a few more complex queries that utilize the full power of OpenSearch.retriever.get_relevant_documents("what animated or comedy movies have been released in the last 30 years about animated toys?")    query='animated toys' filter=Operation(operator=<Operator.AND: 'and'>, arguments=[Operation(operator=<Operator.OR: 'or'>, arguments=[Comparison(comparator=<Comparator.EQ: 'eq'>, attribute='genre', value='animated'), Comparison(comparator=<Comparator.EQ: 'eq'>, attribute='genre', value='comedy')]), Comparison(comparator=<Comparator.GTE: 'gte'>, attribute='year', value=1990)]) limit=None    [Document(page_content='Toys come alive and have a blast doing so', metadata={'year': 1995, 'genre': 'animated'})]vectorstore.client.indices.delete(index="opensearch-self-query-demo")    {'acknowledged': True}PreviousMyScaleNextPineconeCreating an OpenSearch vector storeCreating our self-querying retrieverTesting it outFilter kComplex queries in Action!CommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.
OpenSearch is a scalable, flexible, and extensible open-source software suite for search, analytics, and observability applications licensed under Apache 2.0. OpenSearch is a distributed search and analytics engine based on Apache Lucene.
OpenSearch is a scalable, flexible, and extensible open-source software suite for search, analytics, and observability applications licensed under Apache 2.0. OpenSearch is a distributed search and analytics engine based on Apache Lucene. ->: a few more complex queries that utilize the full power of OpenSearch.retriever.get_relevant_documents("what animated or comedy movies have been released in the last 30 years about animated toys?")    query='animated toys' filter=Operation(operator=<Operator.AND: 'and'>, arguments=[Operation(operator=<Operator.OR: 'or'>, arguments=[Comparison(comparator=<Comparator.EQ: 'eq'>, attribute='genre', value='animated'), Comparison(comparator=<Comparator.EQ: 'eq'>, attribute='genre', value='comedy')]), Comparison(comparator=<Comparator.GTE: 'gte'>, attribute='year', value=1990)]) limit=None    [Document(page_content='Toys come alive and have a blast doing so', metadata={'year': 1995, 'genre': 'animated'})]vectorstore.client.indices.delete(index="opensearch-self-query-demo")    {'acknowledged': True}PreviousMyScaleNextPineconeCreating an OpenSearch vector storeCreating our self-querying retrieverTesting it outFilter kComplex queries in Action!CommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.