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vllm.config.structured_outputs

Classes:

StructuredOutputsConfig

Dataclass which contains structured outputs config for the engine.

Methods:

  • compute_hash

    WARNING: Whenever a new field is added to this config,

Attributes:

Source code in vllm/config/structured_outputs.py
@config
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_any_whitespace: bool = False
    """If `True`, json output will always be compact without any whitespace.
    If `False`, the model may generate whitespace between JSON fields,
    which is still valid JSON. 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."""
    reasoning_parser_plugin: str = ""
    """Path to a dynamically reasoning parser plugin that can be dynamically
    loaded and registered."""
    enable_in_reasoning: bool = False
    """Whether to use structured input for reasoning."""

    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 = safe_hash(str(factors).encode(), usedforsecurity=False).hexdigest()
        return hash_str

    @model_validator(mode="after")
    def _validate_structured_output_config(self) -> 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."
            )
        return self

backend = 'auto' class-attribute instance-attribute

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_additional_properties = False class-attribute instance-attribute

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.

disable_any_whitespace = False class-attribute instance-attribute

If True, json output will always be compact without any whitespace. If False, the model may generate whitespace between JSON fields, which is still valid JSON. This is only supported for xgrammar and guidance backends.

enable_in_reasoning = False class-attribute instance-attribute

Whether to use structured input for reasoning.

reasoning_parser = '' class-attribute instance-attribute

Select the reasoning parser depending on the model that you're using. This is used to parse the reasoning content into OpenAI API format.

reasoning_parser_plugin = '' class-attribute instance-attribute

Path to a dynamically reasoning parser plugin that can be dynamically loaded and registered.

compute_hash()

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.

Source code in vllm/config/structured_outputs.py
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 = safe_hash(str(factors).encode(), usedforsecurity=False).hexdigest()
    return hash_str