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Copy file name to clipboardExpand all lines: articles/ai-services/openai/concepts/content-credentials.md
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ms.author: pafarley
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ms.service: azure-ai-openai
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ms.topic: conceptual
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ms.date: 02/20/2025
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ms.date: 04/23/2025
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manager: nitinme
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---
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## What are Content Credentials?
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Content Credentials in the Azure OpenAI Service provide customers with information about the origin of an image generated by the DALL-E series models. This information is represented by a manifest attached to the image. The manifest is cryptographically signed by a certificate that traces back to Azure OpenAI Service.
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Content Credentials in the Azure OpenAI Service provide customers with information about the origin of an image generated by the image generation models. This information is represented by a manifest attached to the image. The manifest is cryptographically signed by a certificate that traces back to Azure OpenAI Service.
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The manifest contains several key pieces of information:
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| Field name | Field content |
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| ---| ---|
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|`"description"`| This field has a value of `"AI Generated Image"` for all DALL-E model generated images, attesting to the AI-generated nature of the image. |
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|`"softwareAgent"`| This field has a value of `"Azure OpenAI DALL-E"` for all images generated by DALL-E series models in Azure OpenAI Service. |
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|`"description"`| This field has a value of `"AI Generated Image"` for all generated images, attesting to the AI-generated nature of the image. |
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|`"softwareAgent"`| This field has a value of `"Azure OpenAI DALL-E"`or `"Azure OpenAI ImageGen"`for all images generated by DALL-E series models or GPT-image-1 models in Azure OpenAI Service. |
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|`"when"`|The timestamp of when the Content Credentials were created. |
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## How do I use Content Credentials in my solution today?
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Customers may use Content Credentials by:
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- Ensuring that their AIgenerated images contain Content Credentials
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No additional set-up is necessary. Content Credentials are automatically applied to all generated images from DALL·E in the Azure OpenAI Service.
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- Ensuring that their AI-generated images contain Content Credentials
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No additional set-up is necessary. Content Credentials are automatically applied to all generated images from DALL·E and GPT-image-1 in the Azure OpenAI Service.
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- Verifying that an image has Content Credentials
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There are two recommended ways today to check the credential of an image generated by Azure OpenAI DALL-E models:
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There are two recommended ways today to check the credential of an image generated by Azure OpenAI models:
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-**Content Credentials Verify webpage (contentcredentials.org/verify)**: This is a tool that allows users to inspect the Content Credentials of a piece of content. If an image was generated by DALL-E in Azure OpenAI, the tool will display that its Content Credentials were issued by Microsoft Corporation alongside the date and time of issuance.
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-**Content Credentials Verify webpage (contentcredentials.org/verify)**: This is a tool that allows users to inspect the Content Credentials of a piece of content. If an image was generated by an Azure OpenAI image generation model, the tool will display that its Content Credentials were issued by Microsoft Corporation alongside the date and time of issuance.
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:::image type="content" source="../media/encryption/credential-check.png" alt-text="Screenshot of the content credential verification website.":::
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This page shows that an image generated by Azure OpenAI DALL-E has Content Credentials issued by Microsoft.
Copy file name to clipboardExpand all lines: articles/ai-services/openai/concepts/content-filter.md
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> [!IMPORTANT]
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> The content filtering system isn't applied to prompts and completions processed by the audio models such as Whisper in Azure OpenAI Service. Learn more about the [Audio models in Azure OpenAI](models.md?tabs=standard-audio#standard-deployment-regional-models-by-endpoint).
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Azure OpenAI Service includes a content filtering system that works alongside core models, including DALL-E image generation models. This system works by running both the prompt and completion through an ensemble of classification models designed to detect and prevent the output of harmful content. The content filtering system detects and takes action on specific categories of potentially harmful content in both input prompts and output completions. Variations in API configurations and application design might affect completions and thus filtering behavior.
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Azure OpenAI Service includes a content filtering system that works alongside core models, including image generation models. This system works by running both the prompt and completion through an ensemble of classification models designed to detect and prevent the output of harmful content. The content filtering system detects and takes action on specific categories of potentially harmful content in both input prompts and output completions. Variations in API configurations and application design might affect completions and thus filtering behavior.
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The text content filtering models for the hate, sexual, violence, and self-harm categories have been specifically trained and tested on the following languages: English, German, Japanese, Spanish, French, Italian, Portuguese, and Chinese. However, the service can work in many other languages, but the quality might vary. In all cases, you should do your own testing to ensure that it works for your application.
Copy file name to clipboardExpand all lines: articles/ai-services/openai/concepts/default-safety-policies.md
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| Profanity | Prompts | N/A |
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In addition to the above safety configurations, Azure OpenAI DALL-E also comes with [prompt transformation](./prompt-transformation.md) by default. This transformation occurs on all prompts to enhance the safety of your original prompt, specifically in the risk categories of diversity, deceptive generation of political candidates, depictions of public figures, protected material, and others.
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In addition to the above safety configurations, the latest image generation models also come with [prompt transformation](./prompt-transformation.md) by default. This transformation occurs on all prompts to enhance the safety of your original prompt, specifically in the risk categories of diversity, deceptive generation of political candidates, depictions of public figures, protected material, and others.
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|[GPT-4o & GPT-4o mini & GPT-4 Turbo](#gpt-4o-and-gpt-4-turbo)| The latest most capable Azure OpenAI models with multimodal versions, which can accept both text and images as input. |
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|[GPT-4](#gpt-4)| A set of models that improve on GPT-3.5 and can understand and generate natural language and code. |
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|[GPT-3.5](#gpt-35)| A set of models that improve on GPT-3 and can understand and generate natural language and code. |
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|[Embeddings](#embeddings)| A set of models that can convert text into numerical vector form to facilitate text similarity. |
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|[DALL-E](#dall-e-models)| A series of models that can generate original images from natural language. |
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|[Embeddings](#embeddings-models)| A set of models that can convert text into numerical vector form to facilitate text similarity. |
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|[Image generation](#image-generation-models)| A series of models that can generate original images from natural language. |
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|[Audio](#audio-models)| A series of models for speech to text, translation, and text to speech. GPT-4o audio models support either low-latency, "speech in, speech out" conversational interactions or audio generation. |
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## GPT 4.1 series
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OpenAI's MTEB benchmark testing found that even when the third generation model's dimensions are reduced to less than `text-embeddings-ada-002` 1,536 dimensions performance remains slightly better.
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## DALL-E
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## Image generation models
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The DALL-E models generate images from text prompts that the user provides. DALL-E 3 is generally available for use with the REST APIs. DALL-E 2 and DALL-E 3 with client SDKs are in preview.
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The image generation models generate images from text prompts that the user provides. GPT-image-1 is in limited access public preview. DALL-E 3 is generally available for use with the REST APIs. DALL-E 2 and DALL-E 3 with client SDKs are in preview.
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### Availability
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**For access to `gpt-image-1` registration is required, and access will be granted based on Microsoft's eligibility criteria**. Customers who have access to other limited access models will still need to request access for this model.
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Request access: [`computer-use-preview` limited access model application](https://aka.ms/oai/gptimage1access)
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Once access has been granted, you will need to create a deployment for the model.
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### Region availability
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| Model | Region |
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|---|---|
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|`dall-e-3`| East US<br>Australia East<br>Sweden Central|
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|`gpt-image-1`| West US 2 (Global Standard) <br> UAE North (Global Standard) |
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## Audio models
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Copy file name to clipboardExpand all lines: articles/ai-services/openai/concepts/prompt-transformation.md
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# What is prompt transformation?
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Prompt transformation is a process included in DALL-E 3 image generation that applies a safety and quality system message to your original prompt. It uses a large language model (LLM) call to add the message before sending your prompt to the model for image generation. This system message enriches your original prompt with the goal of generating more diverse and higher-quality images while maintaining intent.
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Prompt transformation is a process included in the DALL-E 3 and GPT-image-1 (preview) models that applies a safety and quality system message to your original prompt. It uses a large language model (LLM) call to add the message before sending your prompt to the model for image generation. This system message enriches your original prompt with the goal of generating more diverse and higher-quality images while maintaining intent.
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After prompt transformation is applied to the original prompt, content filtering is applied as a secondary step before image generation; for more information, see [Content filtering](./content-filter.md).
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> [!TIP]
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> Learn more about image generation prompting in OpenAI's [DALL·E documentation](https://platform.openai.com/docs/guides/images/language-specific-tips).
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> Learn more about image generation prompting in OpenAI's [Image generation documentation](https://platform.openai.com/docs/guides/images/language-specific-tips).
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## Prompt transformation example
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Prompt transformation is essential for responsible and high-quality generations. Not only does prompt transformation improve the safety of your generated image, but it also enriches your prompt in a more descriptive manner, leading to higher quality and descriptive imagery.
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Default prompt transformation in Azure OpenAI DALL-E 3 contains safety enhancements that steer the model away from generating images of Copyright Studio characters and artwork, public figures, and other harmful content such as sexual, hate and unfairness, violence, and self-harm content.
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Default prompt transformation contains safety enhancements that steer the model away from generating images of Copyright Studio characters and artwork, public figures, and other harmful content such as sexual, hate and unfairness, violence, and self-harm content.
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## How do I use prompt transformation?
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Prompt transformation is applied by default to all Azure OpenAI DALL-E 3 requests. No extra setup is required to benefit from prompt transformation enhancements.
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Prompt transformation is applied by default to all Azure OpenAI DALL-E 3 and GPT-image-1 requests. No extra setup is required to benefit from prompt transformation enhancements.
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Like image generation, prompt transformation is non-deterministic due to the nature of large language models. A single original prompt may lead to many image variants.
Copy file name to clipboardExpand all lines: articles/ai-services/openai/faq.yml
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- question: |
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How do the capabilities of Azure OpenAI compare to OpenAI?
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answer: |
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Azure OpenAI Service gives customers advanced language AI with OpenAI GPT-3, Codex, and DALL-E models with the security and enterprise promise of Azure. Azure OpenAI codevelops the APIs with OpenAI, ensuring compatibility and a smooth transition from one to the other.
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Azure OpenAI Service gives customers advanced language AI with the latest OpenAI models with the security and enterprise promise of Azure. Azure OpenAI codevelops the APIs with OpenAI, ensuring compatibility and a smooth transition from one to the other.
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With Azure OpenAI, customers get the security capabilities of Microsoft Azure while running the same models as OpenAI.
Copy file name to clipboardExpand all lines: articles/ai-services/openai/how-to/content-filters.md
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# How to configure content filters
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The content filtering system integrated into Azure AI Foundry runs alongside the core models, including DALL-E image generation models. It uses an ensemble of multi-class classification models to detect four categories of harmful content (violence, hate, sexual, and self-harm) at four severity levels respectively (safe, low, medium, and high), and optional binary classifiers for detecting jailbreak risk, existing text, and code in public repositories.
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The content filtering system integrated into Azure AI Foundry runs alongside the core models, including image generation models. It uses an ensemble of multi-class classification models to detect four categories of harmful content (violence, hate, sexual, and self-harm) at four severity levels respectively (safe, low, medium, and high), and optional binary classifiers for detecting jailbreak risk, existing text, and code in public repositories.
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The default content filtering configuration is set to filter at the medium severity threshold for all four content harms categories for both prompts and completions. That means that content that is detected at severity level medium or high is filtered, while content detected at severity level low or safe is not filtered by the content filters. Learn more about content categories, severity levels, and the behavior of the content filtering system [here](../concepts/content-filter.md).
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