langchain.text_splitter.MarkdownTextSplitter¶

class langchain.text_splitter.MarkdownTextSplitter(**kwargs: Any)[source]¶

Attempts to split the text along Markdown-formatted headings.

Initialize a MarkdownTextSplitter.

Methods

__init__(**kwargs)

Initialize a MarkdownTextSplitter.

atransform_documents(documents, **kwargs)

Asynchronously transform a sequence of documents by splitting them.

create_documents(texts[, metadatas])

Create documents from a list of texts.

from_huggingface_tokenizer(tokenizer, **kwargs)

Text splitter that uses HuggingFace tokenizer to count length.

from_language(language, **kwargs)

from_tiktoken_encoder([encoding_name, ...])

Text splitter that uses tiktoken encoder to count length.

get_separators_for_language(language)

split_documents(documents)

Split documents.

split_text(text)

Split text into multiple components.

transform_documents(documents, **kwargs)

Transform sequence of documents by splitting them.

__init__(**kwargs: Any) None[source]¶

Initialize a MarkdownTextSplitter.

async atransform_documents(documents: Sequence[Document], **kwargs: Any) Sequence[Document]¶

Asynchronously transform a sequence of documents by splitting them.

create_documents(texts: List[str], metadatas: Optional[List[dict]] = None) List[Document]¶

Create documents from a list of texts.

classmethod from_huggingface_tokenizer(tokenizer: Any, **kwargs: Any) TextSplitter¶

Text splitter that uses HuggingFace tokenizer to count length.

classmethod from_language(language: Language, **kwargs: Any) RecursiveCharacterTextSplitter¶
classmethod from_tiktoken_encoder(encoding_name: str = 'gpt2', model_name: Optional[str] = None, allowed_special: Union[Literal['all'], AbstractSet[str]] = {}, disallowed_special: Union[Literal['all'], Collection[str]] = 'all', **kwargs: Any) TS¶

Text splitter that uses tiktoken encoder to count length.

static get_separators_for_language(language: Language) List[str]¶
split_documents(documents: Iterable[Document]) List[Document]¶

Split documents.

split_text(text: str) List[str]¶

Split text into multiple components.

transform_documents(documents: Sequence[Document], **kwargs: Any) Sequence[Document]¶

Transform sequence of documents by splitting them.