vllm/vllm/config/structured_outputs.py
Harry Mellor 8ed039d527
Move StructuredOutputsConfig from config/__init__.py to config/structured_outputs.py (#25153)
Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
2025-09-18 11:24:27 +00:00

65 lines
2.8 KiB
Python

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