# This file was auto-generated by Fern from our API Definition.

import typing

import pydantic
from ..core.pydantic_utilities import IS_PYDANTIC_V2, UniversalBaseModel


class StructuredIndexingToolParameters(UniversalBaseModel):
    """
    LLM-exposed parameters for the structured indexing tool that indexes documents into the Vectara platform and can be filled in during execution.
    """

    corpus_key: typing.Optional[str] = pydantic.Field(default=None)
    """
    The key identifying the target corpus for document indexing. If not provided, will be filled in by the LLM.
    """

    document_id: typing.Optional[str] = pydantic.Field(default=None)
    """
    The unique identifier for the document within the corpus, preferably human readable IDs.
    """

    title: typing.Optional[str] = pydantic.Field(default=None)
    """
    The title of the document being indexed.
    """

    description: typing.Optional[str] = pydantic.Field(default=None)
    """
    A brief description or summary of the document content.
    """

    metadata: typing.Optional[typing.Dict[str, typing.Optional[typing.Any]]] = pydantic.Field(default=None)
    """
    The metadata key-value pairs to associate with the document. If present, this gets merged with existing artifact metadata.
    """

    document: typing.Optional[typing.Dict[str, typing.Optional[typing.Any]]] = pydantic.Field(default=None)
    """
    The structured document to index with full hierarchical content.
    """

    if IS_PYDANTIC_V2:
        model_config: typing.ClassVar[pydantic.ConfigDict] = pydantic.ConfigDict(extra="allow", frozen=True)  # type: ignore # Pydantic v2
    else:

        class Config:
            frozen = True
            smart_union = True
            extra = pydantic.Extra.allow
