all values and keyscluster_data    {'ids': ['578c6d24-3763-11ee-a8ab-b7b7b34f99ba',      '578c6d25-3763-11ee-a8ab-b7b7b34f99ba',      'fb2fc7d8-3762-11ee-a8ab-b7b7b34f99ba',      'fb2fc7d9-3762-11ee-a8ab-b7b7b34f99ba',      '6b40881a-3762-11ee-a8ab-b7b7b34f99ba',      '6b40881b-3762-11ee-a8ab-b7b7b34f99ba',      '581e691e-3762-11ee-a8ab-b7b7b34f99ba',      '581e691f-3762-11ee-a8ab-b7b7b34f99ba'],     'embeddings': None,     'metadatas': [{}, {}, {}, {}, {}, {}, {}, {}],     'documents': ['hello bagel',      'this is langchain',      'hello bagel',      'this is langchain',      'hello bagel',      'this is langchain',      'hello bagel',      'this is langchain']}cluster.delete_cluster()Create cluster with metadata & filter using metadata‚Äãtexts = ["hello bagel", "this is langchain"]metadatas = [{"source": "notion"}, {"source": "google"}]cluster = Bagel.from_texts(cluster_name="testing", texts=texts, metadatas=metadatas)cluster.similarity_search_with_score("hello bagel", where={"source": "notion"})    [(Document(page_content='hello bagel', metadata={'source': 'notion'}), 0.0)]# delete the clustercluster.delete_cluster()PreviousAzure Cognitive SearchNextCassandraInstallation and SetupCreate VectorStore from textsCreate VectorStore from docsGet all text/doc from ClusterCreate cluster with metadata & filter using metadataCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.
BagelDB (Open Vector Database for AI), is like GitHub for AI data.
BagelDB (Open Vector Database for AI), is like GitHub for AI data. ->: all values and keyscluster_data    {'ids': ['578c6d24-3763-11ee-a8ab-b7b7b34f99ba',      '578c6d25-3763-11ee-a8ab-b7b7b34f99ba',      'fb2fc7d8-3762-11ee-a8ab-b7b7b34f99ba',      'fb2fc7d9-3762-11ee-a8ab-b7b7b34f99ba',      '6b40881a-3762-11ee-a8ab-b7b7b34f99ba',      '6b40881b-3762-11ee-a8ab-b7b7b34f99ba',      '581e691e-3762-11ee-a8ab-b7b7b34f99ba',      '581e691f-3762-11ee-a8ab-b7b7b34f99ba'],     'embeddings': None,     'metadatas': [{}, {}, {}, {}, {}, {}, {}, {}],     'documents': ['hello bagel',      'this is langchain',      'hello bagel',      'this is langchain',      'hello bagel',      'this is langchain',      'hello bagel',      'this is langchain']}cluster.delete_cluster()Create cluster with metadata & filter using metadata‚Äãtexts = ["hello bagel", "this is langchain"]metadatas = [{"source": "notion"}, {"source": "google"}]cluster = Bagel.from_texts(cluster_name="testing", texts=texts, metadatas=metadatas)cluster.similarity_search_with_score("hello bagel", where={"source": "notion"})    [(Document(page_content='hello bagel', metadata={'source': 'notion'}), 0.0)]# delete the clustercluster.delete_cluster()PreviousAzure Cognitive SearchNextCassandraInstallation and SetupCreate VectorStore from textsCreate VectorStore from docsGet all text/doc from ClusterCreate cluster with metadata & filter using metadataCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.