text: can add filters on text key, or any of the metadata fields. Note: Since Rockset stores each metadata field as a separate column internally, these filters are much faster than other vector databases which store all metadata as a single JSON.For eg, to find all texts NOT containing the substring "and", you can use the following code:output = docsearch.similarity_search_with_relevance_scores(    query,    4,    RocksetDB.DistanceFunction.COSINE_SIM,    where_str="{} NOT LIKE '%citizens%'".format(TEXT_KEY),)print("output length:", len(output))for d, dist in output:    print(dist, d.metadata, d.page_content[:20] + "...")### output length: 4# 0.7651359650263554 {'source': '../../../state_of_the_union.txt'} Madam Speaker, Madam...# 0.7486265516824893 {'source': '../../../state_of_the_union.txt'} And Iâ€™m taking robus...# 0.7469625542348115 {'source': '../../../state_of_the_union.txt'} And so many families...# 0.7344177777547739 {'source': '../../../state_of_the_union.txt'} We see the unity amo...3. [Optional] Drop all inserted documentsâ€‹In order to delete texts from the Rockset collection, you need to know the unique ID associated with each document inside Rockset. These ids can either be supplied directly by the user while inserting the texts (in the RocksetDB.add_texts() function), else Rockset will generate a unique ID or each document. Either way, Rockset.add_texts() returns the ids for the inserted documents.To delete these docs, simply use the RocksetDB.delete_texts() function.docsearch.delete_texts(ids)Congratulations!â€‹Voila! In this example you successfuly created a Rockset