code: import lancedb
  import uuid
  from datetime import datetime
  from tqdm import tqdm
  from typing import Optional, List, Iterator, Dict
  
  from memgpt.config import MemGPTConfig
  from memgpt.agent_store.storage import StorageConnector, TableType
  from memgpt.config import AgentConfig, MemGPTConfig
  from memgpt.constants import MEMGPT_DIR
  from memgpt.utils import printd
  from memgpt.data_types import Record, Message, Passage, Source
  
  from datetime import datetime
  
  from lancedb.pydantic import Vector, LanceModel
  
  """ Initial implementation - not complete """
  
  
  def get_db_model(table_name: str, table_type: TableType):
      config = MemGPTConfig.load()
  
      if table_type == TableType.ARCHIVAL_MEMORY or table_type == TableType.PASSAGES:
          # create schema for archival memory
          class PassageModel(LanceModel):
              """Defines data model for storing Passages (consisting of text, embedding)"""
  
              id: uuid.UUID
              user_id: str
              text: str
              doc_id: str
              agent_id: str
              data_source: str
              embedding: Vector(config.embedding_dim)
              metadata_: Dict
  
              def __repr__(self):
                  return f"<Passage(passage_id='{self.id}', text='{self.text}', embedding='{self.embedding})>"
  
              def to_record(self):
                  return Passage(
                      text=self.text,
                      embedding=self.embedding,
                      doc_id=self.doc_id,
                      user_id=self.user_id,
                      id=self.id,
                      data_source=self.data_source,
                      agent_id=self.agent_id,
                      metadata=self.metadata_,
                  )
  
          return PassageModel
      elif table_type == TableType.RECALL_MEMORY:
  
          class MessageModel(LanceModel):
              """Defines data model for storing Message objects"""
  
              __abstract__ = True  # this line is necessary
  
              # Assuming message_id is the primary key
              id: uuid.UUID
              user_id: str
              agent_id: str
  
              # openai info
              role: str
              text: str
              model: str
              user: str
  
              # function info
              function_name: str
              function_args: str
              function_response: str
  
              embedding = Vector(config.embedding_dim)
  
              # Add a datetime column, with default value as the current time
              created_at = datetime
  
              def __repr__(self):
                  return f"<Message(message_id='{self.id}', text='{self.text}', embedding='{self.embedding})>"
  
              def to_record(self):
                  return Message(
                      user_id=self.user_id,
                      agent_id=self.agent_id,
                      role=self.role,
                      name=self.name,
                      text=self.text,
                      model=self.model,
                      function_name=self.function_name,
                      function_args=self.function_args,
                      function_response=self.function_response,
                      embedding=self.embedding,
                      created_at=self.created_at,
                      id=self.id,
                  )
  
          """Create database model for table_name"""
          return MessageModel
      elif table_type == TableType.DATA_SOURCES:
  
          class SourceModel(LanceModel):
              """Defines data model for storing Passages (consisting of text, embedding)"""
  
              # Assuming passage_id is the primary key
              id: uuid.UUID
              user_id: str
              name: str
              created_at: datetime
  
              def __repr__(self):
                  return f"<Source(passage_id='{self.id}', name='{self.name}')>"
  
              def to_record(self):
                  return Source(id=self.id, user_id=self.user_id, name=self.name, created_at=self.created_at)
  
          """Create database model for table_name"""
          return SourceModel
      else:
          raise ValueError(f"Table type {table_type} not implemented")
  
  
  class LanceDBConnector(StorageConnector):
      """Storage via LanceDB"""
  
      # TODO: this should probably eventually be moved into a parent DB class
  
      def __init__(self, name: Optional[str] = None, agent_config: Optional[AgentConfig] = None):
          # TODO
          pass
  
      def generate_where_filter(self, filters: Dict) -> str:
          where_filters = []
          for key, value in filters.items():
              where_filters.append(f"{key}={value}")
          return where_filters.join(" AND ")
  
      @abstractmethod
      def get_all_paginated(self, filters: Optional[Dict] = {}, page_size: Optional[int] = 1000) -> Iterator[List[Record]]:
          # TODO
          pass
  
      @abstractmethod
      def get_all(self, filters: Optional[Dict] = {}, limit=10) -> List[Record]:
          # TODO
          pass
  
      @abstractmethod
      def get(self, id: str) -> Optional[Record]:
          # TODO
          pass
  
      @abstractmethod
      def size(self, filters: Optional[Dict] = {}) -> int:
          # TODO
          pass
  
      @abstractmethod
      def insert(self, record: Record):
          # TODO
          pass
  
      @abstractmethod
      def insert_many(self, records: List[Record], show_progress=False):
          # TODO
          pass
  
      @abstractmethod
      def query(self, query: str, query_vec: List[float], top_k: int = 10, filters: Optional[Dict] = {}) -> List[Record]:
          # TODO
          pass
  
      @abstractmethod
      def query_date(self, start_date, end_date):
          # TODO
          pass
  
      @abstractmethod
      def query_text(self, query):
          # TODO
          pass
  
      @abstractmethod
      def delete_table(self):
          # TODO
          pass
  
      @abstractmethod
      def delete(self, filters: Optional[Dict] = {}):
          # TODO
          pass
  
      @abstractmethod
      def save(self):
          # TODO
          pass
  
apis: lancedb.pydantic.Vector
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