RecursiveDocumentSplitter

Recursively chunk text into smaller pieces using a list of separators, creating more semantically meaningful chunks than fixed-size splitting.

Key Features

• Applies separators in order from most general to most specific, respecting natural text boundaries.
• Splits by paragraph, sentence, line, and word by default.
• Supports custom separator lists including regex patterns and the special "sentence" separator.
• Configurable chunk size in words, characters, or tokens.
• Configurable overlap between consecutive chunks.
• Accepts optional parameters for the sentence tokenizer.

Configuration

1. Drag the RecursiveDocumentSplitter component onto the canvas from the Component Library.
2. Click the component to open the configuration panel.
3. Configure the parameters as needed.

Connections

RecursiveDocumentSplitter accepts a list of documents (documents) as input and outputs a list of documents (documents) with smaller text chunks.

Connect converters or DocumentCleaner to the input. Connect the output to document embedders such as SentenceTransformersDocumentEmbedder, or directly to DocumentWriter for storage.

Usage Example

Using the Component in an Index

This example shows an index using recursive splitting with custom separators.

components:
  TextFileToDocument:
    type: haystack.components.converters.txt.TextFileToDocument
    init_parameters:
      encoding: utf-8
      store_full_path: false
  DocumentCleaner:
    type: haystack.components.preprocessors.document_cleaner.DocumentCleaner
    init_parameters:
      remove_empty_lines: true
      remove_extra_whitespaces: true
  RecursiveDocumentSplitter:
    type: haystack.components.preprocessors.recursive_splitter.RecursiveDocumentSplitter
    init_parameters:
      split_length: 200
      split_overlap: 20
      split_unit: word
      separators:
      - "\n\n"
      - sentence
      - "\n"
      - " "
      sentence_splitter_params:
  SentenceTransformersDocumentEmbedder:
    type: haystack.components.embedders.sentence_transformers_document_embedder.SentenceTransformersDocumentEmbedder
    init_parameters:
      model: sentence-transformers/all-MiniLM-L6-v2
      batch_size: 32
      progress_bar: true
      normalize_embeddings: false
  DocumentWriter:
    type: haystack.components.writers.document_writer.DocumentWriter
    init_parameters:
      document_store:
        type: haystack_integrations.document_stores.opensearch.document_store.OpenSearchDocumentStore
        init_parameters:
          hosts:
          index: documents-index
          max_chunk_bytes: 104857600
          embedding_dim: 384
          return_embedding: false
          create_index: true
          similarity: cosine
      policy: NONE

connections:
- sender: TextFileToDocument.documents
  receiver: DocumentCleaner.documents
- sender: DocumentCleaner.documents
  receiver: RecursiveDocumentSplitter.documents
- sender: RecursiveDocumentSplitter.documents
  receiver: SentenceTransformersDocumentEmbedder.documents
- sender: SentenceTransformersDocumentEmbedder.documents
  receiver: DocumentWriter.documents

max_runs_per_component: 100

metadata: {}

inputs:
  files:
  - TextFileToDocument.sources

Parameters

Inputs

Parameter	Type	Default	Description
documents	List[Document]		List of documents to split.

Outputs

Parameter	Type	Default	Description
documents	List[Document]		List of documents with smaller chunks of text.

Init Parameters

These are the parameters you can configure in Pipeline Builder:

Parameter	Type	Default	Description
split_length	int	200	The maximum length of each chunk by default in words, but can be in characters or tokens. See the split_units parameter.
split_overlap	int	0	The number of characters to overlap between consecutive chunks.
split_unit	Literal['word', 'char', 'token']	word	The unit of the split_length parameter. It can be either "word", "char", or "token". If "token" is selected, the text will be split into tokens using the tiktoken tokenizer (o200k_base).
separators	Optional[List[str]]	None	An optional list of separator strings to use for splitting the text. The string separators will be treated as regular expressions unless the separator is "sentence", in that case the text will be split into sentences using a custom sentence tokenizer based on NLTK. If no separators are provided, the default separators ["\n\n", "sentence", "\n", " "] are used.
sentence_splitter_params	Optional[Dict[str, Any]]	None	Optional parameters to pass to the sentence tokenizer.

Run Method Parameters

These are the parameters you can configure for the component's run() method. This means you can pass these parameters at query time through the API, in Playground, or when running a job. For details, see Modify Pipeline Parameters at Query Time.

Parameter	Type	Default	Description
documents	List[Document]		List of Documents to split.