# coding: utf-8

"""
    Mixpeek API

    This is the Mixpeek API, providing access to various endpoints for data processing and retrieval.

    The version of the OpenAPI document: 1.3.0
    Contact: info@mixpeek.com
    Generated by OpenAPI Generator (https://openapi-generator.tech)

    Do not edit the class manually.
"""  # noqa: E501


from __future__ import annotations
import pprint
import re  # noqa: F401
import json

from pydantic import BaseModel, ConfigDict, Field, StrictStr
from typing import Any, ClassVar, Dict, List, Optional
from typing_extensions import Annotated
from mixpeek.models.logical_operator_input import LogicalOperatorInput
from typing import Optional, Set
from typing_extensions import Self

class BatchDeleteDocumentsRequest(BaseModel):
    """
    Request model for batch deleting multiple documents by explicit IDs or filters.  Supports TWO modes: 1. Explicit IDs mode: Provide 'document_ids' array 2. Filter mode: Provide 'filters' to delete all matching documents  Use Cases:     - Delete 5 specific documents in one API call     - Delete all documents matching criteria     - Bulk cleanup operations  Requirements:     - EITHER 'document_ids' OR 'filters' must be provided     - NOT BOTH modes simultaneously
    """ # noqa: E501
    document_ids: Optional[Annotated[List[StrictStr], Field(min_length=1, max_length=1000)]] = Field(default=None, description="OPTIONAL. List of document IDs to delete. Use this mode when you know exact document IDs to delete. Mutually exclusive with filters mode. Maximum 1000 documents per batch request.")
    filters: Optional[LogicalOperatorInput] = Field(default=None, description="OPTIONAL. Filter conditions to match documents for deletion. Mutually exclusive with 'document_ids' array. If provided, deletes ALL documents matching the filters. Use with caution - can delete many documents at once.")
    __properties: ClassVar[List[str]] = ["document_ids", "filters"]

    model_config = ConfigDict(
        populate_by_name=True,
        validate_assignment=True,
        protected_namespaces=(),
    )


    def to_str(self) -> str:
        """Returns the string representation of the model using alias"""
        return pprint.pformat(self.model_dump(by_alias=True))

    def to_json(self) -> str:
        """Returns the JSON representation of the model using alias"""
        # TODO: pydantic v2: use .model_dump_json(by_alias=True, exclude_unset=True) instead
        return json.dumps(self.to_dict())

    @classmethod
    def from_json(cls, json_str: str) -> Optional[Self]:
        """Create an instance of BatchDeleteDocumentsRequest from a JSON string"""
        return cls.from_dict(json.loads(json_str))

    def to_dict(self) -> Dict[str, Any]:
        """Return the dictionary representation of the model using alias.

        This has the following differences from calling pydantic's
        `self.model_dump(by_alias=True)`:

        * `None` is only added to the output dict for nullable fields that
          were set at model initialization. Other fields with value `None`
          are ignored.
        """
        excluded_fields: Set[str] = set([
        ])

        _dict = self.model_dump(
            by_alias=True,
            exclude=excluded_fields,
            exclude_none=True,
        )
        # override the default output from pydantic by calling `to_dict()` of filters
        if self.filters:
            _dict['filters'] = self.filters.to_dict()
        return _dict

    @classmethod
    def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
        """Create an instance of BatchDeleteDocumentsRequest from a dict"""
        if obj is None:
            return None

        if not isinstance(obj, dict):
            return cls.model_validate(obj)

        _obj = cls.model_validate({
            "document_ids": obj.get("document_ids"),
            "filters": LogicalOperatorInput.from_dict(obj["filters"]) if obj.get("filters") is not None else None
        })
        return _obj


