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feat/1001: sglang integration (#1122)
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# Copyright 2023-present, Argilla, Inc. | ||
# | ||
# 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. | ||
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from typing import TYPE_CHECKING, Any, Dict, List, Optional, Union | ||
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from pydantic import Field, PrivateAttr | ||
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from distilabel.mixins.runtime_parameters import RuntimeParameter | ||
from distilabel.models.embeddings.base import Embeddings | ||
from distilabel.models.mixins.cuda_device_placement import CudaDevicePlacementMixin | ||
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if TYPE_CHECKING: | ||
from sglang import Engine | ||
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class SGLangEmbeddings(Embeddings, CudaDevicePlacementMixin): | ||
"""`sglang` library implementation for embedding generation. | ||
Attributes: | ||
model: the model Hugging Face Hub repo id or a path to a directory containing the | ||
model weights and configuration files. | ||
dtype: the data type to use for the model. Defaults to `auto`. | ||
trust_remote_code: whether to trust the remote code when loading the model. Defaults | ||
to `False`. | ||
quantization: the quantization mode to use for the model. Defaults to `None`. | ||
revision: the revision of the model to load. Defaults to `None`. | ||
seed: the seed to use for the random number generator. Defaults to `0`. | ||
extra_kwargs: additional dictionary of keyword arguments that will be passed to the | ||
`Engine` class of `sglang` library. Defaults to `{}`. | ||
_model: the `SGLang` model instance. This attribute is meant to be used internally | ||
and should not be accessed directly. It will be set in the `load` method. | ||
References: | ||
- https://github.com/sgl-project/sglang/blob/main/python/sglang/srt/server_args.py | ||
Examples: | ||
Generating sentence embeddings: | ||
```python | ||
if __name__ == "__main__": | ||
from distilabel.models import SGLangEmbeddings | ||
embeddings = SGLangEmbeddings(model="intfloat/e5-mistral-7b-instruct") | ||
embeddings.load() | ||
results = embeddings.encode(inputs=["distilabel is awesome!", "and Argilla!"]) | ||
print(results) | ||
# [ | ||
# [0.0203704833984375, -0.0060882568359375, ...], | ||
# [0.02398681640625, 0.0177001953125 ...], | ||
# ] | ||
``` | ||
""" | ||
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model: str | ||
dtype: str = "auto" | ||
trust_remote_code: bool = False | ||
quantization: Optional[str] = None | ||
revision: Optional[str] = None | ||
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seed: int = 0 | ||
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extra_kwargs: Optional[RuntimeParameter[Dict[str, Any]]] = Field( | ||
default_factory=dict, | ||
description="Additional dictionary of keyword arguments that will be passed to the" | ||
" `Engine` class of `sglang` library. See all the supported arguments at: " | ||
"https://github.com/sgl-project/sglang/blob/main/python/sglang/srt/entrypoints/engine.py", | ||
) | ||
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_model: "Engine" = PrivateAttr(None) | ||
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def load(self) -> None: | ||
"""Loads the `sglang` model using either the path or the Hugging Face Hub repository id.""" | ||
super().load() | ||
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CudaDevicePlacementMixin.load(self) | ||
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try: | ||
from sglang import Engine | ||
except ImportError as err: | ||
raise ImportError( | ||
"sglang is not installed. Please install it with sglang document https://docs.sglang.ai/start/install.html." | ||
) from err | ||
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self._model = Engine( | ||
model_path=self.model, | ||
dtype=self.dtype, | ||
trust_remote_code=self.trust_remote_code, | ||
quantization=self.quantization, | ||
revision=self.revision, | ||
random_seed=self.seed, | ||
**self.extra_kwargs, # type: ignore | ||
) | ||
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def unload(self) -> None: | ||
"""Unloads the `SGLang` model.""" | ||
self._model = None | ||
CudaDevicePlacementMixin.unload(self) | ||
super().unload() | ||
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@property | ||
def model_name(self) -> str: | ||
"""Returns the name of the model.""" | ||
return self.model | ||
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def encode(self, inputs: List[str]) -> List[List[Union[int, float]]]: | ||
"""Generates embeddings for the provided inputs. | ||
Args: | ||
inputs: a list of texts for which an embedding has to be generated. | ||
Returns: | ||
The generated embeddings. | ||
""" | ||
return [output["embedding"] for output in self._model.encode(inputs)] |
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