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articles/ai-services/document-intelligence/how-to-guides/includes/v4-0/java-sdk.md

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ms.service: azure-ai-document-intelligence
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ms.topic: include
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ms.date: 11/19/2024
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ms.date: 02/10/2025
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ms.author: lajanuar
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ms.custom: devx-track-csharp, linux-related-content
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---

articles/ai-services/document-intelligence/how-to-guides/includes/v4-0/javascript-sdk.md

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ms.date: 02/10/2025
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articles/ai-services/document-intelligence/how-to-guides/includes/v4-0/python-sdk.md

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articles/ai-services/document-intelligence/quickstarts/includes/csharp-sdk.md

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ms.service: azure-ai-document-intelligence
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ms.date: 12/17/2024
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ms.date: 02/10/2025
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monikerRange: ">=doc-intel-3.0.0"
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---

articles/ai-services/document-intelligence/quickstarts/includes/java-sdk.md

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<!-- markdownlint-disable MD025 -->
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>[!TIP]
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>
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> * Visual Studio Code offers a **Coding Pack for Java** for Windows and macOS.The coding pack is a bundle of VS Code, the Java Development Kit (JDK), and a collection of suggested extensions by Microsoft. The Coding Pack can also be used to fix an existing development environment.
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> * If you are using VS Code and the Coding Pack For Java, install the [**Gradle for Java**](https://marketplace.visualstudio.com/items?itemName=vscjava.vscode-gradle) extension.
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> * If you're using VS Code and the Coding Pack For Java, install the [**Gradle for Java**](https://marketplace.visualstudio.com/items?itemName=vscjava.vscode-gradle) extension.
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* If you aren't using Visual Studio Code, make sure you have the following installed in your development environment:
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* An Azure AI services or Document Intelligence resource. Once you have your Azure subscription, create a [single-service](https://portal.azure.com/#create/Microsoft.CognitiveServicesFormRecognizer) or [multi-service](https://portal.azure.com/#create/Microsoft.CognitiveServicesAIServices) Document Intelligence resource, in the Azure portal, to get your key and endpoint. You can use the free pricing tier (`F0`) to try the service, and upgrade later to a paid tier for production.
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> [!TIP]
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> Create an Azure AI services resource if you plan to access multiple Azure AI services under a single endpoint/key. For Document Intelligence access only, create a Document Intelligence resource. Please note that you'll need a single-service resource if you intend to use [Microsoft Entra authentication](/azure/active-directory/authentication/overview-authentication).
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> Create an Azure AI services resource if you plan to access multiple Azure AI services under a single endpoint/key. For Document Intelligence access only, create a Document Intelligence resource. You need a single-service resource if you intend to use [Microsoft Entra authentication](/azure/active-directory/authentication/overview-authentication).
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* After your resource deploys, select **Go to resource**. You need the key and endpoint from the resource you create to connect your application to the Document Intelligence API. Later, you paste your key and endpoint into the code:
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articles/ai-services/document-intelligence/quickstarts/includes/javascript-sdk.md

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---
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<!-- markdownlint-disable MD025 -->
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* An Azure AI services or Document Intelligence resource. Once you have your Azure subscription, create a [single-service](https://portal.azure.com/#create/Microsoft.CognitiveServicesFormRecognizer) or [multi-service](https://portal.azure.com/#create/Microsoft.CognitiveServicesAIServices) Document Intelligence resource, in the Azure portal, to get your key and endpoint. You can use the free pricing tier (`F0`) to try the service, and upgrade later to a paid tier for production.
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> [!TIP]
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> Create an Azure AI services resource if you plan to access multiple Azure AI services under a single endpoint/key. For Document Intelligence access only, create a Document Intelligence resource. Please note that you'll need a single-service resource if you intend to use [Microsoft Entra authentication](/azure/active-directory/authentication/overview-authentication).
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> Create an Azure AI services resource if you plan to access multiple Azure AI services under a single endpoint/key. For Document Intelligence access only, create a Document Intelligence resource. You need a single-service resource if you intend to use [Microsoft Entra authentication](/azure/active-directory/authentication/overview-authentication).
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* After your resource deploys, select **Go to resource**. You need the key and endpoint from the resource you create to connect your application to the Document Intelligence API. You paste your key and endpoint into the code later in the quickstart:
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articles/ai-services/document-intelligence/quickstarts/includes/python-sdk.md

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<!-- markdownlint-disable MD025 -->

articles/ai-services/document-intelligence/train/custom-model.md

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* For PDF and TIFF, up to 2,000 pages can be processed (with a free tier subscription, only the first two pages are processed).
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* The file size for analyzing documents is 500 MB for paid (S0) tier and 4 MB for free (F0) tier.
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* The file size for analyzing documents is `500 MB` for paid (S0) tier and `4 MB` for free (F0) tier.
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* Image dimensions must be between 50 x 50 pixels and 10,000 px x 10,000 pixels.
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* Image dimensions must be between 50 x 50 pixels and 10,000 pixels x 10,000 pixels.
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* If your PDFs are password-locked, you must remove the lock before submission.
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* The minimum height of the text to be extracted is 12 pixels for a 1024 x 768 pixel image. This dimension corresponds to about `8`-point text at 150 dots per inch.
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* The minimum height of the text to be extracted is 12 pixels for a 1024 x 768 pixel image. This dimension corresponds to about `8`-point text at `150` dots per inch.
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* For custom model training, the maximum number of pages for training data is 500 for the custom template model and 50,000 for the custom neural model.
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* For custom extraction model training, the total size of training data is 50 MB for template model and 1GB for the neural model.
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* For custom extraction model training, the total size of training data is `50 MB` for template model and `1` GB for the neural model.
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* For custom classification model training, the total size of training data is `1GB` with a maximum of 10,000 pages.
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* For custom classification model training, the total size of training data is `1 GB` with a maximum of 10,000 pages.
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### Optimal training data
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*-Behaves differently depending upon model. With template models, synthetic data is generated at training time. With neural models, exiting text recognized in the region is selected.
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> When choosing between the two model types, start with a custom neural model if it meets your functional needs. See [custom neural](custom-neural.md) to learn more about custom neural models.
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> To choose between the two model types, start with a custom neural model if it meets your functional needs. See [custom neural](custom-neural.md) to learn more about custom neural models.
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:::moniker-end
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| Custom neural v4.0 v3.1 v3.0 | [Document Intelligence 3.1](/rest/api/aiservices/document-models/analyze-document?view=rest-aiservices-2023-07-31&preserve-view=true&tabs=HTTP)| [Document Intelligence SDK](../quickstarts/get-started-sdks-rest-api.md?view=doc-intel-3.0.0&preserve-view=true)| [Document Intelligence Studio](https://formrecognizer.appliedai.azure.com/studio)
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| Custom form v2.1 | [Document Intelligence 2.1 GA API](/rest/api/aiservices/analyzer?view=rest-aiservices-v2.1&preserve-view=true) | [Document Intelligence SDK](../quickstarts/get-started-sdks-rest-api.md?view=doc-intel-2.1.0&preserve-view=true?pivots=programming-language-python)| [Sample labeling tool](https://fott-2-1.azurewebsites.net/)|
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> [!NOTE]
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> Custom template models trained with the 3.0 API will have a few improvements over the 2.1 API stemming from improvements to the OCR engine. Datasets used to train a custom template model using the 2.1 API can still be used to train a new model using the 3.0 API.
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> Custom template models trained with the 3.0 API have a few improvements over the 2.1 API stemming from improvements to the OCR engine. Datasets used to train a custom template model using the 2.1 API can still be used to train a new model using the 3.0 API.
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* For best results, provide one clear photo or high-quality scan per document.
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* Supported file formats are JPEG/JPG, PNG, BMP, TIFF, and PDF (text-embedded or scanned). Text-embedded PDFs are best to eliminate the possibility of error in character extraction and location.
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* For PDF and TIFF files, up to 2,000 pages can be processed. With a free tier subscription, only the first two pages are processed.
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* One clear photo or high-quality scan per document should be provided for best results, provide.
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* File formats supported are JPEG/JPG, PNG, BMP, TIFF, and PDF (text-embedded or scanned). Text-embedded PDFs are best to eliminate the possibility of error in character extraction and location.
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* PDF and TIFF files, up to 2,000 pages, can be processed. With a free tier subscription, only the first two pages are processed.
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* The file size must be less than 500 MB for paid (S0) tier and 4 MB for free (F0) tier.
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* Image dimensions must be between 50 x 50 pixels and 10,000 x 10,000 pixels.
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* PDF dimensions are up to 17 x 17 inches, corresponding to Legal or A3 paper size, or smaller.
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* The total size of the training data is 500 pages or less.
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* If your PDFs are password-locked, you must remove the lock before submission.
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* PDFs that are password-locked must have the password lock removed before submission.
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> [!TIP]
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> Training data:
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> * If possible, use text-based PDF documents instead of image-based documents. Scanned PDFs are handled as images.
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> * Please supply only a single instance of the form per document.
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> * Supply only a single instance of the form per document.
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> * For filled-in forms, use examples that have all their fields filled in.
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> * If your form images are of lower quality, use a larger dataset. For example, use 10 to 15 images.

articles/ai-services/document-intelligence/versioning/sdk-overview-v3-1.md

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#### Use a Microsoft Entra token credential
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> [!NOTE]
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> Regional endpoints do not support Microsoft Entra authentication. Create a [custom subdomain](../../../ai-services/authentication.md?tabs=powershell#create-a-resource-with-a-custom-subdomain) for your resource in order to use this type of authentication.
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> Regional endpoints don't support Microsoft Entra authentication. Create a [custom subdomain](../../../ai-services/authentication.md?tabs=powershell#create-a-resource-with-a-custom-subdomain) for your resource in order to use this type of authentication.
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Authorization is easiest using the `DefaultAzureCredential`. It provides a default token credential, based upon the running environment, capable of handling most Azure authentication scenarios.
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