langchain_community.document_loaders.csv_loader
.UnstructuredCSVLoader¶
- class langchain_community.document_loaders.csv_loader.UnstructuredCSVLoader(file_path: str, mode: str = 'single', **unstructured_kwargs: Any)[source]¶
Load CSV files using Unstructured.
Like other Unstructured loaders, UnstructuredCSVLoader can be used in both “single” and “elements” mode. If you use the loader in “elements” mode, the CSV file will be a single Unstructured Table element. If you use the loader in “elements” mode, an HTML representation of the table will be available in the “text_as_html” key in the document metadata.
Examples
from langchain_community.document_loaders.csv_loader import UnstructuredCSVLoader
loader = UnstructuredCSVLoader(“stanley-cups.csv”, mode=”elements”) docs = loader.load()
- Parameters
file_path – The path to the CSV file.
mode – The mode to use when loading the CSV file. Optional. Defaults to “single”.
**unstructured_kwargs – Keyword arguments to pass to unstructured.
Methods
__init__
(file_path[, mode])- param file_path
The path to the CSV file.
A lazy loader for Documents.
load
()Load file.
load_and_split
([text_splitter])Load Documents and split into chunks.
- __init__(file_path: str, mode: str = 'single', **unstructured_kwargs: Any)[source]¶
- Parameters
file_path – The path to the CSV file.
mode – The mode to use when loading the CSV file. Optional. Defaults to “single”.
**unstructured_kwargs – Keyword arguments to pass to unstructured.
- load_and_split(text_splitter: Optional[TextSplitter] = None) List[Document] ¶
Load Documents and split into chunks. Chunks are returned as Documents.
- Parameters
text_splitter – TextSplitter instance to use for splitting documents. Defaults to RecursiveCharacterTextSplitter.
- Returns
List of Documents.