Document(page_content='Team: Rangers\n"Payroll (millions)": 120.51\n"Wins": 93', lookup_str='', metadata={'source': './example_data/mlb_teams_2012.csv', 'row': 6}, lookup_index=0), Document(page_content='Team: Orioles\n"Payroll (millions)": 81.43\n"Wins": 93', lookup_str='...
from langchain.document_loaders import UnstructuredWordDocumentLoader loader = UnstructuredWordDocumentLoader("example_data/fake.docx") data = loader.load() data LangChain 0.0.148from langchain.document_loaders import UnstructuredWordDocumentLoader loader = UnstructuredWordDocumentLoader("example_data/fake.d...
defload_word(directory_path):data=[]forfilenameinos.listdir(directory_path):# check if the file is a doc or docx file# 检查所有doc以及docx后缀的文件iffilename.endswith(".doc")orfilename.endswith(".docx"):# langchain自带功能,加载word文档loader=UnstructuredWordDocumentLoader(f'{directory_path...
langchain提供了很多文档加载的类,以便进行不同的文件加载,这些类都通过 langchain.document_loaders 引入。 例如:UnstructuredFileLoader(txt文件读取)、UnstructuredFileLoader(word文件读取)、MarkdownTextSplitter(markdown文件读取)、UnstructuredPDFLoader(PDF文件读取) 本文准备了四种格式的文件进行加载测试,文件默认放在do...
API_KEY']="apiKey"#Init loaderloader=PyPDFLoader(filePath)#Load documentdocuments=loader.load()...
documents = loader.load() 1. 2. 3. 4. 特别说明:使用 Markdown 加载器需要安装unstructured包,它能够智能识别文档结构并提取内容。 3. Office 文档加载器 from langchain_community.document_loaders import ( UnstructuredWordDocumentLoader, UnstructuredPowerPointLoader, ...
System Info I'm trying to load multiple doc files, it is not loading, below is the code txt_loader = DirectoryLoader(folder_path, glob="./*.docx", loader_cls=UnstructuredWordDocumentLoader) txt_documents = txt_loader.load() I have tried ...
tools from flask import Flask need_embedding = False persist_directory = 'chroma' if need_embedding: # 加载Word文档并提取文本 # loader = UnstructuredWordDocumentLoader("./short.docx") loader = Docx2txtLoader("./short.docx") documents = loader.load() # 将文本分割成块 text_splitter = ...
# 加载Word文档并提取文本 # loader = UnstructuredWordDocumentLoader("./short.docx") loader = Docx2txtLoader("./short.docx") documents = loader.load() # 将文本分割成块 text_splitter = CharacterTextSplitter(chunk_size=2000, chunk_overlap=500) texts = text_splitter.split_documents(documents) #...
load_and_split(textsplitter) step2:解析txt/pdf等原始文件,不同类型的文件有不同种类多Loader,比如txt文件有TextLoader,具体load()实现如下: def load(self) -> List[Document]: """Load from file path.""" text = "" try: with open(self.file_path, encoding=self.encoding) as f: text = f....