I have read that delta live tables will keep a history of 7 days. However after creating a streaming live table and using the dlt.apply_changes function. With this code

def run_pipeline(table_name,keys,sequence_by):
    lower_table_name = table_name.lower()
    @dlt.view(name = f"{lower_table_name}_schema",
                     comment= "Test")
    def create_raw_schema():
        return(spark.read.format("parquet")
              .option("inferschema", True)
              .load(f"s3://mybucket/test/dbo/{table_name}/")
              .limit(10)
              )
 
    #creating hist table
    @dlt.table(name=f"s{lower_table_name}_hist",
                   comment = "test")
    def create_hist_table():
      return (
        spark.readStream.format("cloudFiles")
          .option("cloudFiles.format", "parquet")
          .schema(dlt.read(f"{lower_table_name}_schema").schema)
          .load(f"s3://mybucket/test/dbo/{table_name}/")
      )
 
    #creating current table
    dlt.create_streaming_live_table(
        name = f"{lower_table_name}",
        path = f"s3://mybucket/test/cdc/{table_name}__ct/")
    
    dlt.apply_changes(
        target = f"{lower_table_name}",
        source = f"{lower_table_name}_hist",
        keys = keys,
        sequence_by = col(sequence_by)
    )

when I attempt to access any version history using

SELECT * FROM dlt.my_table TIMESTAMP AS OF "2022-10-10"

I get this message "Cannot time travel views."