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### YamlMime:Hub
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title: Azure OpenAI Documentation
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title: Azure OpenAI Service Documentation
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summary: Learn how to use Azure OpenAI's powerful language models including the GPT-3, Codex and Embeddings model series for content generation, summarization, semantic search, and natural language to code translation.
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brand: azure
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metadata:
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title: Azure OpenAI - Documentation, quickstarts, API reference
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title: Azure OpenAI Service - Documentation, quickstarts, API reference
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titleSuffix: Azure Cognitive Services
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description: Learn how to use Azure OpenAI's powerful language models including the GPT-3, Codex and Embeddings model series.
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---
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title: What is Azure OpenAI?
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title: What is Azure OpenAI Service?
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titleSuffix: Azure Cognitive Services
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description: Apply advanced language models to variety of use cases with the Azure OpenAI service
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description: Apply advanced language models to variety of use cases with Azure OpenAI
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manager: nitinme
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author: ChrisHMSFT
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ms.author: chrhoder
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keywords:
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---
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# What is Azure OpenAI?
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# What is Azure OpenAI Service?
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The Azure OpenAI service provides REST API access to OpenAI's powerful language models including the GPT-3, Codex and Embeddings model series. These models can be easily adapted to your specific task including but not limited to content generation, summarization, semantic search, and natural language to code translation. Users can access the service through REST APIs, Python SDK, or our web-based interface in the Azure OpenAI Studio.
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Azure OpenAI Service provides REST API access to OpenAI's powerful language models including the GPT-3, Codex and Embeddings model series. These models can be easily adapted to your specific task including but not limited to content generation, summarization, semantic search, and natural language to code translation. Users can access the service through REST APIs, Python SDK, or our web-based interface in the Azure OpenAI Studio.
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### Features overview
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## Responsible AI
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At Microsoft, we're committed to the advancement of AI driven by principles that put people first. Generative models such as the ones available in the Azure OpenAI service have significant potential benefits, but without careful design and thoughtful mitigations, such models have the potential to generate incorrect or even harmful content. Microsoft has made significant investments to help guard against abuse and unintended harm, which includes requiring applicants to show well-defined use cases, incorporating Microsoft’s <ahref="https://www.microsoft.com/ai/responsible-ai?activetab=pivot1:primaryr6"target="_blank">principles for responsible AI use</a>, building content filters to support customers, and providing responsible AI implementation guidance to onboarded customers.
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At Microsoft, we're committed to the advancement of AI driven by principles that put people first. Generative models such as the ones available in Azure OpenAI have significant potential benefits, but without careful design and thoughtful mitigations, such models have the potential to generate incorrect or even harmful content. Microsoft has made significant investments to help guard against abuse and unintended harm, which includes requiring applicants to show well-defined use cases, incorporating Microsoft’s <ahref="https://www.microsoft.com/ai/responsible-ai?activetab=pivot1:primaryr6"target="_blank">principles for responsible AI use</a>, building content filters to support customers, and providing responsible AI implementation guidance to onboarded customers.
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## How do I get access to Azure OpenAI?
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How do I get access to Azure OpenAI Service?
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How do I get access to Azure OpenAI?
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Access is currently limited as we navigate high demand, upcoming product improvements, and <ahref="https://www.microsoft.com/ai/responsible-ai?activetab=pivot1:primaryr6"target="_blank">Microsoft’s commitment to responsible AI</a>. For now, we're working with customers with an existing partnership with Microsoft, lower risk use cases, and those committed to incorporating mitigations. In addition to applying for initial access, all solutions using the Azure OpenAI service are required to go through a use case review before they can be released for production use.
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Access is currently limited as we navigate high demand, upcoming product improvements, and <ahref="https://www.microsoft.com/ai/responsible-ai?activetab=pivot1:primaryr6"target="_blank">Microsoft’s commitment to responsible AI</a>. For now, we're working with customers with an existing partnership with Microsoft, lower risk use cases, and those committed to incorporating mitigations. In addition to applying for initial access, all solutions using Azure OpenAI are required to go through a use case review before they can be released for production use.
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More specific information is included in the application form. We appreciate your patience as we work to responsibly enable broader access to the Azure OpenAI service.
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More specific information is included in the application form. We appreciate your patience as we work to responsibly enable broader access to Azure OpenAI.
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Apply here for initial access or for a production review:
All solutions using the Azure OpenAI service are also required to go through a use case review before they can be released for production use, and are evaluated on a case-by-case basis. In general, the more sensitive the scenario the more important risk mitigation measures will be for approval.
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All solutions using Azure OpenAI are also required to go through a use case review before they can be released for production use, and are evaluated on a case-by-case basis. In general, the more sensitive the scenario the more important risk mitigation measures will be for approval.
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## Comparing Azure OpenAI and OpenAI
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### Tokens
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OpenAI Enterprise processes text by breaking it down into tokens. Tokens can be words or just chunks of characters. For example, the word “hamburger” gets broken up into the tokens “ham”, “bur” and “ger”, while a short and common word like “pear” is a single token. Many tokens start with a whitespace, for example “ hello” and “ bye”.
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Azure OpenAI processes text by breaking it down into tokens. Tokens can be words or just chunks of characters. For example, the word “hamburger” gets broken up into the tokens “ham”, “bur” and “ger”, while a short and common word like “pear” is a single token. Many tokens start with a whitespace, for example “ hello” and “ bye”.
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The total number of tokens processed in a given request depends on the length of your input, output and request parameters. The quantity of tokens being processed will also affect your response latency and throughput for the models.
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### Resources
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The Azure OpenAI service is a new product offering on Azure. You can get started with the Azure OpenAI service the same way as any other Azure product where you [create a resource](how-to/create-resource.md), or instance of the service, in your Azure Subscription. You can read more about Azure's [resource management design](../../azure-resource-manager/management/overview.md).
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Azure OpenAI is a new product offering on Azure. You can get started with Azure OpenAI the same way as any other Azure product where you [create a resource](how-to/create-resource.md), or instance of the service, in your Azure Subscription. You can read more about Azure's [resource management design](../../azure-resource-manager/management/overview.md).
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### Deployments
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Once you create an Azure OpenAI Resource, you must deploy a model before you can start making API calls and generating text. This action can be done using the Deployment APIs. These APIs allow you to specify the model you wish to use.
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### In-context learning
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The models used by the Azure OpenAI service use natural language instructions and examples provided during the generation call to identify the task being asked and skill required. When you use this approach, the first part of the prompt includes natural language instructions and/or examples of the specific task desired. The model then completes the task by predicting the most probable next piece of text. This technique is known as "in-context" learning. These models aren't retrained during this step but instead give predictions based on the context you include in the prompt.
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The models used by Azure OpenAI use natural language instructions and examples provided during the generation call to identify the task being asked and skill required. When you use this approach, the first part of the prompt includes natural language instructions and/or examples of the specific task desired. The model then completes the task by predicting the most probable next piece of text. This technique is known as "in-context" learning. These models aren't retrained during this step but instead give predictions based on the context you include in the prompt.
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There are three main approaches for in-context learning: Few-shot, one-shot and zero-shot. These approaches vary based on the amount of task-specific data that is given to the model:
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title: Azure OpenAI REST API reference
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title: Azure OpenAI Service REST API reference
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titleSuffix: Azure OpenAI
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description: Learn how to use the Azure OpenAI REST API. In this article, you'll learn about authorization options, how to structure a request and receive a response.
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services: cognitive-services
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ms.custom:
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# Azure OpenAI REST API reference
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# Azure OpenAI Service REST API reference
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This article provides details on the REST API endpoints for the Azure OpenAI Service, a service in the Azure Cognitive Services suite. The REST APIs are broken up into two categories:
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title: What's new in Azure OpenAI?
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title: What's new in Azure OpenAI Service?
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titleSuffix: Azure Cognitive Services
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description: Learn about the latest news and features updates for Azure OpenAI
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# What's new in Azure OpenAI
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# What's new in Azure OpenAI Service
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## January 2023
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### New Features
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***Service GA**. Azure OpenAI is now generally available.
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***Service GA**. Azure OpenAI Service is now generally available.
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***New models**: Addition of the latest text model, text-davinci-003 (East US, West Europe), text-ada-embeddings-002 (East US, South Central US, West Europe)
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