class_docstr: Knowledge base table interface
  Handlers requests to KB table and modifies data in linked vector db table
class_docstr_tok: ["Knowledge","base","table","interface","Handlers","requests","to","KB","table","and","modifies","data","in","linked","vector","db","table"]
docstr: Converts string to embeddings
  :param content: input string
  :return: embeddings
docstr_tok: ["Converts","string","to","embeddings",":","param","content",":","input","string",":","return",":","embeddings"]
code: def _content_to_embeddings(self, content: str) -> List[float]:
      """
      Converts string to embeddings
      :param content: input string
      :return: embeddings
      """
      df = pd.DataFrame([[content]], columns=[TableField.CONTENT.value])
      res = self._df_to_embeddings(df)
      return res[TableField.EMBEDDINGS.value][0]
  
imports: import copy
  from typing import List
  import pandas
  import mindsdb_sql.planner.utils
  from mindsdb_sql.parser.ast import BinaryOperation, Constant, Identifier, Select, Update, Delete, Star
  from mindsdb_sql.parser.dialects.mindsdb import CreatePredictor
  import mindsdb.interfaces.storage.db
  from mindsdb.integrations.libs.vectordatabase_handler import TableField
  from mindsdb.utilities.exception import EntityExistsError, EntityNotExistsError
label_desc: Use image node_id 10 for calling the KnowledgeBaseTable obj's underlying member method code with example usage: obj._content_to_embeddings(content) and returns: res