What is Azure OpenAI Service?

 Azure OpenAI Service provides REST API access to OpenAI's powerful language models including the GPT-4, GPT-35-Turbo, and Embeddings model series. In addition, the new GPT-4 and gpt-35-turbo model series have now reached general availability. 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.

Features overview

FeatureAzure OpenAI
Models availableGPT-4 series
GPT-35-Turbo series
Embeddings series
Learn more in our Models page.
Fine-tuningAda
Babbage
Curie
Cushman
Davinci
Fine-tuning is currently unavailable to new customers.
PriceAvailable here
Virtual network support & private link supportYes, unless using Azure OpenAI on your data.
Managed IdentityYes, via Azure Active Directory
UI experienceAzure portal for account & resource management,
Azure OpenAI Service Studio for model exploration and fine tuning
Model regional availabilityModel availability
Content filteringPrompts and completions are evaluated against our content policy with automated systems. High severity content will be filtered.

How do I get access to Azure OpenAI?

How do I get access to Azure OpenAI?

Access is currently limited as we navigate high demand, upcoming product improvements, and Microsoft’s commitment to responsible AI. For now, we're working with customers with an existing partnership with Microsoft, lower risk use cases, and those committed to incorporating mitigations.

More specific information is included in the application form. We appreciate your patience as we work to responsibly enable broader access to Azure OpenAI.

Apply here for access:

Apply now

Comparing Azure OpenAI and OpenAI

Azure OpenAI Service gives customers advanced language AI with OpenAI GPT-4, GPT-3, Codex, and DALL-E models with the security and enterprise promise of Azure. Azure OpenAI co-develops the APIs with OpenAI, ensuring compatibility and a smooth transition from one to the other.

With Azure OpenAI, customers get the security capabilities of Microsoft Azure while running the same models as OpenAI. Azure OpenAI offers private networking, regional availability, and responsible AI content filtering.

Key concepts

Prompts & completions

The completions endpoint is the core component of the API service. This API provides access to the model's text-in, text-out interface. Users simply need to provide an input prompt containing the English text command, and the model will generate a text completion.

Here's an example of a simple prompt and completion:

Prompt""" count to 5 in a for loop """

Completionfor i in range(1, 6): print(i

Tokens

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”.


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.


Resources

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, or instance of the service, in your Azure Subscription. You can read more about Azure's resource management design.


Deployments

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.


Prompt engineering

GPT-3, GPT-3.5, and GPT-4 models from OpenAI are prompt-based. With prompt-based models, the user interacts with the model by entering a text prompt, to which the model responds with a text completion. This completion is the model’s continuation of the input text.


While these models are extremely powerful, their behavior is also very sensitive to the prompt. This makes prompt engineering an important skill to develop.


Prompt construction can be difficult. In practice, the prompt acts to configure the model weights to complete the desired task, but it's more of an art than a science, often requiring experience and intuition to craft a successful prompt.


Models

The service provides users access to several different models. Each model provides a different capability and price point.


GPT-4 models are the latest available models. Due to high demand access to this model series is currently only available by request. To request access, existing Azure OpenAI customers can apply by filling out this form


The DALL-E models, currently in preview, generate images from text prompts that the user provides.


Learn more about each model on our models concept page.


Next steps

Learn more about the underlying models that power Azure OpenAI.


For more such content follow, like, share my Blog.
Cloudify with Nashet 
Nashet  Ali 

Comments