LarkSuite (FeiShu)
LarkSuite is an enterprise collaboration platform developed by ByteDance.
This notebook covers how to load data from theLarkSuite 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), checkoutLarkSuite open platform document for API details.
from getpassimport getpass
from langchain_community.document_loaders.larksuiteimport(
LarkSuiteDocLoader,
LarkSuiteWikiLoader,
)
DOMAIN=input("larksuite domain")
ACCESS_TOKEN= getpass("larksuite tenant_access_token or user_access_token")
DOCUMENT_ID=input("larksuite document id")
API Reference:LarkSuiteDocLoader |LarkSuiteWikiLoader
Load From Document
from pprintimport pprint
larksuite_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'})]
Load From Wiki
from pprintimport pprint
DOCUMENT_ID=input("larksuite wiki id")
larksuite_loader= LarkSuiteWikiLoader(DOMAIN, ACCESS_TOKEN, DOCUMENT_ID)
docs= larksuite_loader.load()
pprint(docs)
[Document(page_content='Test doc\nThis is a test wiki doc.\n', metadata={'document_id': 'TxOKdtMWaoSTDLxYS4ZcdEI7nwc', 'revision_id': 15, 'title': 'Test doc'})]
# see https://python.langchain.com/docs/use_cases/summarization for more details
from langchain.chains.summarizeimport load_summarize_chain
from langchain_community.llms.fakeimport FakeListLLM
llm= FakeListLLM()
chain= load_summarize_chain(llm, chain_type="map_reduce")
chain.run(docs)
API Reference:load_summarize_chain |FakeListLLM
Related
- Document loaderconceptual guide
- Document loaderhow-to guides