chore: import upstream snapshot with attribution

docs-website/reference_versioned_docs/version-2.18/integrations-api/azure_doc_intelligence.md

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+---
+title: "Azure Document Intelligence"
+id: integrations-azure_doc_intelligence
+description: "Azure Document Intelligence integration for Haystack"
+slug: "/integrations-azure_doc_intelligence"
+---
+
+<a id="haystack_integrations.components.converters.azure_doc_intelligence.converter"></a>
+
+## Module haystack\_integrations.components.converters.azure\_doc\_intelligence.converter
+
+<a id="haystack_integrations.components.converters.azure_doc_intelligence.converter.AzureDocumentIntelligenceConverter"></a>
+
+### AzureDocumentIntelligenceConverter
+
+Converts files to Documents using Azure's Document Intelligence service.
+
+This component uses the azure-ai-documentintelligence package (v1.0.0+) and outputs
+GitHub Flavored Markdown for better integration with LLM/RAG applications.
+
+Supported file formats: PDF, JPEG, PNG, BMP, TIFF, DOCX, XLSX, PPTX, HTML.
+
+Key features:
+- Markdown output with preserved structure (headings, tables, lists)
+- Inline table integration (tables rendered as markdown tables)
+- Improved layout analysis and reading order
+- Support for section headings
+
+To use this component, you need an active Azure account
+and a Document Intelligence or Cognitive Services resource. For setup instructions, see
+[Azure documentation](https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/quickstarts/get-started-sdks-rest-api).
+
+### Usage example
+
+```python
+import os
+from haystack_integrations.components.converters.azure_doc_intelligence import (
+    AzureDocumentIntelligenceConverter,
+)
+from haystack.utils import Secret
+
+converter = AzureDocumentIntelligenceConverter(
+    endpoint=os.environ["AZURE_DI_ENDPOINT"],
+    api_key=Secret.from_env_var("AZURE_DI_API_KEY"),
+)
+
+results = converter.run(sources=["invoice.pdf", "contract.docx"])
+documents = results["documents"]
+
+# Documents contain markdown with inline tables
+print(documents[0].content)
+```
+
+<a id="haystack_integrations.components.converters.azure_doc_intelligence.converter.AzureDocumentIntelligenceConverter.__init__"></a>
+
+#### AzureDocumentIntelligenceConverter.\_\_init\_\_
+
+```python
+def __init__(endpoint: str,
+             *,
+             api_key: Secret = Secret.from_env_var("AZURE_DI_API_KEY"),
+             model_id: str = "prebuilt-document",
+             store_full_path: bool = False)
+```
+
+Creates an AzureDocumentIntelligenceConverter component.
+
+**Arguments**:
+
+- `endpoint`: The endpoint URL of your Azure Document Intelligence resource.
+Example: "https://YOUR_RESOURCE.cognitiveservices.azure.com/"
+- `api_key`: API key for Azure authentication. Can use Secret.from_env_var()
+to load from AZURE_DI_API_KEY environment variable.
+- `model_id`: Azure model to use for analysis. Options:
+- "prebuilt-document": General document analysis (default)
+- "prebuilt-read": Fast OCR for text extraction
+- "prebuilt-layout": Enhanced layout analysis with better table/structure detection
+- Custom model IDs from your Azure resource
+- `store_full_path`: If True, stores complete file path in metadata.
+If False, stores only the filename (default).
+
+<a id="haystack_integrations.components.converters.azure_doc_intelligence.converter.AzureDocumentIntelligenceConverter.warm_up"></a>
+
+#### AzureDocumentIntelligenceConverter.warm\_up
+
+```python
+def warm_up()
+```
+
+Initializes the Azure Document Intelligence client.
+
+<a id="haystack_integrations.components.converters.azure_doc_intelligence.converter.AzureDocumentIntelligenceConverter.run"></a>
+
+#### AzureDocumentIntelligenceConverter.run
+
+```python
+@component.output_types(documents=list[Document],
+                        raw_azure_response=list[dict])
+def run(
+    sources: list[str | Path | ByteStream],
+    meta: dict[str, Any] | list[dict[str, Any]] | None = None
+) -> dict[str, list[Document] | list[dict]]
+```
+
+Convert a list of files to Documents using Azure's Document Intelligence service.
+
+**Arguments**:
+
+- `sources`: List of file paths or ByteStream objects.
+- `meta`: 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, because the two lists will be
+zipped. If `sources` contains ByteStream objects, their `meta` will be added to the output Documents.
+
+**Returns**:
+
+A dictionary with the following keys:
+- `documents`: List of created Documents
+- `raw_azure_response`: List of raw Azure responses used to create the Documents
+
+<a id="haystack_integrations.components.converters.azure_doc_intelligence.converter.AzureDocumentIntelligenceConverter.to_dict"></a>
+
+#### AzureDocumentIntelligenceConverter.to\_dict
+
+```python
+def to_dict() -> dict[str, Any]
+```
+
+Serializes the component to a dictionary.
+
+**Returns**:
+
+Dictionary with serialized data.
+
+<a id="haystack_integrations.components.converters.azure_doc_intelligence.converter.AzureDocumentIntelligenceConverter.from_dict"></a>
+
+#### AzureDocumentIntelligenceConverter.from\_dict
+
+```python
+@classmethod
+def from_dict(cls, data: dict[str,
+                              Any]) -> "AzureDocumentIntelligenceConverter"
+```
+
+Deserializes the component from a dictionary.
+
+**Arguments**:
+
+- `data`: The dictionary to deserialize from.
+
+**Returns**:
+
+The deserialized component.