name="onnx/model.onnx"
)
else:
assert mock_automodel.called_once_with(
mock_automodel.assert_called_once_with(
"katanemo/bge-large-en-v1.5", device_map=glb.DEVICE
)
@ -59,9 +59,9 @@ def test_get_zero_shot_model(mock_tokenizer, mock_pipeline, mock_ort_model, mock
# Assertions
assert zero_shot_model["model_name"] == "katanemo/bart-large-mnli"
assert mock_tokenizer.called_once_with("katanemo/bart-large-mnli")
mock_tokenizer.assert_called_once_with("katanemo/bart-large-mnli")
if glb.DEVICE != "cuda":
assert mock_ort_model.called_once_with(
mock_ort_model.assert_called_once_with(
"katanemo/bart-large-mnli", file_name="onnx/model.onnx"
)
else:
@ -72,7 +72,7 @@ def test_get_zero_shot_model(mock_tokenizer, mock_pipeline, mock_ort_model, mock
@patch("app.loader.AutoTokenizer.from_pretrained")
@patch("app.loader.OVModelForSequenceClassification.from_pretrained")
@patch("app.loader.AutoModelForSequenceClassification.from_pretrained")
def test_get_prompt_guard(mock_ov_model, mock_auto_model, mock_tokenizer):
def test_get_prompt_guard(mock_auto_model, mock_ov_model, mock_tokenizer):
# Mock model based on device
if glb.DEVICE == "cpu":
mock_ov_model.return_value = MagicMock()
@ -85,17 +85,17 @@ def test_get_prompt_guard(mock_ov_model, mock_auto_model, mock_tokenizer):
# Assertions
assert prompt_guard["model_name"] == arch_guard_model_type[glb.DEVICE]
assert mock_tokenizer.called_once_with(
mock_tokenizer.assert_called_once_with(
arch_guard_model_type[glb.DEVICE], trust_remote_code=True
)
if glb.DEVICE == "cpu":
assert mock_ov_model.called_once_with(
mock_ov_model.assert_called_once_with(
arch_guard_model_type[glb.DEVICE],
device_map=glb.DEVICE,
low_cpu_mem_usage=True,
)
else:
assert mock_auto_model.called_once_with(
mock_auto_model.assert_called_once_with(
arch_guard_model_type[glb.DEVICE],
device_map=glb.DEVICE,
low_cpu_mem_usage=True,

18
model_server/app/tests/test_loaders_gpu.py
View file

@ -33,15 +33,15 @@ def test_get_embedding_model(mock_tokenizer, mock_automodel, mock_ort_model, moc
# Assertions
assert embedding_model["model_name"] == "katanemo/bge-large-en-v1.5"
assert mock_tokenizer.called_once_with(
mock_tokenizer.assert_called_once_with(
"katanemo/bge-large-en-v1.5", trust_remote_code=True
)
if glb.DEVICE != "cuda":
assert mock_ort_model.called_once_with(
mock_ort_model.assert_called_once_with(
"katanemo/bge-large-en-v1.5", file_name="onnx/model.onnx"
)
else:
assert mock_automodel.called_once_with(
mock_automodel.assert_called_once_with(
"katanemo/bge-large-en-v1.5", device_map=glb.DEVICE
)
@ -59,9 +59,9 @@ def test_get_zero_shot_model(mock_tokenizer, mock_pipeline, mock_ort_model, mock
# Assertions
assert zero_shot_model["model_name"] == "katanemo/bart-large-mnli"
assert mock_tokenizer.called_once_with("katanemo/bart-large-mnli")
mock_tokenizer.assert_called_once_with("katanemo/bart-large-mnli")
if glb.DEVICE != "cuda":
assert mock_ort_model.called_once_with(
mock_ort_model.assert_called_once_with(
"katanemo/bart-large-mnli", file_name="onnx/model.onnx"
)
else:
@ -72,7 +72,7 @@ def test_get_zero_shot_model(mock_tokenizer, mock_pipeline, mock_ort_model, mock
@patch("app.loader.AutoTokenizer.from_pretrained")
@patch("app.loader.OVModelForSequenceClassification.from_pretrained")
@patch("app.loader.AutoModelForSequenceClassification.from_pretrained")
def test_get_prompt_guard(mock_ov_model, mock_auto_model, mock_tokenizer):
def test_get_prompt_guard(mock_auto_model, mock_ov_model, mock_tokenizer):
# Mock model based on device
if glb.DEVICE == "cpu":
mock_ov_model.return_value = MagicMock()
@ -85,17 +85,17 @@ def test_get_prompt_guard(mock_ov_model, mock_auto_model, mock_tokenizer):
# Assertions
assert prompt_guard["model_name"] == arch_guard_model_type[glb.DEVICE]
assert mock_tokenizer.called_once_with(
mock_tokenizer.assert_called_once_with(
arch_guard_model_type[glb.DEVICE], trust_remote_code=True
)
if glb.DEVICE == "cpu":
assert mock_ov_model.called_once_with(
mock_ov_model.assert_called_once_with(
arch_guard_model_type[glb.DEVICE],
device_map=glb.DEVICE,
low_cpu_mem_usage=True,
)
else:
assert mock_auto_model.called_once_with(
mock_auto_model.assert_called_once_with(
arch_guard_model_type[glb.DEVICE],
device_map=glb.DEVICE,
low_cpu_mem_usage=True,

18
model_server/app/tests/test_loaders_mps.py
View file

@ -33,15 +33,15 @@ def test_get_embedding_model(mock_tokenizer, mock_automodel, mock_ort_model, moc
# Assertions
assert embedding_model["model_name"] == "katanemo/bge-large-en-v1.5"
assert mock_tokenizer.called_once_with(
mock_tokenizer.assert_called_once_with(
"katanemo/bge-large-en-v1.5", trust_remote_code=True
)
if glb.DEVICE != "cuda":
assert mock_ort_model.called_once_with(
mock_ort_model.assert_called_once_with(
"katanemo/bge-large-en-v1.5", file_name="onnx/model.onnx"
)
else:
assert mock_automodel.called_once_with(
mock_automodel.assert_called_once_with(
"katanemo/bge-large-en-v1.5", device_map=glb.DEVICE
)
@ -59,9 +59,9 @@ def test_get_zero_shot_model(mock_tokenizer, mock_pipeline, mock_ort_model, mock
# Assertions
assert zero_shot_model["model_name"] == "katanemo/bart-large-mnli"
assert mock_tokenizer.called_once_with("katanemo/bart-large-mnli")
mock_tokenizer.assert_called_once_with("katanemo/bart-large-mnli")
if glb.DEVICE != "cuda":
assert mock_ort_model.called_once_with(
mock_ort_model.assert_called_once_with(
"katanemo/bart-large-mnli", file_name="onnx/model.onnx"
)
else:
@ -72,7 +72,7 @@ def test_get_zero_shot_model(mock_tokenizer, mock_pipeline, mock_ort_model, mock
@patch("app.loader.AutoTokenizer.from_pretrained")
@patch("app.loader.OVModelForSequenceClassification.from_pretrained")
@patch("app.loader.AutoModelForSequenceClassification.from_pretrained")
def test_get_prompt_guard(mock_ov_model, mock_auto_model, mock_tokenizer):
def test_get_prompt_guard(mock_auto_model, mock_ov_model, mock_tokenizer):
# Mock model based on device
if glb.DEVICE == "cpu":
mock_ov_model.return_value = MagicMock()
@ -85,17 +85,17 @@ def test_get_prompt_guard(mock_ov_model, mock_auto_model, mock_tokenizer):
# Assertions
assert prompt_guard["model_name"] == arch_guard_model_type[glb.DEVICE]
assert mock_tokenizer.called_once_with(
mock_tokenizer.assert_called_once_with(
arch_guard_model_type[glb.DEVICE], trust_remote_code=True
)
if glb.DEVICE == "cpu":
assert mock_ov_model.called_once_with(
mock_ov_model.assert_called_once_with(
arch_guard_model_type[glb.DEVICE],
device_map=glb.DEVICE,
low_cpu_mem_usage=True,
)
else:
assert mock_auto_model.called_once_with(
mock_auto_model.assert_called_once_with(
arch_guard_model_type[glb.DEVICE],
device_map=glb.DEVICE,
low_cpu_mem_usage=True,

586
model_server/poetry.lock generated
View file

@ -156,7 +156,6 @@ files = [
[package.dependencies]
aiohappyeyeballs = ">=2.3.0"
aiosignal = ">=1.1.2"
async-timeout = {version = ">=4.0,<5.0", markers = "python_version < \"3.11\""}
attrs = ">=17.3.0"
frozenlist = ">=1.1.1"
multidict = ">=4.5,<7.0"
@ -202,10 +201,8 @@ files = [
]
[package.dependencies]
exceptiongroup = {version = ">=1.0.2", markers = "python_version < \"3.11\""}
idna = ">=2.8"
sniffio = ">=1.1"
typing-extensions = {version = ">=4.1", markers = "python_version < \"3.11\""}
[package.extras]
doc = ["Sphinx (>=7.4,<8.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
@ -223,9 +220,6 @@ files = [
{file = "asgiref-3.8.1.tar.gz", hash = "sha256:c343bd80a0bec947a9860adb4c432ffa7db769836c64238fc34bdc3fec84d590"},
]
[package.dependencies]
typing-extensions = {version = ">=4", markers = "python_version < \"3.11\""}
[package.extras]
tests = ["mypy (>=0.800)", "pytest", "pytest-asyncio"]
@ -244,17 +238,6 @@ files = [
six = ">=1.6.1,<2.0"
wheel = ">=0.23.0,<1.0"
[[package]]
name = "async-timeout"
version = "4.0.3"
description = "Timeout context manager for asyncio programs"
optional = false
python-versions = ">=3.7"
files = [
{file = "async-timeout-4.0.3.tar.gz", hash = "sha256:4640d96be84d82d02ed59ea2b7105a0f7b33abe8703703cd0ab0bf87c427522f"},
{file = "async_timeout-4.0.3-py3-none-any.whl", hash = "sha256:7405140ff1230c310e51dc27b3145b9092d659ce68ff733fb0cefe3ee42be028"},
]
[[package]]
name = "attrs"
version = "24.2.0"
@ -547,20 +530,6 @@ files = [
{file = "distro-1.9.0.tar.gz", hash = "sha256:2fa77c6fd8940f116ee1d6b94a2f90b13b5ea8d019b98bc8bafdcabcdd9bdbed"},
]
[[package]]
name = "exceptiongroup"
version = "1.2.2"
description = "Backport of PEP 654 (exception groups)"
optional = false
python-versions = ">=3.7"
files = [
{file = "exceptiongroup-1.2.2-py3-none-any.whl", hash = "sha256:3111b9d131c238bec2f8f516e123e14ba243563fb135d3fe885990585aa7795b"},
{file = "exceptiongroup-1.2.2.tar.gz", hash = "sha256:47c2edf7c6738fafb49fd34290706d1a1a2f4d1c6df275526b62cbb4aa5393cc"},
]
[package.extras]
test = ["pytest (>=6)"]
[[package]]
name = "fastapi"
version = "0.115.0"
@ -779,13 +748,13 @@ six = "*"
[[package]]
name = "googleapis-common-protos"
version = "1.65.0"
version = "1.66.0"
description = "Common protobufs used in Google APIs"
optional = false
python-versions = ">=3.7"
files = [
{file = "googleapis_common_protos-1.65.0-py2.py3-none-any.whl", hash = "sha256:2972e6c496f435b92590fd54045060867f3fe9be2c82ab148fc8885035479a63"},
{file = "googleapis_common_protos-1.65.0.tar.gz", hash = "sha256:334a29d07cddc3aa01dee4988f9afd9b2916ee2ff49d6b757155dc0d197852c0"},
{file = "googleapis_common_protos-1.66.0-py2.py3-none-any.whl", hash = "sha256:d7abcd75fabb2e0ec9f74466401f6c119a0b498e27370e9be4c94cb7e382b8ed"},
{file = "googleapis_common_protos-1.66.0.tar.gz", hash = "sha256:c3e7b33d15fdca5374cc0a7346dd92ffa847425cc4ea941d970f13680052ec8c"},
]
[package.dependencies]
@ -1071,84 +1040,84 @@ i18n = ["Babel (>=2.7)"]
[[package]]
name = "jiter"
version = "0.7.0"
version = "0.7.1"
description = "Fast iterable JSON parser."
optional = false
python-versions = ">=3.8"
files = [
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six = ">=1.12.0"
tensorboard = ">=2.18,<2.19"
tensorflow-io-gcs-filesystem = {version = ">=0.23.1", markers = "python_version < \"3.12\""}
termcolor = ">=1.1.0"
typing-extensions = ">=3.6.6"
wrapt = ">=1.11.0"
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tensorflow-cpu = ["tensorflow-cpu (>=2.16.0,<2.17.0)"]
tensorflow-gpu = ["tensorflow-gpu (>=2.16.0,<2.17.0)"]
tensorflow-rocm = ["tensorflow-rocm (>=2.16.0,<2.17.0)"]
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name = "termcolor"
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@ -3804,17 +3726,6 @@ dev = ["tokenizers[testing]"]
docs = ["setuptools-rust", "sphinx", "sphinx-rtd-theme"]
testing = ["black (==22.3)", "datasets", "numpy", "pytest", "requests", "ruff"]
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@ -4051,20 +3962,19 @@ files = [
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click = ">=7.0"
h11 = ">=0.8"
typing-extensions = {version = ">=4.0", markers = "python_version < \"3.11\""}
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version = "0.45.0"
description = "A built-package format for Python"
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@ -4415,5 +4325,5 @@ type = ["pytest-mypy"]
[metadata]
lock-version = "2.0"
python-versions = ">=3.10"
content-hash = "0059a180bd04f29e53c4b5d4649e004d7e652cbdf97ffcc4fbce741e373f9589"
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content-hash = "a659aa13f1f10ebe0b43487110ecfb6f80d3fbab08aeef61261790d712fbe7f9"

4
model_server/pyproject.toml
View file

@ -1,6 +1,6 @@
[tool.poetry]
name = "archgw_modelserver"
version = "0.1.1"
version = "0.1.2"
description = "A model server for serving models"
authors = ["Katanemo Labs, Inc <archgw@katanemo.com>"]
license = "Apache 2.0"
@ -12,7 +12,7 @@ packages = [
include = ["app/*.yaml"]
[tool.poetry.dependencies]
python = ">=3.10"
python = ">=3.12"
fastapi = "0.115.0"
sentence-transformers = "3.1.1"
torch = "2.4.1"