is an enterprise collaboration platform developed by ByteDance.This notebook covers how to load data from the LarkSuite REST API into a format that can be ingested into LangChain, along with example usage for text summarization.The LarkSuite API requires an access token (tenant_access_token or user_access_token), checkout LarkSuite open platform document for API details.from getpass import getpassfrom langchain.document_loaders.larksuite import LarkSuiteDocLoaderDOMAIN = input("larksuite domain")ACCESS_TOKEN = getpass("larksuite tenant_access_token or user_access_token")DOCUMENT_ID = input("larksuite document id")from pprint import pprintlarksuite_loader = LarkSuiteDocLoader(DOMAIN, ACCESS_TOKEN, DOCUMENT_ID)docs = larksuite_loader.load()pprint(docs)    [Document(page_content='Test Doc\nThis is a Test Doc\n\n1\n2\n3\n\n', metadata={'document_id': 'V76kdbd2HoBbYJxdiNNccajunPf', 'revision_id': 11, 'title': 'Test Doc'})]# see https://python.langchain.com/docs/use_cases/summarization for more detailsfrom langchain.chains.summarize import load_summarize_chainchain = load_summarize_chain(llm, chain_type="map_reduce")chain.run(docs)PreviousJupyter NotebookNextMastodonCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.
LarkSuite is an enterprise collaboration platform developed by ByteDance.
LarkSuite is an enterprise collaboration platform developed by ByteDance. ->: is an enterprise collaboration platform developed by ByteDance.This notebook covers how to load data from the LarkSuite REST API into a format that can be ingested into LangChain, along with example usage for text summarization.The LarkSuite API requires an access token (tenant_access_token or user_access_token), checkout LarkSuite open platform document for API details.from getpass import getpassfrom langchain.document_loaders.larksuite import LarkSuiteDocLoaderDOMAIN = input("larksuite domain")ACCESS_TOKEN = getpass("larksuite tenant_access_token or user_access_token")DOCUMENT_ID = input("larksuite document id")from pprint import pprintlarksuite_loader = LarkSuiteDocLoader(DOMAIN, ACCESS_TOKEN, DOCUMENT_ID)docs = larksuite_loader.load()pprint(docs)    [Document(page_content='Test Doc\nThis is a Test Doc\n\n1\n2\n3\n\n', metadata={'document_id': 'V76kdbd2HoBbYJxdiNNccajunPf', 'revision_id': 11, 'title': 'Test Doc'})]# see https://python.langchain.com/docs/use_cases/summarization for more detailsfrom langchain.chains.summarize import load_summarize_chainchain = load_summarize_chain(llm, chain_type="map_reduce")chain.run(docs)PreviousJupyter NotebookNextMastodonCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.