chore: import upstream snapshot with attribution

docs-website/reference/integrations-api/amazon_textract.md

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+---
+title: "Amazon Textract"
+id: integrations-amazon_textract
+description: "Amazon Textract integration for Haystack"
+slug: "/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
+
+```python
+from haystack_integrations.components.converters.amazon_textract import AmazonTextractConverter
+
+converter = AmazonTextractConverter()
+results = converter.run(sources=["document.png"])
+documents = results["documents"]
+```
+
+#### __init__
+
+```python
+__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** (<code>Secret | None</code>) – AWS access key ID.
+- **aws_secret_access_key** (<code>Secret | None</code>) – AWS secret access key.
+- **aws_session_token** (<code>Secret | None</code>) – AWS session token.
+- **aws_region_name** (<code>Secret | None</code>) – AWS region name. Must be a region that supports Textract.
+- **aws_profile_name** (<code>Secret | None</code>) – AWS profile name from the credentials file.
+- **feature_types** (<code>list\[str\] | None</code>) – 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** (<code>bool</code>) – If True, stores the complete file path in Document metadata.
+  If False, stores only the filename (default).
+- **boto3_config** (<code>dict\[str, Any\] | None</code>) – Dictionary of configuration options for the underlying boto3 client.
+  Can be used to tune retry behavior, timeouts, and connection management.
+
+#### warm_up
+
+```python
+warm_up() -> None
+```
+
+Initializes the AWS Textract client.
+
+#### run
+
+```python
+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** (<code>list\[str | Path | ByteStream\]</code>) – List of file paths or ByteStream objects to convert.
+- **meta** (<code>dict\[str, Any\] | list\[dict\[str, Any\]\] | None</code>) – 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** (<code>list\[str\] | None</code>) – 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:**
+
+- <code>dict\[str, Any\]</code> – 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
+
+```python
+to_dict() -> dict[str, Any]
+```
+
+Serializes the component to a dictionary.
+
+**Returns:**
+
+- <code>dict\[str, Any\]</code> – Dictionary with serialized data.
+
+#### from_dict
+
+```python
+from_dict(data: dict[str, Any]) -> AmazonTextractConverter
+```
+
+Deserializes the component from a dictionary.
+
+**Parameters:**
+
+- **data** (<code>dict\[str, Any\]</code>) – The dictionary to deserialize from.
+
+**Returns:**
+
+- <code>AmazonTextractConverter</code> – The deserialized component.