Announcing a new OpenAI feature for developers on Azure  | Microsoft Azure Blog (2024)

We are thrilled to announce the launch of OpenAI’s latest model, GPT-4o Next.

We are thrilled to announce the launch of OpenAI’s latest model on Azure. This new model, officially named GPT-4o-2024-08-06, brings innovative features designed to elevate developer experiences on Azure. Specifically, the new model focuses on enhancing productivity through Structured Outputs, like JSON Schemas, for the new GPT-4o and GPT-4o mini models.

A focus on Structured Outputs

GPT-4o was first announced in May 2024, as OpenAI’s new multimodal model, followed by GPT-4o mini in July 2024. Today’s version is designed with a specific use case in mind: simplifying the process of generating well-defined, structured outputs from AI models. This feature is particularly valuable for developers who need to validate and format AI outputs into structures like JSON Schemas. Developers often face challenges validating and formatting AI outputs into well-defined structures like JSON Schemas.

Structured Outputs addresses this by allowing developers to specify the desired output format directly from the AI model. This feature enables developers to define a JSON Schema for text outputs, simplifying the process of generating data payloads that can seamlessly integrate with other systems or enhance user experiences.

Use cases for JSON

JSON Schema is essential for defining the structure and constraints of JSON documents, ensuring they follow specific formats with mandatory properties and value types. It enhances data understandability through semantic annotation and serves as a domain-specific language for optimized application requirements. Development teams use JSON Schema to maintain consistency across platforms, drive model-driven UI constraints, and automatically generate user interfaces. It aids in data serialization, security testing, and partial validation in technical scenarios. JSON Schema also supports automated testing, Schema inference, and machine-readable web profiles, improving data interoperability. It standardizes validation interfaces and reporting, handles external validation, and ensures data consistency within and across documents. It can also help with customer support and how to communicate in a timely manner.

Two flavors of Structured Outputs

Structured Outputs is available in two forms:

  1. User-defined JSON Schema: This option allows developers to specify the exact JSON Schema they want the AI to follow, supported by both GPT-4o-2024-08-06 and GPT-4o-mini-2024-07-18.
  2. More Accurate Tool Output (“Strict Mode”): This limited version lets developers define specific function signatures for tool use, supported by all models that support function calling, including GPT-3.5 Turbo, GPT-4, GPT-4 Turbo, and GPT-4o models from June 2023 onwards.

Technical guidance on using Structured Outputs

To help you get started with Structured Outputs, we recommend the following approach.

Getting started with Structured Outputs

  1. Define Your JSON Schema: Determine the structure you want your AI outputs to follow. This can include required fields, data types, and other constraints.
  2. Configure the AI model: Use the Structured Outputs feature to specify your JSON Schema within the API call. This ensures that the AI output adheres to your defined structure.
  3. Integration and testing: Integrate the output into your application or system, and test thoroughly to ensure compliance with your JSON Schema.

Example use case: Customer support automation

Imagine you’re developing a customer support chatbot that needs to generate responses in a specific format for logging and analytics. By using Structured Outputs, you can define a JSON Schema that includes fields like responseText, intent, confidenceScore, and timestamp. This ensures that every response generated by the chatbot is formatted correctly, making it easier to log, analyze, and act upon.

Example API call

Here’s an example API call to illustrate how to use Structured Outputs:

{ "model": "gpt-4o-2024-08-06", "prompt": "Generate a customer support response", "structured_output": { "schema": { "type": "object", "properties": { "responseText": { "type": "string" }, "intent": { "type": "string" }, "confidenceScore": { "type": "number" }, "timestamp": { "type": "string", "format": "date-time" } }, "required": ["responseText", "intent", "confidenceScore", "timestamp"] } }}

Pricing

We will make pricing for this feature available soon. Please bookmark the Azure OpenAI Service pricing page.

Learn more about the future of AI

We’ve been rolling out several new models recently, and we understand it can be a lot to keep up with. This flurry of activity is all about empowering developer innovation. Each new model brings unique capabilities and enhancements, helping you build even more powerful and versatile applications.

The launch of this new model feature for GPT-4o and GPT-4o mini marks a significant milestone in our ongoing efforts to push the boundaries of AI capabilities. We’re excited to see how developers will leverage these new features to create innovative and impactful applications.

Azure ai studio

Craft AI solutions your way

Stay tuned for more updates and get ready to experience the future of AI with these new developer features for GPT-4o and mini. Start experimenting in the Azure OpenAI Playground.

Announcing a new OpenAI feature for developers on Azure  | Microsoft Azure Blog (2024)

FAQs

What is the difference between Azure OpenAI and OpenAI? ›

Microsoft Azure OpenAI— Microsoft Azure OpenAI is a collaboration between Microsoft and OpenAI that provides Azure customers access to OpenAI's powerful models. Their partnership extends the benefits of implementing AI models with Azure's cloud services.

Is GPT 4 available in Azure OpenAI? ›

GPT-4o mini, announced by OpenAI today, is available simultaneously on Azure AI, supporting text processing capabilities with excellent speed and with image, audio, and video coming later. Try it at no cost in the Azure OpenAI Studio Playground.

What is new in OpenAI? ›

Azure OpenAI on your own data (preview) updates

Azure OpenAI On Your Data now supports private endpoints. Ability to filter access to sensitive documents. Automatically refresh your index on a schedule. Vector search and semantic search options.

What Azure OpenAI base model can you deploy to access the capabilities of Chatgpt? ›

The most capable and cost effective model in the GPT-3.5 family is GPT-3.5 Turbo, which has been optimized for chat and works well for traditional completions tasks as well. GPT-3.5 Turbo is available for use with the Chat Completions API.

What is the main advantage of using Azure OpenAI services? ›

Azure OpenAI Service offers pricing based on both Pay-As-You-Go and Provisioned Throughput Units (PTUs). Pay-As-You-Go allows you to pay for the resources you consume, making it flexible for variable workloads.

Is Azure OpenAI faster than OpenAI API? ›

The code was executed every 30 minutes for a period of 48 hours. The findings indicate that for 90% of the runs Azure OpenAI is slightly faster than OpenAI, but 10% of Azure OpenAI's runs take very long.

How are ChatGPT OpenAI and Azure OpenAI related? ›

In summary, ChatGPT is developed by OpenAI, and Azure OpenAI is the collaboration between OpenAI and Microsoft to make OpenAI's models accessible through the Azure platform.

How can developers optimize the performance of Azure OpenAI models? ›

Utilize tools like the Azure OpenAI Sizing Tool to evaluate and optimize your PTU allocations based on real usage patterns, ensuring a balanced and cost-effective deployment. Primary Resources: Cost Optimization | Microsoft Learn. GenAI Gateway Capabilities in APIM.

Is OpenAI running in Azure? ›

Yes, Azure OpenAI on your data is part of the Azure OpenAI Service and works with the models available in Azure OpenAI.

What is better than OpenAI? ›

Mistral AI

Who is it best for: Businesses and users seeking powerful and flexible AI capabilities for content creation and more. Mistral AI is a cutting-edge French company that offers state-of-the-art text generation models, providing users with a robust alternative to OpenAI's GPT.

What is the benefit of OpenAI? ›

Enhanced efficiency: OpenAI's models can automate knowledge-based tasks in ways that were previously impossible. It can also handle complex tasks like data analysis, report generation and content creation. The automation of rote tasks may help free up humans for more creative, strategic and empathetic roles.

How does Azure OpenAI work? ›

Azure OpenAI On Your Data works by sending instructions to a large language model in the form of prompts to answer user queries using your data. If there is a certain behavior that is critical to the application, you can repeat the behavior in system message to increase its accuracy.

What are Azure OpenAI embeddings? ›

The embedding is an information dense representation of the semantic meaning of a piece of text. Each embedding is a vector of floating-point numbers, such that the distance between two embeddings in the vector space is correlated with semantic similarity between two inputs in the original format.

What are the capabilities of using Azure OpenAI to generate code? ›

The Azure OpenAI Service models can generate code for you using natural language prompts, fixing bugs in completed code, and providing code comments. These models can also explain and simplify existing code to help you understand what it does and how to improve it.

How to migrate from OpenAI to Azure OpenAI? ›

For switching between OpenAI and Azure OpenAI Service endpoints, you need to make slight changes to your code. Update the authentication, model keyword argument, and other differences (Python examples below). Use environment variables for API keys and endpoints. For OpenAI, set openai.

Are OpenAI and ChatGPT the same? ›

Yes, ChatGPT is a product developed by OpenAI. It is one of the language models in the GPT (Generative Pre-trained Transformer) series created by OpenAI. ChatGPT is specifically fine-tuned for conversational interactions, making it adept at generating human-like text in a dialogue format.

What is the difference between Azure OpenAI and copilot? ›

Knowing the distinctions between them can help you select the most appropriate tool. Microsoft 365 Copilot is a general assistant, whereas custom solutions created with Azure AI Studio can be specialized for specific use cases.

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