deepset-ai--haystack/docs-website/reference_versioned_docs/version-2.30/integrations-api/amazon_textract.md

title, id, description, slug

title	id	description	slug
Amazon Textract	integrations-amazon_textract	Amazon Textract integration for Haystack	/integrations-amazon_textract

haystack_integrations.components.converters.amazon_textract.converter

AmazonTextractConverter

Converts documents to Haystack Documents using AWS Textract.

This component uses AWS Textract to extract text and optionally structured data (tables, forms) from images and single-page PDFs.

When feature_types is not set, the component uses DetectDocumentText for plain text OCR. When feature_types is set (e.g. ["TABLES", "FORMS"]), it uses AnalyzeDocument for richer structural analysis.

Natural-language queries are also supported via the queries parameter on run(). When queries are provided, the QUERIES feature type is added automatically and Textract returns answers extracted from the document.

Supported input formats: JPEG, PNG, TIFF, BMP, and single-page PDF (up to 10 MB).

AWS credentials are resolved via Secret parameters or the default boto3 credential chain (environment variables, AWS config files, IAM roles).

Usage example

from haystack_integrations.components.converters.amazon_textract import AmazonTextractConverter

converter = AmazonTextractConverter()
results = converter.run(sources=["document.png"])
documents = results["documents"]

init

__init__(
    *,
    aws_access_key_id: Secret | None = Secret.from_env_var(
        "AWS_ACCESS_KEY_ID", strict=False
    ),
    aws_secret_access_key: Secret | None = Secret.from_env_var(
        "AWS_SECRET_ACCESS_KEY", strict=False
    ),
    aws_session_token: Secret | None = Secret.from_env_var(
        "AWS_SESSION_TOKEN", strict=False
    ),
    aws_region_name: Secret | None = Secret.from_env_var(
        "AWS_DEFAULT_REGION", strict=False
    ),
    aws_profile_name: Secret | None = Secret.from_env_var(
        "AWS_PROFILE", strict=False
    ),
    feature_types: list[str] | None = None,
    store_full_path: bool = False,
    boto3_config: dict[str, Any] | None = None
) -> None

Creates an AmazonTextractConverter component.

Parameters:

• aws_access_key_id (Secret | None) – AWS access key ID.
• aws_secret_access_key (Secret | None) – AWS secret access key.
• aws_session_token (Secret | None) – AWS session token.
• aws_region_name (Secret | None) – AWS region name. Must be a region that supports Textract.
• aws_profile_name (Secret | None) – AWS profile name from the credentials file.
• feature_types (list[str] | None) – List of feature types to detect when using AnalyzeDocument. Valid values: "TABLES", "FORMS", "SIGNATURES", "LAYOUT". If None, uses DetectDocumentText for basic text extraction. The "QUERIES" feature type is managed automatically when the queries parameter is passed to run().
• store_full_path (bool) – If True, stores the complete file path in Document metadata. If False, stores only the filename (default).
• boto3_config (dict[str, Any] | None) – Dictionary of configuration options for the underlying boto3 client. Can be used to tune retry behavior, timeouts, and connection management.

warm_up

warm_up() -> None

Initializes the AWS Textract client.

run

run(
    sources: list[str | Path | ByteStream],
    meta: dict[str, Any] | list[dict[str, Any]] | None = None,
    queries: list[str] | None = None,
) -> dict[str, Any]

Convert documents to Haystack Documents using AWS Textract.

Parameters:

• sources (list[str | Path | ByteStream]) – List of file paths or ByteStream objects to convert.
• meta (dict[str, Any] | list[dict[str, Any]] | None) – Optional 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.
• queries (list[str] | None) – Optional list of natural-language questions to ask about each document. When provided, the Textract QUERIES feature type is enabled automatically and each question is sent as a query. Answers are included in the raw Textract response. Example: ["What is the patient name?", "What is the total due?"]

Returns:

• dict[str, Any] – A dictionary with the following keys:
• documents: List of created Documents with extracted text as content.
• raw_textract_response: List of raw Textract API responses.

to_dict

to_dict() -> dict[str, Any]

Serializes the component to a dictionary.

Returns:

• dict[str, Any] – Dictionary with serialized data.

from_dict

from_dict(data: dict[str, Any]) -> AmazonTextractConverter

Deserializes the component from a dictionary.

Parameters:

• data (dict[str, Any]) – The dictionary to deserialize from.

Returns:

• AmazonTextractConverter – The deserialized component.