a President has is nominating someone to serve on the United States Supreme Court.         And I did that 4 days ago, when I nominated Circuit Court of Appeals Judge Ketanji Brown Jackson. One of our nation‚Äôs top legal minds, who will continue Justice Breyer‚Äôs legacy of excellence.Get connection info and data schema‚Äãprint(str(docsearch))Filtering‚ÄãYou can have direct access to myscale SQL where statement. You can write WHERE clause following standard SQL.NOTE: Please be aware of SQL injection, this interface must not be directly called by end-user.If you customized your column_map under your setting, you search with filter like this:from langchain.vectorstores import MyScale, MyScaleSettingsfrom langchain.document_loaders import TextLoaderloader = TextLoader("../../modules/state_of_the_union.txt")documents = loader.load()text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)docs = text_splitter.split_documents(documents)embeddings = OpenAIEmbeddings()for i, d in enumerate(docs):    d.metadata = {"doc_id": i}docsearch = MyScale.from_documents(docs, embeddings)    Inserting data...: 100%|‚ñà‚ñà‚ñà‚ñà‚ñà‚ñà‚ñà‚ñà‚ñà‚ñà| 42/42 [00:15<00:00,  2.68it/s]Similarity search with score‚ÄãThe returned distance score is cosine distance. Therefore, a lower score is better.meta = docsearch.metadata_columnoutput = docsearch.similarity_search_with_relevance_scores(    "What did the president say about Ketanji Brown Jackson?",    k=4,    where_str=f"{meta}.doc_id<10",)for d, dist in output:    print(dist, d.metadata, d.page_content[:20] + "...")    0.229655921459198 {'doc_id': 0} Madam Speaker, Madam...    0.24506962299346924 {'doc_id': 8} And so many families...    0.24786919355392456 {'doc_id': 1} Groups of citizens b...    0.24875116348266602 {'doc_id': 6} And I‚Äôm taking robus...Deleting your data‚ÄãYou can either drop the table with .drop() method or partially delete your data with .delete() method.# use directly a `where_str` to
MyScale is a cloud-based database optimized for AI applications and solutions, built on the open-source ClickHouse.
MyScale is a cloud-based database optimized for AI applications and solutions, built on the open-source ClickHouse. ->: a President has is nominating someone to serve on the United States Supreme Court.         And I did that 4 days ago, when I nominated Circuit Court of Appeals Judge Ketanji Brown Jackson. One of our nation‚Äôs top legal minds, who will continue Justice Breyer‚Äôs legacy of excellence.Get connection info and data schema‚Äãprint(str(docsearch))Filtering‚ÄãYou can have direct access to myscale SQL where statement. You can write WHERE clause following standard SQL.NOTE: Please be aware of SQL injection, this interface must not be directly called by end-user.If you customized your column_map under your setting, you search with filter like this:from langchain.vectorstores import MyScale, MyScaleSettingsfrom langchain.document_loaders import TextLoaderloader = TextLoader("../../modules/state_of_the_union.txt")documents = loader.load()text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)docs = text_splitter.split_documents(documents)embeddings = OpenAIEmbeddings()for i, d in enumerate(docs):    d.metadata = {"doc_id": i}docsearch = MyScale.from_documents(docs, embeddings)    Inserting data...: 100%|‚ñà‚ñà‚ñà‚ñà‚ñà‚ñà‚ñà‚ñà‚ñà‚ñà| 42/42 [00:15<00:00,  2.68it/s]Similarity search with score‚ÄãThe returned distance score is cosine distance. Therefore, a lower score is better.meta = docsearch.metadata_columnoutput = docsearch.similarity_search_with_relevance_scores(    "What did the president say about Ketanji Brown Jackson?",    k=4,    where_str=f"{meta}.doc_id<10",)for d, dist in output:    print(dist, d.metadata, d.page_content[:20] + "...")    0.229655921459198 {'doc_id': 0} Madam Speaker, Madam...    0.24506962299346924 {'doc_id': 8} And so many families...    0.24786919355392456 {'doc_id': 1} Groups of citizens b...    0.24875116348266602 {'doc_id': 6} And I‚Äôm taking robus...Deleting your data‚ÄãYou can either drop the table with .drop() method or partially delete your data with .delete() method.# use directly a `where_str` to