53 lines
1.9 KiB
Python
53 lines
1.9 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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"""vLLM: a high-throughput and memory-efficient inference engine for LLMs"""
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# The version.py should be independent library, and we always import the
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# version library first. Such assumption is critical for some customization.
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from .version import __version__, __version_tuple__ # isort:skip
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# The environment variables override should be imported before any other
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# modules to ensure that the environment variables are set before any
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# other modules are imported.
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import vllm.env_override # isort:skip # noqa: F401
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from vllm.engine.arg_utils import AsyncEngineArgs, EngineArgs
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from vllm.engine.async_llm_engine import AsyncLLMEngine
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from vllm.engine.llm_engine import LLMEngine
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from vllm.entrypoints.llm import LLM
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from vllm.executor.ray_utils import initialize_ray_cluster
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from vllm.inputs import PromptType, TextPrompt, TokensPrompt
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from vllm.model_executor.models import ModelRegistry
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from vllm.outputs import (ClassificationOutput, ClassificationRequestOutput,
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CompletionOutput, EmbeddingOutput,
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EmbeddingRequestOutput, PoolingOutput,
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PoolingRequestOutput, RequestOutput, ScoringOutput,
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ScoringRequestOutput)
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from vllm.pooling_params import PoolingParams
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from vllm.sampling_params import SamplingParams
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__all__ = [
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"__version__",
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"__version_tuple__",
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"LLM",
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"ModelRegistry",
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"PromptType",
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"TextPrompt",
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"TokensPrompt",
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"SamplingParams",
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"RequestOutput",
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"CompletionOutput",
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"PoolingOutput",
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"PoolingRequestOutput",
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"EmbeddingOutput",
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"EmbeddingRequestOutput",
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"ClassificationOutput",
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"ClassificationRequestOutput",
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"ScoringOutput",
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"ScoringRequestOutput",
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"LLMEngine",
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"EngineArgs",
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"AsyncLLMEngine",
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"AsyncEngineArgs",
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"initialize_ray_cluster",
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"PoolingParams",
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]
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