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65 lines
2.8 KiB
Python
65 lines
2.8 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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import hashlib
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from typing import Any, Literal
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from pydantic.dataclasses import dataclass
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from vllm.config.utils import config
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StructuredOutputsBackend = Literal["auto", "xgrammar", "guidance", "outlines",
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"lm-format-enforcer"]
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@config
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@dataclass
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class StructuredOutputsConfig:
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"""Dataclass which contains structured outputs config for the engine."""
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backend: StructuredOutputsBackend = "auto"
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"""Which engine will be used for structured outputs (e.g. JSON schema,
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regex, etc) by default. With "auto", we will make opinionated choices
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based on request contents and what the backend libraries currently support,
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so the behavior is subject to change in each release."""
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disable_fallback: bool = False
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"""If `True`, vLLM will not fallback to a different backend on error."""
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disable_any_whitespace: bool = False
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"""If `True`, the model will not generate any whitespace during structured
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outputs. This is only supported for xgrammar and guidance backends."""
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disable_additional_properties: bool = False
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"""If `True`, the `guidance` backend will not use `additionalProperties`
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in the JSON schema. This is only supported for the `guidance` backend and
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is used to better align its behaviour with `outlines` and `xgrammar`."""
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reasoning_parser: str = ""
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"""Select the reasoning parser depending on the model that you're using.
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This is used to parse the reasoning content into OpenAI API format."""
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def compute_hash(self) -> str:
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"""
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WARNING: Whenever a new field is added to this config,
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ensure that it is included in the factors list if
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it affects the computation graph.
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Provide a hash that uniquely identifies all the configs
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that affect the structure of the computation
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graph from input ids/embeddings to the final hidden states,
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excluding anything before input ids/embeddings and after
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the final hidden states.
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"""
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# no factors to consider.
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# this config will not affect the computation graph.
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factors: list[Any] = []
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hash_str = hashlib.md5(str(factors).encode(),
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usedforsecurity=False).hexdigest()
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return hash_str
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def __post_init__(self):
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if (self.disable_any_whitespace
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and self.backend not in ("xgrammar", "guidance")):
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raise ValueError("disable_any_whitespace is only supported for "
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"xgrammar and guidance backends.")
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if (self.disable_additional_properties and self.backend != "guidance"):
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raise ValueError("disable_additional_properties is only supported "
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"for the guidance backend.")
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