= CubeSemanticLoader(api_url, api_token)documents = loader.load()Returns a list of documents with the following attributes:page_contentmetadatatable_namecolumn_namecolumn_data_typecolumn_titlecolumn_descriptioncolumn_valuescube_data_obj_type# Given string containing page contentpage_content = 'Users View City, None'# Given dictionary containing metadatametadata = {    'table_name': 'users_view',    'column_name': 'users_view.city',    'column_data_type': 'string',    'column_title': 'Users View City',    'column_description': 'None',    'column_member_type': 'dimension',    'column_values': [        'Austin',        'Chicago',        'Los Angeles',        'Mountain View',        'New York',        'Palo Alto',        'San Francisco',        'Seattle'    ],    'cube_data_obj_type': 'view'}PreviousCSVNextDatadog LogsAbout CubeExampleCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.
This notebook demonstrates the process of retrieving Cube's data model metadata in a format suitable for passing to LLMs as embeddings, thereby enhancing contextual information.
This notebook demonstrates the process of retrieving Cube's data model metadata in a format suitable for passing to LLMs as embeddings, thereby enhancing contextual information. ->: = CubeSemanticLoader(api_url, api_token)documents = loader.load()Returns a list of documents with the following attributes:page_contentmetadatatable_namecolumn_namecolumn_data_typecolumn_titlecolumn_descriptioncolumn_valuescube_data_obj_type# Given string containing page contentpage_content = 'Users View City, None'# Given dictionary containing metadatametadata = {    'table_name': 'users_view',    'column_name': 'users_view.city',    'column_data_type': 'string',    'column_title': 'Users View City',    'column_description': 'None',    'column_member_type': 'dimension',    'column_values': [        'Austin',        'Chicago',        'Los Angeles',        'Mountain View',        'New York',        'Palo Alto',        'San Francisco',        'Seattle'    ],    'cube_data_obj_type': 'view'}PreviousCSVNextDatadog LogsAbout CubeExampleCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.