Add Azure Form Recognizer integration tile

integrations/azure-form-recognizer.md

@@ -0,0 +1,82 @@
+---
+layout: integration
+name: Azure Form Recognizer
+description: Convert files to Documents using Azure's Document Intelligence service (Form Recognizer SDK)
+authors:
+    - name: deepset
+      socials:
+        github: deepset-ai
+        twitter: deepset_ai
+        linkedin: https://www.linkedin.com/company/deepset-ai/
+pypi: https://pypi.org/project/azure-form-recognizer-haystack
+repo: https://github.com/deepset-ai/haystack-core-integrations/tree/main/integrations/azure_form_recognizer
+type: Data Ingestion
+report_issue: https://github.com/deepset-ai/haystack-core-integrations/issues
+logo: /logos/azure-ai.png
+version: Haystack 2.0
+toc: true
+---
+
+### **Table of Contents**
+- [Overview](#overview)
+- [Installation](#installation)
+- [Usage](#usage)
+
+## Overview
+
+[`AzureOCRDocumentConverter`](https://docs.haystack.deepset.ai/docs/azureocrdocumentconverter) converts files to Haystack Documents using [Azure's Document Intelligence](https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/) service through the [`azure-ai-formrecognizer`](https://pypi.org/project/azure-ai-formrecognizer/) SDK.
+
+**Supported file formats**: PDF, JPEG, PNG, BMP, TIFF, DOCX, XLSX, PPTX, HTML.
+
+Unlike the [`AzureDocumentIntelligenceConverter`](azure-doc-intelligence.md) (which produces Markdown), this component extracts tables as separate `Document` objects that preserve their two-dimensional (CSV) structure, and returns the remaining text with page breaks (`\f`) so it can be split per page by downstream preprocessors.
+
+You need an active Azure account and a Document Intelligence or Cognitive Services resource. Follow the [Azure setup guide](https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/quickstarts/get-started-sdks-rest-api) to create your resource.
+
+## Installation
+
+```bash
+pip install azure-form-recognizer-haystack
+```
+
+## Usage
+
+Provide your service endpoint and an API key. By default the component reads the key from the `AZURE_AI_API_KEY` environment variable.
+
+```python
+import os
+from haystack_integrations.components.converters.azure_form_recognizer import AzureOCRDocumentConverter
+from haystack.utils import Secret
+
+converter = AzureOCRDocumentConverter(
+    endpoint=os.environ["AZURE_AI_ENDPOINT"],
+    api_key=Secret.from_env_var("AZURE_AI_API_KEY"),
+)
+
+results = converter.run(sources=["document.pdf"])
+documents = results["documents"]
+print(documents[0].content)
+```
+
+### In a pipeline
+
+```python
+from haystack import Pipeline
+from haystack.document_stores.in_memory import InMemoryDocumentStore
+from haystack.components.preprocessors import DocumentCleaner, DocumentSplitter
+from haystack.components.writers import DocumentWriter
+from haystack.utils import Secret
+from haystack_integrations.components.converters.azure_form_recognizer import AzureOCRDocumentConverter
+
+document_store = InMemoryDocumentStore()
+
+pipeline = Pipeline()
+pipeline.add_component("converter", AzureOCRDocumentConverter(endpoint="azure_resource_url", api_key=Secret.from_env_var("AZURE_AI_API_KEY")))
+pipeline.add_component("cleaner", DocumentCleaner())
+pipeline.add_component("splitter", DocumentSplitter(split_by="sentence", split_length=5))
+pipeline.add_component("writer", DocumentWriter(document_store=document_store))
+pipeline.connect("converter", "cleaner")
+pipeline.connect("cleaner", "splitter")
+pipeline.connect("splitter", "writer")
+
+pipeline.run({"converter": {"sources": ["my_file.pdf"]}})
+```