TextLoader 是 LangChain 中用于加载文本文件的工具。让我详细解释它的功能和实现: 基本功能 fromlangchain.document_loadersimportTextLoaderclassTextLoader:def__init__(self,file_path:str,encoding:str='utf-8'):"""参数:file_path: 文本文件路径encoding: 文件编码,默认utf-8"""self.file_path=file_pathself...
接着,加载文档,将其分割成块,嵌入每个块并将其加载到向量存储中。 raw_documents = TextLoader("test_text.txt", encoding='utf-8').load() text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0) documents = text_splitter.split_documents(raw_documents) 注意:如果是中文文本需要指定编码...
walk(root_dir): # Go through each file for file in filenames: try: # Load up the file as a doc and split loader = TextLoader(os.path.join(dirpath, file), encoding='utf-8') docs.extend(loader.load_and_split()) except Exception as e: pass 代码语言:javascript 代码运行次数:0 ...
# 设置代理os.environ['HTTP_PROXY'] = 'socks5h://127.0.0.1:13659'os.environ['HTTPS_PROXY'] = 'socks5h://127.0.0.1:13659' # 创建文本加载器loader = TextLoader('/Users/aihe/Downloads/demo.txt', encoding='utf8') # 加载文档documents = loader.load() # 文本分块text_splitter = Characte...
笔者认为 Langchain 作为一个大语言模型应用开发框架,解决了现在开发人工智能应用的一些切实痛点。以 GPT 模型为例: 1.数据滞后,现在训练的数据是到 2021 年 9 月。 2.token 数量限制,如果让它对一个 300 页的 pdf 进行总结,直接使用则无能为力。
#loader = TextLoader(file_path=file_path,encoding='utf8') documents=loader.load() # Split documents ernieChunkSize=384 text_splitter = RecursiveCharacterTextSplitter(chunk_size=ernieChunkSize, chunk_overlap=0) splits = text_splitter.split_documents(documents) ...
1. TextLoader:最基础的文本加载器 from langchain_community.document_loaders import TextLoader loader = TextLoader("./example.txt", encoding="utf-8") documents = loader.load() # 输出示例 # Document(page_content='文件内容', metadata={'source': './example.txt'}) 1. 2. 3. 4. 5. 6. 7...
from langchain.chains import RetrievalQA from langchain.llms import OpenAI from langchain.document_loaders import TextLoader from langchain.indexes import VectorstoreIndexCreator loader = TextLoader('../state_of_the_union.txt', encoding='utf8') # 对加载的内容进行索引 index = VectorstoreIndexCreato...
content = uploaded_file.read().decode('utf-8') # st.write(content) file_path = "temp/file.txt" write_text_file(content, file_path) loader = TextLoader(file_path) docs = loader.load() text_splitter = CharacterTextSp...
fromlangchain.document_loadersimportTextLoader documents=TextLoader("/path/to/document.md",encoding='utf-8').load() 加载Csv文件 fromlangchain.document_loaders.csv_loaderimportCSVLoader loader=CSVLoader(file_path='/path/to/data.csv')data=loader.load() ...