class_docstr: Operator that store vector in the Weaviate class.
  
  .. seealso::
      For more information on how to use this operator, take a look at the guide:
      :ref:`howto/operator:WeaviateIngestOperator`
  
  Operator that accepts input json or pandas dataframe to generate embeddings on or accepting provided
  custom vectors and store them in the Weaviate class.
  
  :param conn_id: The Weaviate connection.
  :param class_name: The Weaviate class to be used for storing the data objects into.
  :param input_data: The list of dicts or pandas dataframe representing Weaviate data objects to generate
      embeddings on (or provides custom vectors) and store them in the Weaviate class.
  :param input_json: (Deprecated) The JSON representing Weaviate data objects to generate embeddings on (or provides
      custom vectors) and store them in the Weaviate class.
  :param vector_col: key/column name in which the vectors are stored.
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code: def __init__(
      self,
      conn_id: str,
      class_name: str,
      input_json: list[dict[str, Any]] | pd.DataFrame | None = None,
      input_data: list[dict[str, Any]] | pd.DataFrame | None = None,
      vector_col: str = "Vector",
      uuid_column: str = "id",
      tenant: str | None = None,
      **kwargs: Any,
  ) -> None:
      self.batch_params = kwargs.pop("batch_params", {})
      self.hook_params = kwargs.pop("hook_params", {})
  
      super().__init__(**kwargs)
      self.class_name = class_name
      self.conn_id = conn_id
      self.vector_col = vector_col
      self.input_json = input_json
      self.uuid_column = uuid_column
      self.tenant = tenant
      if input_data is not None:
          self.input_data = input_data
      elif input_json is not None:
          warnings.warn(
              "Passing 'input_json' to WeaviateIngestOperator is deprecated and"
              " you should use 'input_data' instead",
              AirflowProviderDeprecationWarning,
          )
          self.input_data = input_json
      else:
          raise TypeError("Either input_json or input_data is required")
  
file_path: airflow/airflow/providers/weaviate/operators/weaviate.py
imports: from __future__ import annotations
  import warnings
  from functools import cached_property
  from typing import TYPE_CHECKING, Any, Sequence
  from airflow.exceptions import AirflowProviderDeprecationWarning
  from airflow.models import BaseOperator
  from airflow.providers.weaviate.hooks.weaviate import WeaviateHook
label_desc: Use image node_id 1 to create a new WeaviateIngestOperator object from inherited base classes: BaseOperator with example: obj = WeaviateIngestOperator(conn_id, class_name, input_json, input_data, vector_col, uuid_column, tenant)