Add Amazon Textract integration page (#484)

* Add Amazon Textract integration page

* Address comments

Author: bogdankostic

integrations/amazon-textract.md

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+---
+layout: integration
+name: Amazon Textract
+description: Use Amazon Textract with Haystack to extract text, tables, forms, and answers to queries from documents
+authors:
+    - name: deepset
+      socials:
+        github: deepset-ai
+        twitter: deepset_ai
+        linkedin: https://www.linkedin.com/company/deepset-ai/
+pypi: https://pypi.org/project/amazon-textract-haystack
+repo: https://github.com/deepset-ai/haystack-core-integrations/tree/main/integrations/amazon_textract
+type: Data Ingestion
+report_issue: https://github.com/deepset-ai/haystack-core-integrations/issues
+logo: /logos/aws.png
+version: Haystack 2.0
+toc: true
+---
+
+### **Table of Contents**
+- [Overview](#overview)
+- [Installation](#installation)
+- [Usage](#usage)
+
+## Overview
+
+[`AmazonTextractConverter`](https://docs.haystack.deepset.ai/docs/amazontextractconverter) provides an integration of [Amazon Textract](https://aws.amazon.com/textract/) with Haystack.
+
+This component uses Amazon Textract's synchronous API to convert images and single-page PDFs into Haystack `Document` objects using OCR. It supports plain text extraction, structural analysis for tables and forms, and natural-language queries on documents.
+
+**Supported file formats**: JPEG, PNG, TIFF, BMP, and single-page PDF (up to 10 MB).
+
+**Key features**:
+- Plain text extraction with `DetectDocumentText`
+- Table, form, signature, and layout detection with `AnalyzeDocument`
+- Natural-language queries to extract specific answers from documents
+- Access to the raw Textract response for downstream processing
+
+## Installation
+
+Install the Amazon Textract integration:
+
+```bash
+pip install amazon-textract-haystack
+```
+
+## Usage
+
+The component uses the standard boto3 credential chain. You can set AWS credentials (`AWS_ACCESS_KEY_ID`, `AWS_SECRET_ACCESS_KEY`, `AWS_DEFAULT_REGION`) as environment variables, configure them via `~/.aws/credentials` and `~/.aws/config`, rely on an IAM role when running on AWS infrastructure, or pass them explicitly as [Secret](https://docs.haystack.deepset.ai/docs/secret-management) arguments.
+
+The Textract API is selected automatically based on how you configure the component: `DetectDocumentText` is used by default for plain text extraction, while `AnalyzeDocument` is used whenever you set `feature_types` or pass `queries` at runtime.
+
+### Basic text extraction
+
+Extract plain text from a document with the default configuration, which calls `DetectDocumentText`:
+
+```python
+from haystack_integrations.components.converters.amazon_textract import AmazonTextractConverter
+
+converter = AmazonTextractConverter()
+results = converter.run(sources=["document.png"])
+documents = results["documents"]
+
+print(documents[0].content)
+```
+
+### Table and form analysis
+
+Use `AnalyzeDocument` to detect tables and forms by setting `feature_types`:
+
+```python
+from haystack_integrations.components.converters.amazon_textract import AmazonTextractConverter
+
+converter = AmazonTextractConverter(feature_types=["TABLES", "FORMS"])
+results = converter.run(sources=["invoice.png"])
+
+documents = results["documents"]
+raw_responses = results["raw_textract_response"]
+```
+
+Valid `feature_types` values: `"TABLES"`, `"FORMS"`, `"SIGNATURES"`, `"LAYOUT"`.
+
+### Natural-language queries
+
+Ask questions about a document and get extracted answers. The `QUERIES` feature type is enabled automatically when you pass the `queries` parameter at runtime:
+
+```python
+from haystack_integrations.components.converters.amazon_textract import AmazonTextractConverter
+
+converter = AmazonTextractConverter()
+results = converter.run(
+    sources=["medical_form.png"],
+    queries=["What is the patient name?", "What is the date of birth?"],
+)
+
+documents = results["documents"]
+raw_responses = results["raw_textract_response"]
+```
+
+Queries can be combined with `feature_types` for both structural and question-based extraction:
+
+```python
+converter = AmazonTextractConverter(feature_types=["TABLES", "FORMS"])
+results = converter.run(
+    sources=["invoice.png"],
+    queries=["What is the total amount due?"],
+)
+```
+
+### Explicit credentials
+
+```python
+from haystack.utils import Secret
+from haystack_integrations.components.converters.amazon_textract import AmazonTextractConverter
+
+converter = AmazonTextractConverter(
+    aws_access_key_id=Secret.from_env_var("MY_AWS_KEY"),
+    aws_secret_access_key=Secret.from_env_var("MY_AWS_SECRET"),
+    aws_region_name=Secret.from_token("us-east-1"),
+)
+```
+
+For more details on Amazon Textract capabilities and setup, refer to the [Amazon Textract documentation](https://docs.aws.amazon.com/textract/latest/dg/what-is.html).
+
+### License
+
+`amazon-textract-haystack` is distributed under the terms of the [Apache-2.0](https://spdx.org/licenses/Apache-2.0.html) license.