Develop apps that use Azure AI services
This article provides documentation, samples and other resources for learning how to develop applications that use Azure OpenAI Service and other Azure AI Services.
Azure AI reference templates
Azure AI reference templates provide you with well-maintained, easy to deploy reference implementations. These ensure a high-quality starting point for your intelligent applications. The end-to-end solutions provide popular, comprehensive reference applications. The building blocks are smaller-scale samples that focus on specific scenarios and tasks.
End-to-end solutions
| Link | Description |
|---|---|
| Get started with the .NET enterprise chat sample using RAG | An article that walks you through deploying and using the Enterprise chat app sample for .NET. This sample is a complete end-to-end solution demonstrating the Retrieval-Augmented Generation (RAG) pattern running in Azure, using Azure AI Search for retrieval and Azure OpenAI large language models to power ChatGPT-style and Q&A experiences. |
| Build an AI assistant using RAG | This sample is a complete end-to-end solution demonstrating how to design and implement a Q&A AI assistant, which uses the Embeddings API and Completions API in Azure OpenAI Service, as well as the vector database in Azure Cosmos DB. |
Building blocks
| Link | Description |
|---|---|
| Build a chat app with Azure OpenAI (Python) | A simple Python Quart app that streams responses from ChatGPT to an HTML/JS frontend using JSON Lines over a ReadableStream. (The Python code is provided as a reference and could be adapted to .NET.) |
| Build a LangChain with Azure OpenAI (Python) | A sample shows how to take a human prompt as HTTP Get or Post input, calculates the completions using chains of human input and templates. This is a starting point that can be used for more sophisticated chains. (The Python code is provided as a reference and could be adapted to .NET.) |
| Build a ChatGPT Plugin with Azure Container Apps (Python) | A sample for creating ChatGPT Plugin using GitHub Codespaces, VS Code, and Azure. The sample includes templates to deploy the plugin to Azure Container Apps using the Azure Developer CLI. (The Python code is provided as a reference and could be adapted to .NET.) |
| Azure AI .NET Template Gallery | For the full list of Azure AI templates, visit our gallery. All app templates in our gallery can be spun up and deployed using a single command: azd up. |
| Smart load balancing with Azure Container Apps | This solution is built using the high-performance YARP C# reverse-proxy framework from Microsoft. However, you don't need to understand C# to use it, you can just build the provided Docker image. This is an alternative solution to the API Management OpenAI smart load balancer, with the same logic. |
| Smart load balancing with Azure API Management | The enterprise solution shows how to create an Azure API Management Policy to seamlessly expose a single endpoint to your applications while keeping an efficient logic to consume two or more OpenAI or any API backends based on availability and priority. |
Azure OpenAI
End-to-end solutions
| Link | Description |
|---|---|
| Get started with the .NET enterprise chat sample using RAG | An article that walks you through deploying and using the Enterprise chat app sample for .NET. This sample is a complete end-to-end solution demonstrating the Retrieval-Augmented Generation (RAG) pattern running in Azure, using Azure AI Search for retrieval and Azure OpenAI large language models to power ChatGPT-style and Q&A experiences. |
Building blocks
| Link | Description |
|---|---|
| Vector Similarity Search with Azure Cache for Redis Enterprise (Python) | An article that walks you through using Azure Cache for Redis as a backend vector store for RAG scenarios. (The Python code is provided as a reference and could be adapted to .NET.) |
| OpenAI solutions with your own data using PostgreSQL (Python) | An article discussing how Azure Database for PostgreSQL Flexible Server and Azure Cosmos DB for PostgreSQL supports the pgvector extension, along with an overview, scenarios, etc. (The Python code is provided as a reference and could be adapted to .NET.) |
SDKs and other samples/guidance
| Link | Description |
|---|---|
| Azure OpenAI SDK for .NET | The GitHub source version of the Azure OpenAI client library for .NET is an adaptation of OpenAI's REST APIs that provides an idiomatic interface and rich integration with the rest of the Azure SDK ecosystem. It can connect to Azure OpenAI resources or to the non-Azure OpenAI inference endpoint, making it a great choice for even non-Azure OpenAI development. |
| Azure OpenAI SDK Releases | Links to all Azure OpenAI SDK library packages, including links for .NET, Java, JavaScript and Go. |
| Azure.AI.OpenAI NuGet package | The NuGet version of the Azure OpenAI client library for .NET. |
| Get started using GPT-35-Turbo and GPT-4 | An article that walks you through creating a chat completion sample. |
| Completions | A collection of 10 samples that demonstrate how to use the Azure OpenAI client library for .NET to chat, stream replies, use your own data, transcribe/translate audio, generate images, etc. |
| Streaming Chat Completions | A deep link to the samples demonstrating streaming completions. |
| OpenAI with Microsoft Entra ID Role based access control | A look at authentication using Microsoft Entra ID. |
| OpenAI with Managed Identities | An article with more complex security scenarios that require Azure role-based access control (Azure RBAC). This document covers how to authenticate to your OpenAI resource using Microsoft Entra ID. |
| More samples | A collection of OpenAI samples written in .NET. |
| More guidance | The hub page for Azure OpenAI Service documentation. |
Other Azure AI services
End-to-end solutions
| Link | Description |
|---|---|
| Captioning and Call Center Transcription | A repo containing samples for captions and transcriptions in a call center scenario. |
| Use Form Recognizer to automate a paper based process using the New patient registration with Form Recognizer workshop. (Code) | A complete walkthrough of an Azure AI Document Intelligence scenario in a workshop format. |
Building blocks
| Link | Description |
|---|---|
| Use Speech to converse with OpenAI | An article detailing how to use Azure AI Speech to converse with Azure OpenAI Service. The text recognized by the Speech service is sent to Azure OpenAI. Speech service then synthesizes the text response from Azure OpenAI. |
| Translate documents from and into more than 100 different languages | An article showing how to translate local files or network files in many different formats, to more than 100 different languages. Supported formats include HTML, PDF, all Office document formats, Markdown, MHTML, Outlook, MSG, XLIFF, CSV, TSV and plain text. |
SDKs and samples/guidance
| Link | Description |
|---|---|
| Integrate Speech into your apps with Speech SDK Samples | A repo of samples for the Azure Cognitive Services Speech SDK. Links to samples for speech recognition, translation, speech synthesis, and more. |
| Azure AI Document Intelligence SDK | Azure AI Document Intelligence (formerly Form Recognizer) is a cloud service that uses machine learning to analyze text and structured data from documents. The Document Intelligence software development kit (SDK) is a set of libraries and tools that enable you to easily integrate Document Intelligence models and capabilities into your applications. |
| Extract structured data from forms, receipts, invoices, and cards using Form Recognizer in .NET | A repo of samples for the Azure.AI.FormRecognizer client library. |
| Extract, classify, and understand text within documents using Text Analytics in .NET | The client Library for Text Analytics. This is part of the Azure AI Language service, which provides Natural Language Processing (NLP) features for understanding and analyzing text. |
| Document Translation in .NET | A quickstart article that details how to use Document Translation to translate a source document into a target language while preserving structure and text formatting. |
| Question Answering in .NET | A quickstart article to get an answer (and confidence score) from a body of text that you send along with your question. |
| Conversational Language Understanding in .NET | The client library for Conversational Language Understanding (CLU), a cloud-based conversational AI service, which can extract intents and entities in conversations and acts like an orchestrator to select the best candidate to analyze conversations to get best response from apps like Qna, Luis, and Conversation App. |
| Analyze images | Sample code and setup documents for the Microsoft Azure AI Image Analysis SDK |
Azure AI reference templates
Azure AI reference templates provide you with well-maintained, easy to deploy reference implementations. These ensure a high-quality starting point for your intelligent applications. The end-to-end solutions provide popular, comprehensive reference applications. The building blocks are smaller-scale samples that focus on specific scenarios and tasks.
End-to-end solutions
| Link | Description |
|---|---|
| Get started with the Python enterprise chat sample using RAG | An article that walks you through deploying and using the Enterprise chat app sample for Python. This sample is a complete end-to-end solution demonstrating the Retrieval-Augmented Generation (RAG) pattern running in Azure, using Azure AI Search for retrieval and Azure OpenAI large language models to power ChatGPT-style and Q&A experiences. |
Building blocks
| Building Block | Description |
|---|---|
| Build a chat app with Azure OpenAI in Python | A simple Python Quart app that streams responses from ChatGPT to an HTML/JS frontend using JSON Lines over a ReadableStream. |
| Build a LangChain with Azure OpenAI in Python | An Azure Functions sample that shows how to take a human prompt as HTTP Get or Post input, calculates the completions using chains of human input and templates. This is a starting point that can be used for more sophisticated chains. |
| Build a ChatGPT Plugin with Azure Container Apps in Python | A sample for creating ChatGPT Plugin using GitHub Codespaces, VS Code, and Azure. The sample includes templates to deploy the plugin to Azure Container Apps using the Azure Developer CLI. |
| Summarize Text using Azure AI Language with Azure Functions | Take text documents as input, summarize using Azure AI Language, and then output to another text document using Azure Functions. |
| Azure AI Python Template Gallery | For the full list of Azure AI templates, visit our gallery. All app templates in our gallery can be spun up and deployed using a single command: azd up. |
| Smart load balancing with Azure Container Apps | This sample solution is built using the high-performance YARP C# reverse-proxy framework from Microsoft. However, you don't need to understand C# to use it, you can just build the provided Docker image. This is an alternative solution to the API Management OpenAI smart load balancer, with the same logic. |
| Smart load balancing with Azure API Management | The enterprise sample solution shows how to create an Azure API Management Policy to seamlessly expose a single endpoint to your applications while keeping an efficient logic to consume two or more OpenAI or any API backends based on availability and priority. |
| Evaulate your chat app | Evaluate a chat app's answers against a set of correct or ideal answers (known as ground truth). The evaulation tools can be used with any Chat API which conforms to the Chat protocol. |
| Load test your chat app with Locust | Use a Locust test to validate your chat app can handle the expected load. If your chat app doesn't scale on your App Service due to Azure OpenAI TPM limits, add a load balancer and test your load again. Smart load balancers include Azure API Management and Azure Container Apps. |
Azure OpenAI
End-to-end solutions
| Link | Description |
|---|---|
| Get started with the Python enterprise chat sample using RAG | An article that walks you through deploying and using the Enterprise chat app sample for Python. This sample is a complete end-to-end solution demonstrating the Retrieval-Augmented Generation (RAG) pattern running in Azure, using Azure AI Search for retrieval and Azure OpenAI large language models to power ChatGPT-style and Q&A experiences. |
Building blocks
| Link | Description |
|---|---|
| Build a chat app with Azure OpenAI in Python | A simple Python Quart app that streams responses from ChatGPT to an HTML/JS frontend using JSON Lines over a ReadableStream. |
| Build a LangChain with Azure OpenAI in Python | A sample shows how to take a human prompt as HTTP Get or Post input, calculates the completions using chains of human input and templates. This is a starting point that can be used for more sophisticated chains. |
| Build a ChatGPT Plugin with Azure Container Apps in Python | A sample for creating ChatGPT Plugin using GitHub Codespaces, VS Code, and Azure. The sample includes templates to deploy the plugin to Azure Container Apps using the Azure Developer CLI. |
| Vector Similarity Search with Azure Cache for Redis Enterprise | A walkthrough using Azure Cache for Redis as a backend vector store for RAG scenarios. |
| OpenAI solutions with your own data using PostgreSQL | An article discussing how Azure Database for PostgreSQL Flexible Server and Azure Cosmos DB for PostgreSQL supports the pgvector extension, along with an overview, scenarios, etc. |
SDKs and other samples/guidance
| Link | Description |
|---|---|
| OpenAI SDK for Python | The GitHub source code version of the OpenAI Python library provides convenient access to the OpenAI API from applications written in the Python language. |
| Azure OpenAI SDK Releases | Links to all Azure OpenAI SDK library packages, including links for .NET, Java, JavaScript and Go. |
| openai Python Package | The PyPi version of the OpenAI Python library. |
| Get started using GPT-35-Turbo and GPT-4 | An article that walks you through creating a chat completion sample. |
| Streaming Chat completions | A notebook containing example of getting chat completions to work using the Azure endpoints. This example focuses on chat completions but also touches on some other operations that are also available using the API. |
| Switch from OpenAI to Azure OpenAI | Guidance article on the small changes you need to make to your code in order to swap back and forth between OpenAI and the Azure OpenAI Service. |
| Embeddings | A notebook demonstrating operations how to use embeddings that can be done using the Azure endpoints. This example focuses on embeddings but also touches some other operations that are also available using the API. |
| Deploy a model and generate text | An article with minimal, straightforward detailing steps to programmatically chat. |
| OpenAI with Microsoft Entry ID Role based access control | A look at authentication using Microsoft Entra ID. |
| OpenAI with Managed Identities | An article with more complex security scenarios requires Azure role-based access control (Azure RBAC). This document covers how to authenticate to your OpenAI resource using Microsoft Entra ID. |
| More samples | A compilation of useful Azure OpenAI Service resources and code samples to help you get started and accelerate your technology adoption journey. |
| More guidance | The hub page for Azure OpenAI Service documentation. |
Other Azure AI services
End-to-end solutions
| Link | Description |
|---|---|
| Captioning and Call Center Transcription | A repo containing samples for captions and transcriptions in a call center scenario. |
| Use Document Intelligence to automate a paper based process using the New patient registration with Form Recognizer workshop (Code) | A workshop style presentation that walks you through how to use Document Intelligence to convert and automate a paper-based process. |
Building blocks
| Link | Description |
|---|---|
| Use Speech to converse with OpenAI | Use Azure AI Speech to converse with Azure OpenAI Service. The text recognized by the Speech service is sent to Azure OpenAI. The Speech service synthesizes the text response from Azure OpenAI. |
| Translate documents from and into more than 100 different languages using Document Translation sample apps | A repo containing both a Command Line tool and Windows application that serves as a local interface to the Azure Document Translation service for Windows, macOS and Linux. |
SDKs and samples/guidance
| Link | Description |
|---|---|
| Integrate Speech into your apps with Speech SDK Samples | Samples for the Azure Cognitive Services Speech SDK. Links to samples for speech recognition, translation, speech synthesis, and more. |
| Azure AI Document Intelligence SDK | Azure AI Document Intelligence (formerly Form Recognizer) is a cloud service that uses machine learning to analyze text and structured data from documents. The Document Intelligence software development kit (SDK) is a set of libraries and tools that enable you to easily integrate Document Intelligence models and capabilities into your applications. |
| Extract structured data from forms, receipts, invoices, and cards using Form Recognizer in Python | Samples for the Azure.AI.FormRecognizer client library. |
| Extract, classify, and understand text within documents using Text Analytics in Python | The client Library for Text Analytics. This is part of the Azure AI Language service, which provides Natural Language Processing (NLP) features for understanding and analyzing text. |
| Document Translation in Python | A quickstart article that uses Document Translation to translate a source document into a target language while preserving structure and text formatting. |
| Question Answering in Python | A quickstart article with steps to get an answer (and confidence score) from a body of text that you send along with your question. |
| Conversational Language Understanding in Python | The client library for Conversational Language Understanding (CLU), a cloud-based conversational AI service, which can extract intents and entities in conversations and acts like an orchestrator to select the best candidate to analyze conversations to get best response from apps like Qna, Luis, and Conversation App. |
| Analyze images | Sample code and setup documents for the Microsoft Azure AI Image Analysis SDK |
| Azure AI Content Safety SDK for Python | Detects harmful user-generated and AI-generated content in applications and services. Content Safety includes text and image APIs that allow you to detect material that is harmful. |
Azure AI reference templates
Azure AI reference templates provide you with well-maintained, easy to deploy reference implementations. These ensure a high-quality starting point for your intelligent applications. The end-to-end solutions provide popular, comprehensive reference applications. The building blocks are smaller-scale samples that focus on specific scenarios and tasks.
End-to-end solutions
| Link | Description |
|---|---|
| Get started with the JavaScript enterprise chat sample using RAG | An article that walks you through deploying and using the Enterprise chat app sample for JavaScript. This sample is a complete end-to-end solution demonstrating the Retrieval-Augmented Generation (RAG) pattern running in Azure, using Azure AI Search for retrieval and Azure OpenAI large language models to power ChatGPT-style and Q&A experiences. |
- Demo video - JavaScript fullstack
- Demo video - JavaScript frontend with Python backend
Building blocks
| Link | Description |
|---|---|
| Build a chat app with Azure OpenAI (Python) | A simple Python Quart app that streams responses from ChatGPT to an HTML/JS frontend using JSON Lines over a ReadableStream. (The Python code is provided as a reference and could be adapted to JavaScript.) |
| Build a LangChain with Azure OpenAI (Python) | A sample shows how to take a human prompt as HTTP Get or Post input, calculates the completions using chains of human input and templates. This is a starting point that can be used for more sophisticated chains. (The Python code is provided as a reference and could be adapted to JavaScript.) |
| Build a ChatGPT Plugin with Azure Container Apps (Python) | A sample for creating ChatGPT Plugin using GitHub Codespaces, VS Code, and Azure. The sample includes templates to deploy the plugin to Azure Container Apps using the Azure Developer CLI. (The Python code is provided as a reference and could be adapted to JavaScript.) |
| Azure AI JavaScript Template Gallery | For the full list of Azure AI templates, visit our gallery. All app templates in our gallery can be spun up and deployed using a single command: azd up. |
| Smart load balancing with Azure Container Apps | This sample solution is built using the high-performance YARP C# reverse-proxy framework from Microsoft. However, you don't need to understand C# to use it, you can just build the provided Docker image. This is an alternative solution to the API Management OpenAI smart load balancer, with the same logic. |
| Smart load balancing with Azure API Management | The enterprise solution shows how to create an Azure API Management Policy to seamlessly expose a single endpoint to your applications while keeping an efficient logic to consume two or more OpenAI or any API backends based on availability and priority. |
| Evaulate your chat app | Evaluate a chat app's answers against a set of correct or ideal answers (known as ground truth). The evaulation tools can be used with any Chat API which conforms to the Chat protocol. |
Azure OpenAI
End-to-end solutions
| Link | Description |
|---|---|
| Get started with the JavaScript enterprise chat sample using RAG | An article that walks you through deploying and using the Enterprise chat app sample for JavaScript. This sample is a complete end-to-end solution demonstrating the Retrieval-Augmented Generation (RAG) pattern running in Azure, using Azure AI Search for retrieval and Azure OpenAI large language models to power ChatGPT-style and Q&A experiences. |
Building blocks
| Link | Description |
|---|---|
| Vector Similarity Search with Azure Cache for Redis Enterprise (Python) | A walkthrough of using Azure Cache for Redis as a backend vector store for RAG scenarios. (The Python code is provided as a reference and could be adapted to JavaScript.) |
| OpenAI solutions with your own data using PostgreSQL (Python) | An article discussing how Azure Database for PostgreSQL Flexible Server and Azure Cosmos DB for PostgreSQL supports the pgvector extension, along with an overview, scenarios, etc. (The Python code is provided as a reference and could be adapted to JavaScript.) |
SDKs
| Package | Source code | Releases | npm |
|---|---|---|---|
| @azure/openai | Source code | Releases | Package |
Samples and guidance
| Link | Description |
|---|---|
| Get started using GPT-35-Turbo and GPT-4 | An article that walks you through creating a chat completion sample. |
| Completions | A simple example demonstrating how to get completions for the provided prompt. |
| Streaming Chat Completions | A simple example demonstrating how to use streaming chat completions. |
| Switch from OpenAI to Azure OpenAI | Article with guidance on the small changes you need to make to your code in order to swap back and forth between OpenAI and the Azure OpenAI Service. |
| OpenAI with Microsoft Entra ID Role based access control | A look at authentication using Microsoft Entra ID. |
| OpenAI with Managed Identities | An article detailing more complex security scenarios require Azure role-based access control (Azure RBAC). This document covers how to authenticate to your OpenAI resource using Microsoft Entra ID. |
| More samples | OpenAI samples covering a range of scenarios. |
| More guidance | The hub page for Azure OpenAI Service documentation. |
Open source integration
SDKs
| Package | Source code | Releases | npm |
|---|---|---|---|
| @langchain/azure-openai | Source code | Releases | Package |
Other Azure AI services
End-to-end solutions
| Link | Description |
|---|---|
| Captioning and Call Center Transcription | A repo containing samples for captions and transcriptions in a call center scenario. |
Building blocks
| Link | Description |
|---|---|
| Use Speech to converse with OpenAI (C# and Python) | An article that uses Azure AI Speech to converse with Azure OpenAI Service. The text recognized by the Speech service is sent to Azure OpenAI. The Speech service synthesizes the text response from Azure OpenAI. (The C# and Python code is provided as a reference and could be adapted to JavaScript.) |
SDKs
| Link | Description |
|---|---|
| Azure AI Document Intelligence SDK | Azure AI Document Intelligence (formerly Form Recognizer) is a cloud service that uses machine learning to analyze text and structured data from documents. The Document Intelligence software development kit (SDK) is a set of libraries and tools that enable you to easily integrate Document Intelligence models and capabilities into your applications. |
Samples and guidance
| Link | Description |
|---|---|
| Integrate Speech into your apps with Speech SDK Samples | A collection of samples for the Azure Cognitive Services Speech SDK. Links to samples for speech recognition, translation, speech synthesis, and more. |
| Extract structured data from forms, receipts, invoices, and cards using Form Recognizer in JavaScript | A collection of samples for the Azure.AI.FormRecognizer client library. |
| Extract, classify, and understand text within documents using Text Analytics in JavaScript | The client Library for Text Analytics. This is part of the Azure AI Language service, which provides Natural Language Processing (NLP) features for understanding and analyzing text. |
| Document Translation in JavaScript | A quickstart article that uses Document Translation to translate a source document into a target language while preserving structure and text formatting. |
| Analyze images | Sample code and setup documents for the Microsoft Azure AI Image Analysis SDK. |
Azure AI reference templates
Azure AI reference templates provide you with well-maintained, easy to deploy reference implementations. These ensure a high-quality starting point for your intelligent applications. The end-to-end solutions provide popular, comprehensive reference applications. The building blocks are smaller-scale samples that focus on specific scenarios and tasks.
End-to-end solutions
| Link | Description |
|---|---|
| Get started with the Java enterprise chat sample using RAG | An article that walks you through deploying and using the Enterprise chat app sample for Java. This sample is a complete end-to-end solution demonstrating the Retrieval-Augmented Generation (RAG) pattern running in Azure, using Azure AI Search for retrieval and Azure OpenAI large language models to power ChatGPT-style and Q&A experiences. |
Building blocks
| Link | Description |
|---|---|
| Build a chat app with Azure OpenAI (Python) | A simple Python Quart app that streams responses from ChatGPT to an HTML/JS frontend using JSON Lines over a ReadableStream. (The Python code is provided as a reference and could be adapted to Java.) |
| Build a LangChain with Azure OpenAI (Python) | A sample shows how to take a human prompt as HTTP Get or Post input, calculates the completions using chains of human input and templates. This is a starting point that can be used for more sophisticated chains. (The Python code is provided as a reference and could be adapted to Java.) |
| Build a ChatGPT Plugin with Azure Container Apps (Python) | A sample for creating ChatGPT Plugin using GitHub Codespaces, VS Code, and Azure. The sample includes templates to deploy the plugin to Azure Container Apps using the Azure Developer CLI. (The Python code is provided as a reference and could be adapted to Java.) |
| Azure AI Java Template Gallery | For the full list of Azure AI templates, visit our gallery. All app templates in our gallery can be spun up and deployed using a single command: azd up. |
| Smart load balancing with Azure Container Apps | This sample solution is built using the high-performance YARP C# reverse-proxy framework from Microsoft. However, you don't need to understand C# to use it, you can just build the provided Docker image. This is an alternative solution to the API Management OpenAI smart load balancer, with the same logic. |
| Smart load balancing with Azure API Management | The enterprise solution shows how to create an Azure API Management Policy to seamlessly expose a single endpoint to your applications while keeping an efficient logic to consume two or more OpenAI or any API backends based on availability and priority. |
Azure OpenAI
End-to-end solutions
| Link | Description |
|---|---|
| Get started with the Java enterprise chat sample using RAG | An article that walks you through deploying and using the Enterprise chat app sample for Java. This sample is a complete end-to-end solution demonstrating the Retrieval-Augmented Generation (RAG) pattern running in Azure, using Azure AI Search for retrieval and Azure OpenAI large language models to power ChatGPT-style and Q&A experiences. |
Building blocks
| Link | Description |
|---|---|
| Vector Similarity Search with Azure Cache for Redis Enterprise (Python) | An article that walks you through using Azure Cache for Redis as a backend vector store for RAG scenarios. (The Python code is provided as a reference and could be adapted to Java.) |
| OpenAI solutions with your own data using PostgreSQL (Python) | An article discussing how Azure Database for PostgreSQL Flexible Server and Azure Cosmos DB for PostgreSQL supports the pgvector extension, along with an overview, scenarios, etc. (The Python code is provided as a reference and could be adapted to Java.) |
SDKs
| Package | Source code | Releases | Maven |
|---|---|---|---|
| azure-ai-openai | Source code | Releases | Maven package |
| azure-ai-openai-assistants | Source code | Releases | Maven package |
Samples and guidance
| Link | Description |
|---|---|
| Get started using GPT-35-Turbo and GPT-4 | An article that walks you through creating a chat completion sample. |
| Completions | A simple example demonstrating how to get completions for the provided prompt. |
| Streaming Chat Completions | A simple example demonstrating how to use streaming chat completions. |
| Switch from OpenAI to Azure OpenAI | An article with guidance on the small changes you need to make to your code in order to swap back and forth between OpenAI and the Azure OpenAI Service. |
| OpenAI with Microsoft Entra ID Role based access control | An article that looks at authentication using Microsoft Entra ID. |
| OpenAI with Managed Identities | An article detailing more complex security scenarios that require Azure role-based access control (Azure RBAC). This document covers how to authenticate to your OpenAI resource using Microsoft Entra ID. |
| More Samples | The Azure OpenAI service samples are a set of self-contained Java programs that demonstrate interacting with Azure OpenAI service using the client library. Each sample focuses on a specific scenario and can be executed independently. |
| More guidance | The hub page for Azure OpenAI Service documentation. |
Open Source integration
SDKs
| Package | Source code | Releases | Maven |
|---|---|---|---|
| langchain4j-azure-open-ai | Source code | Releases | Maven package |
| langchain4j-azure-ai-search | Source code | Releases | Maven |
| langchain4j-document-loader-azure-storage-blob | n/a | Releases | Maven |
Other Azure AI services
End-to-end solutions
| Link | Description |
|---|---|
| Captioning and Call Center Transcription | A repo containing samples for captions and transcriptions in a call center scenario. |
SDKs
| Link | Description |
|---|---|
| Azure AI Document Intelligence SDK | Azure AI Document Intelligence (formerly Form Recognizer) is a cloud service that uses machine learning to analyze text and structured data from documents. The Document Intelligence software development kit (SDK) is a set of libraries and tools that enable you to easily integrate Document Intelligence models and capabilities into your applications. |
Samples and guidance
| Link | Description |
|---|---|
| Integrate Speech into your apps with Speech SDK Samples | A collection of samples for the Azure Cognitive Services Speech SDK. Links to samples for speech recognition, translation, speech synthesis, and more. |
| Extract structured data from forms, receipts, invoices, and cards using Form Recognizer in Java | A collection of samples for the Azure.AI.FormRecognizer client library. |
| Extract, classify, and understand text within documents using Text Analytics in Java | The client Library for Text Analytics. This is part of the Azure AI Language service, which provides Natural Language Processing (NLP) features for understanding and analyzing text. |
| Document Translation in Java | A quickstart article that explains how to use Document Translation to translate a source document into a target language while preserving structure and text formatting. |
| Analyze images | Sample code and setup documents for the Microsoft Azure AI Image Analysis SDK |
OpenAI for Go developers
| Link | Description |
|---|---|
| Azure OpenAI SDK for Go | The GitHub source version of the Azure OpenAI SDK for Go. |
| Azure OpenAI SDK Releases | Links to all Azure OpenAI SDK library packages, including links for .NET, Java, JavaScript and Go. |
| Package (pkg.go.dev) | The Go package version of Azure OpenAI client module for Go. |
| Get started using GPT-35-Turbo and GPT-4 | An article that walks you through creating a chat completion sample. |
| ChatCompletions | A simple example demonstrating how to implement completions. |
| ChatCompletions using Functions | A simple example demonstrating how to implement completions using Functions. |
| Streaming Chat Completions | A simple example demonstrating how to implement streaming completions. |
| Image generation | A simple example of implementing image generation. |
| Embeddings | A simple example demonstrating how to create embeddings. |
| Other examples | The Go package version of documentation for the OpenAI client module for Go. |
| More guidance | The hub page for Azure OpenAI Service documentation. |
Secure your Azure AI resources
| Link | Description |
|---|---|
| OpenAI with Microsoft Entra ID Role based access control | A look at authentication using Microsoft Entra ID. |
| OpenAI with Managed Identities | An article detailing more complex security scenarios that require Azure role-based access control (Azure RBAC). This document covers how to authenticate to your OpenAI resource using Microsoft Entra ID. |
Speech/Vision
| Link | Description |
|---|---|
| Captioning and Call Center Transcription in Go | A repo containing samples for captions and transcriptions in a call center scenario. |
| Integrate Speech into your apps with Speech SDK for Go | The source for the Azure Cognitive Services Speech SDK. |
Language
| Link | Description |
|---|---|
| Extract, classify, and understand text within documents using Text Analytics in Go | The client library for Text Analytics, which is part of the Azure Cognitive Service for Language, a cloud-based service that provides Natural Language Processing (NLP) features for understanding and analyzing text. |
| Document Translation in Go | A quickstart article showing how to use Document Translation to translate a source document into a target language while preserving structure and text formatting. |
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