LarkSuite (飞书)
LarkSuite 是字节跳动开发的企业协作平台。
本笔记本介绍如何从 LarkSuite
REST API 加载数据,并将其转换为可以被 LangChain 处理的格式,同时提供文本摘要的示例用法。
LarkSuite API 需要访问令牌(tenant_access_token 或 user_access_token),请查看 LarkSuite 开放平台文档 以获取 API 详细信息。
<!--IMPORTS:[{"imported": "LarkSuiteDocLoader", "source": "langchain_community.document_loaders.larksuite", "docs": "https://python.langchain.com/api_reference/community/document_loaders/langchain_community.document_loaders.larksuite.LarkSuiteDocLoader.html", "title": "LarkSuite (FeiShu)"}, {"imported": "LarkSuiteWikiLoader", "source": "langchain_community.document_loaders.larksuite", "docs": "https://python.langchain.com/api_reference/community/document_loaders/langchain_community.document_loaders.larksuite.LarkSuiteWikiLoader.html", "title": "LarkSuite (FeiShu)"}]-->
from getpass import getpass
from langchain_community.document_loaders.larksuite import (
LarkSuiteDocLoader,
LarkSuiteWikiLoader,
)
DOMAIN = input("larksuite domain")
ACCESS_TOKEN = getpass("larksuite tenant_access_token or user_access_token")
DOCUMENT_ID = input("larksuite document id")
从文档加载
from pprint import 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'})]
从维基加载
from pprint import 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'})]
<!--IMPORTS:[{"imported": "load_summarize_chain", "source": "langchain.chains.summarize", "docs": "https://python.langchain.com/api_reference/langchain/chains/langchain.chains.summarize.chain.load_summarize_chain.html", "title": "LarkSuite (FeiShu)"}, {"imported": "FakeListLLM", "source": "langchain_community.llms.fake", "docs": "https://python.langchain.com/api_reference/community/llms/langchain_community.llms.fake.FakeListLLM.html", "title": "LarkSuite (FeiShu)"}]-->
# see https://python.langchain.com/docs/use_cases/summarization for more details
from langchain.chains.summarize import load_summarize_chain
from langchain_community.llms.fake import FakeListLLM
llm = FakeListLLM()
chain = load_summarize_chain(llm, chain_type="map_reduce")
chain.run(docs)