docs = loader.load_and_split(text_splitor) return docs def _load_from_url(self, url): """Load data from url address""" pass def query(self, q): """Query similar doc from Vector """ vector_store = self.init_vector_store() docs = vector_store.similarity_search_with_score(q, k=...
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通过URL读取网页数据 除了从youtube中加载数据,Langchain还可以通过url来加载web网页数据,下面我们看一个例子: fromlangchain.document_loadersimportWebBaseLoaderurl="https://mp.weixin.qq.com/s/RhzHa1oMd0WHk0JamdfVRA"#创建webLoaderloader=WebBaseLoader(url)#获取文档docs=loader.load()#查看文档内容text=do...
from langchain.document_loadersimportMathpixPDFLoader loader=MathpixPDFLoader("./pdf_files/my_algebra.pdf")data=loader.load() PyMuPDF加载器[24]是另一个例子,它与PyPDF执行相同的功能,但速度更快。 在LangChain文档中找到PDF加载器的完整列表[25]。
from langchain_community.document_loaders.csv_loader import CSVLoader loader = CSVLoader(file_path='./example_data/mlb_teams_2012.csv') data = loader.load() print(data) 打印结果: [Document(page_content='Team: Nationals\n"Payroll (millions)": 81.34\n"Wins": 98', lookup_str='', metadata...
from langchain.output_parsers import PydanticOutputParserfrom pydantic import BaseModel, Field, validatorfrom typing import Listmodel_name = 'text-davinci-003'temperature = 0.0model = OpenAI(model_name=model_name, temperature=temperature) # Define your desired data structure.class Joke(BaseModel):set...
(self.url_database)) logger.info(f"New URLs to load: {new_urls}") # Load, split, and add new urls to vectorstore if new_urls: loader = AsyncHtmlLoader(new_urls, ignore_load_errors=True) html2text = Html2TextTransformer() logger.info("Indexing new urls...") docs = loader.load...
documents变量将包含加载的文档,可以访问这些文档以进行进一步处理。每个文档由page_content(文档的文本内容)和metadata(关联元数据,如来源 URL 或标题)组成。同样,我们可以从维基百科中加载文档: from langchain.document_loaders import WikipediaLoaderloader = WikipediaLoader("LangChain")documents = loader.load() ...
fromlangchain.agentsimportload_toolsfromlangchain.agentsimportinitialize_agentfromlangchain.agentsimportAgentTypefromlangchain.chat_modelsimportChatOpenAIfromlangchain.llmsimportOpenAI # First, let's load the language model we're going to use to control the agent.chat = ChatOpenAI(temperature=0) ...
fromlangchain.agentsimportload_toolsfromlangchain.agentsimportinitialize_agentfromlangchain.agentsimportAgentTypefromlangchain.chat_modelsimportChatOpenAIfromlangchain.llmsimportOpenAI # First, let's load the language model we're going to use to control the agent.chat = ChatOpenAI(temperature=0) ...