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For the complete documentation index for agents and LLMs, see llms.txt.

HTMLToDocument

Convert HTML files to documents your pipeline can query, with customizable text extraction options.

Key Features

  • Converts HTML files to Haystack Document objects using the Trafilatura library
  • Customizable extraction via keyword arguments passed to the Trafilatura extract function
  • Supports optional table and link inclusion in the extracted text
  • Supports language filtering to discard documents that don't match a target language
  • Attaches optional metadata to each resulting document
  • Controls whether to store the full file path or just the file name in document metadata

Configuration

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

Connections

HTMLToDocument receives HTML files as input — typically from FileTypeRouter (which routes files by MIME type) or from LinkContentFetcher (when indexing web content). It outputs a list of Document objects that you can send to DocumentJoiner (if you have other converters in your pipeline) or directly to DocumentSplitter for further processing.

Usage Example

Using the Component in an Index

In this index, HTMLToDocument receives HTML files from FileTypeRouter and sends them to DocumentJoiner.

components:
file_classifier:
type: haystack.components.routers.file_type_router.FileTypeRouter
init_parameters:
mime_types:
- text/markdown
- text/html
- text/csv

markdown_converter:
type: haystack.components.converters.txt.TextFileToDocument
init_parameters:
encoding: utf-8

html_converter:
type: haystack.components.converters.html.HTMLToDocument
init_parameters:
# A dictionary of keyword arguments to customize how you want to extract content from your HTML files.
# For the full list of available arguments, see
# the [Trafilatura documentation](https://trafilatura.readthedocs.io/en/latest/corefunctions.html#extract).
extraction_kwargs:
output_format: markdown # Extract text from HTML. You can also also choose "txt"
target_language: # You can define a language (using the ISO 639-1 format) to discard documents that don't match that language.
include_tables: true # If true, includes tables in the output
include_links: true # If true, keeps links along with their targets


csv_converter:
type: haystack.components.converters.csv.CSVToDocument
init_parameters:
encoding: utf-8

joiner:
type: haystack.components.joiners.document_joiner.DocumentJoiner
init_parameters:
join_mode: concatenate
sort_by_score: false

splitter:
type: haystack.components.preprocessors.document_splitter.DocumentSplitter
init_parameters:
split_by: word
split_length: 250
split_overlap: 30
respect_sentence_boundary: true
language: en

document_embedder:
type: haystack.components.embedders.sentence_transformers_document_embedder.SentenceTransformersDocumentEmbedder
init_parameters:
normalize_embeddings: true
model: intfloat/e5-base-v2

writer:
type: haystack.components.writers.document_writer.DocumentWriter
init_parameters:
document_store:
type: haystack_integrations.document_stores.opensearch.document_store.OpenSearchDocumentStore
init_parameters:
hosts:
index: ''
max_chunk_bytes: 104857600
embedding_dim: 768
return_embedding: false
method:
mappings:
settings:
create_index: true
http_auth:
use_ssl:
verify_certs:
timeout:
policy: OVERWRITE

connections: # Defines how the components are connected
- sender: file_classifier.text/markdown
receiver: markdown_converter.sources
- sender: file_classifier.text/html
receiver: html_converter.sources
- sender: file_classifier.text/csv
receiver: csv_converter.sources
- sender: markdown_converter.documents
receiver: joiner.documents
- sender: html_converter.documents
receiver: joiner.documents
- sender: joiner.documents
receiver: splitter.documents
- sender: document_embedder.documents
receiver: writer.documents
- sender: csv_converter.documents
receiver: joiner.documents
- sender: splitter.documents
receiver: document_embedder.documents

inputs: # Define the inputs for your pipeline
files: # This component will receive the files to index as input
- file_classifier.sources

max_runs_per_component: 100

metadata: {}

Parameters

Inputs

ParameterTypeDefaultDescription
sourcesList[Union[str, Path, ByteStream]]List of HTML file paths or ByteStream objects to convert.
metaOptional[Union[Dict[str, Any], List[Dict[str, Any]]]]NoneOptional metadata to attach to the Documents. This value can be either a list of dictionaries or a single dictionary. If it's a single dictionary, its content is added to the metadata of all produced Documents. If it's a list, the length of the list must match the number of sources, because the two lists are zipped. If sources contains ByteStream objects, their meta is added to the output Documents.
extraction_kwargsOptional[Dict[str, Any]]NoneAdditional keyword arguments to customize the extraction process.

Outputs

ParameterTypeDefaultDescription
documentsList[Document]Converted documents

Init Parameters

These are the parameters you can configure in Pipeline Builder:

ParameterTypeDefaultDescription
extraction_kwargsOptional[Dict[str, Any]]NoneA dictionary containing keyword arguments to customize the extraction process. These are passed to the underlying Trafilatura extract function. For the full list of available arguments, see the Trafilatura documentation.
store_full_pathboolFalseIf True, the full path of the file is stored in the metadata of the document. If False, only the file name is stored.

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.

ParameterTypeDefaultDescription
sourcesList[Union[str, Path, ByteStream]]List of HTML file paths or ByteStream objects.
metaOptional[Union[Dict[str, Any], List[Dict[str, Any]]]]NoneOptional metadata to attach to the Documents. This value can be either a list of dictionaries or a single dictionary. If it's a single dictionary, its content is added to the metadata of all produced Documents. If it's a list, the length of the list must match the number of sources, because the two lists will be zipped. If sources contains ByteStream objects, their meta will be added to the output Documents.
extraction_kwargsOptional[Dict[str, Any]]NoneAdditional keyword arguments to customize the extraction process.