class_docstr: This handler handles connection and execution of the Pinecone statements.
class_docstr_tok: ["This","handler","handles","connection","and","execution","of","the","Pinecone","statements","."]
code: def __init__(self, name: str, **kwargs):
      super().__init__(name)
      self.MAX_FETCH_LIMIT = 10000
      self._connection_data = kwargs.get("connection_data")
      self._client_config = {
          "api_key": self._connection_data.get("api_key"),
          "environment": self._connection_data.get("environment"),
      }
      self._table_create_params = {
          "dimension": 8,
          "metric": "cosine",
          "pods": 1,
          "replicas": 1,
          "pod_type": "p1",
      }
      for key in self._table_create_params:
          if key in self._connection_data:
              self._table_create_params[key] = self._connection_data[
                  key
              ]
      self.is_connected = False
      self.connect()
  
imports: from collections import OrderedDict
  from typing import List, Optional
  import pinecone
  import pandas
  import ast
  from mindsdb.integrations.libs.const import HANDLER_CONNECTION_ARG_TYPE
  from mindsdb.integrations.libs.response import RESPONSE_TYPE
  from mindsdb.integrations.libs.response import HandlerResponse
  from mindsdb.integrations.libs.response import HandlerResponse
  from mindsdb.integrations.libs.response import HandlerStatusResponse
  from mindsdb.integrations.libs.vectordatabase_handler import FilterCondition, FilterOperator, TableField, VectorStoreHandler
  from mindsdb.utilities import log
label_desc: Use image node_id 1 to create a new PineconeHandler object from inherited base classes: VectorStoreHandler with example: obj = PineconeHandler(name)