DocumentCleaner

Clean the text in documents by removing whitespaces, empty lines, headers, footers, and more. Use this component in indexing pipelines to prepare documents for further processing by LLMs or embedders.

Key Features

• Removes empty lines and extra whitespaces.
• Removes repeated substrings such as headers and footers across pages.
• Removes specific substrings or text matching a regular expression.
• Normalizes Unicode characters (NFC, NFKC, NFD, or NFKD).
• Converts text to ASCII only, removing accents and non-ASCII characters.
• Optionally retains the original document ID.

Configuration

1. Drag the DocumentCleaner component onto the canvas from the Component Library.
2. Click on the component to open the configuration panel.
3. Configure the component settings:
   • Toggle Remove Empty Lines to remove empty lines from the document.
   • Toggle Remove Extra Whitespaces to remove extra whitespaces from the document.
   • Toggle Remove Repeated Substrings to remove repeated headers and footers from pages. Pages must be separated by a form feed character \f, which is supported by TextFileToDocument and AzureOCRDocumentConverter.
   • Set Remove Substrings to specify a list of strings to remove from the document.
   • Set Remove Regex to specify a regular expression pattern whose matches are removed.
   • Set Unicode Normalization to apply Unicode normalization to the text.
   • Toggle ASCII Only to convert text to ASCII, removing accents and other non-ASCII characters.
   • Toggle Keep ID to retain the original document ID.

Connections

DocumentCleaner accepts a list of Document objects and outputs cleaned Document objects.

It typically receives documents from converters like TextFileToDocument, PDFMinerToDocument, or AzureOCRDocumentConverter, and sends cleaned documents to DocumentSplitter for chunking or directly to document embedders.

Source Code

To check this component's source code, open document_cleaner.py in the Haystack repository.

Usage Examples

Basic Configuration

  DocumentCleaner:
    type: haystack.components.preprocessors.document_cleaner.DocumentCleaner
    init_parameters:
      remove_empty_lines: true
      remove_extra_whitespaces: true
      remove_repeated_substrings: false
      keep_id: false
      ascii_only: false

Using the Component in an Index

This example shows a typical indexing pipeline where DocumentCleaner cleans documents after conversion and before splitting.

# haystack-pipeline
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
      remove_repeated_substrings: false
      remove_substrings:
      remove_regex:
      keep_id: false
      unicode_normalization:
      ascii_only: false
  DocumentSplitter:
    type: haystack.components.preprocessors.document_splitter.DocumentSplitter
    init_parameters:
      split_by: word
      split_length: 200
      split_overlap: 0
      split_threshold: 0
  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: 768
          return_embedding: false
          create_index: true
          similarity: cosine
      policy: NONE

connections:
- sender: TextFileToDocument.documents
  receiver: DocumentCleaner.documents
- sender: DocumentCleaner.documents
  receiver: DocumentSplitter.documents
- sender: DocumentSplitter.documents
  receiver: DocumentWriter.documents

max_runs_per_component: 100

metadata: {}

inputs:
  files:
  - TextFileToDocument.sources

Parameters

Inputs

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

Outputs

Parameter	Type	Description
documents	List[Document]	List of cleaned documents.

Init Parameters

These are the parameters you can configure in Pipeline Builder:

Parameter	Type	Default	Description
remove_empty_lines	bool	True	If True, removes empty lines.
remove_extra_whitespaces	bool	True	If True, removes extra whitespaces.
remove_repeated_substrings	bool	False	If True, removes repeated substrings (headers and footers) from pages. Pages must be separated by a form feed character "\f", which is supported by TextFileToDocument and AzureOCRDocumentConverter.
remove_substrings	Optional[List[str]]	None	List of substrings to remove from the text.
remove_regex	Optional[str]	None	Regex to match and replace substrings by "".
keep_id	bool	False	If True, keeps the IDs of the original documents.
unicode_normalization	Optional[Literal['NFC', 'NFKC', 'NFD', 'NFKD']]	None	Unicode normalization form to apply to the text. Note: This will run before any other steps.
ascii_only	bool	False	Whether to convert the text to ASCII only. Will remove accents from characters and replace them with ASCII characters. Other non-ASCII characters will be removed. Note: This will run before any pattern matching or removal.

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	Description
documents	List[Document]	List of Documents to clean.

Related Information

• DocumentSplitter
• DocumentPreprocessor
• Pipeline Components