Merge pull request #7440 from MicrosoftDocs/main

Auto Publish – main to live - 2025-10-02 05:03 UTC

Author: learn-build-service-prod[bot]

articles/ai-foundry/openai/api-version-lifecycle.md

@@ -6,7 +6,7 @@ manager: nitinme
 ms.service: azure-ai-foundry
 ms.subservice: azure-ai-foundry-openai
 ms.topic: conceptual 
-ms.date: 09/05/2025
+ms.date: 10/01/2025
 author: mrbullwinkle
 ms.author: mbullwin
 recommendations: false
@@ -43,29 +43,13 @@ For the initial v1 Generally Available (GA) API launch we're only supporting a s
 
 ## Code changes
 
-# [API Key](#tab/key)
+# [Python](#tab/python)
 
-### Last generation API 
+### v1 API
 
-```python
-import os
-from openai import AzureOpenAI
-
-client = AzureOpenAI(
-    api_key=os.getenv("AZURE_OPENAI_API_KEY"),  
-    api_version="2025-04-01-preview",
-    azure_endpoint="https://YOUR-RESOURCE-NAME.openai.azure.com")
-    )
-
-response = client.responses.create(
-    model="gpt-4.1-nano", # Replace with your model deployment name 
-    input="This is a test."
-)
+[Python v1 examples](./supported-languages.md)
 
-print(response.model_dump_json(indent=2)) 
-```
-
-### Next generation API
+**API Key**:
 
 ```python
 import os
@@ -88,33 +72,13 @@ print(response.model_dump_json(indent=2))
 - `base_url` passes the Azure OpenAI endpoint and `/openai/v1` is appended to the endpoint address.
 - `api-version` is no longer a required parameter with the v1 GA API.
 
-# [Microsoft Entra ID](#tab/entra)
-
-### Last generation API 
+**API Key** with environment variables set for `OPENAI_BASE_URL` and `OPENAI_API_KEY`:
 
 ```python
-from openai import AzureOpenAI
-from azure.identity import DefaultAzureCredential, get_bearer_token_provider
-
-token_provider = get_bearer_token_provider(
-    DefaultAzureCredential(), "https://cognitiveservices.azure.com/.default"
-)
-
-client = AzureOpenAI(
-  azure_endpoint = "https://YOUR-RESOURCE-NAME.openai.azure.com/", 
-  azure_ad_token_provider=token_provider,
-  api_version="2025-04-01-preview"
-)
-
-response = client.responses.create(
-    model="gpt-4.1-nano", # Replace with your model deployment name 
-    input="This is a test."
-)
-
-print(response.model_dump_json(indent=2)) 
+client = OpenAI()
 ```
 
-### Next generation API
+**Microsoft Entra ID**:
 
 > [!IMPORTANT]
 > Handling automatic token refresh was previously handled through use of the `AzureOpenAI()` client. The v1 API removes this dependency, by adding automatic token refresh support to the `OpenAI()` client.
@@ -143,40 +107,148 @@ print(response.model_dump_json(indent=2))
 - `base_url` passes the Azure OpenAI endpoint and `/openai/v1` is appended to the endpoint address.
 - `api_key` parameter is set to `token_provider`, enabling automatic retrieval and refresh of an authentication token instead of using a static API key.
 
-# [REST](#tab/rest)
+# [C#](#tab/dotnet)
+
+### v1 API
 
-### Last generation API 
+[C# v1 examples](./supported-languages.md)
 
 **API Key**:
 
-```bash
-curl -X POST https://YOUR-RESOURCE-NAME.openai.azure.com/openai/responses?api-version=2025-04-01-preview \
-  -H "Content-Type: application/json" \
-  -H "api-key: $AZURE_OPENAI_API_KEY" \
-  -d '{
-     "model": "gpt-4.1-nano",
-     "input": "This is a test"
-    }'
+```csharp
+OpenAIClient client = new(
+    new ApiKeyCredential("{your-api-key}"),
+    new OpenAIClientOptions()
+    {
+        Endpoint = new("https://YOUR-RESOURCE-NAME.openai.azure.com/openai/v1/"),
+    })
 ```
 
 **Microsoft Entra ID**:
 
-```bash
-curl -X POST https://YOUR-RESOURCE-NAME.openai.azure.com/openai/responses?api-version=2025-04-01-preview \
-  -H "Content-Type: application/json" \
-  -H "Authorization: Bearer $AZURE_OPENAI_AUTH_TOKEN" \
-  -d '{
-     "model": "gpt-4.1-nano",
-     "input": "This is a test"
-    }'
+```csharp
+#pragma warning disable OPENAI001
+
+BearerTokenPolicy tokenPolicy = new(
+    new DefaultAzureCredential(),
+    "https://cognitiveservices.azure.com/.default");
+OpenAIClient client = new(
+    authenticationPolicy: tokenPolicy,
+    options: new OpenAIClientOptions()
+    {
+        Endpoint = new("https://YOUR-RESOURCE-NAME.openai.azure.com/openai/v1/"),
+    })
 ```
 
-### Next generation API
+# [JavaScript](#tab/javascript)
+
+### v1 API
+
+[JavaScript v1 examples](./supported-languages.md)
+
+**API Key**:
+
+```javascript
+const client = new OpenAI({
+    baseURL: "https://YOUR-RESOURCE-NAME.openai.azure.com/openai/v1/",
+    apiKey: "{your-api-key}" 
+});
+```
+
+**API Key** with environment variables set for `OPENAI_BASE_URL` and `OPENAI_API_KEY`:
+
+```javascript
+const client = new OpenAI();
+```
+
+**Microsoft Entra ID**:
+
+```javascript
+const tokenProvider = getBearerTokenProvider(
+    new DefaultAzureCredential(),
+    'https://cognitiveservices.azure.com/.default');
+const client = new OpenAI({
+    baseURL: "https://YOUR-RESOURCE-NAME.openai.azure.com/openai/v1/",
+    apiKey: tokenProvider
+});
+```
+
+# [Go](#tab/go)
+
+### v1 API
+
+[Go v1 examples](./supported-languages.md)
+
+**API Key**:
+
+```go
+client := openai.NewClient(
+    option.WithBaseURL("https://YOUR-RESOURCE-NAME.openai.azure.com/openai/v1/"),
+    option.WithAPIKey("{your-api-key}")
+)
+```
+
+**API Key** with environment variables set for `OPENAI_BASE_URL` and `OPENAI_API_KEY`:
+
+```go
+client := openai.NewClient()
+```
+
+
+**Microsoft Entra ID**:
+
+```go
+tokenCredential, err := azidentity.NewDefaultAzureCredential(nil)
+
+client := openai.NewClient(
+    option.WithBaseURL("https://YOUR-RESOURCE-NAME.openai.azure.com/openai/v1/"),
+    azure.WithTokenCredential(tokenCredential)
+)
+```
+
+# [Java](#tab/Java)
+
+### v1 API
+
+**API Key**:
+
+```java
+
+OpenAIClient client = OpenAIOkHttpClient.builder()
+                .baseUrl("https://YOUR-RESOURCE-NAME.openai.azure.com/openai/v1/")
+                .credential(AzureApiKeyCredential.create("{your-api-key}"))
+                .build();
+```
+
+**API Key** with environment variables set for `OPENAI_BASE_URL` and `OPENAI_API_KEY`:
+
+```java
+OpenAIClient client = OpenAIOkHttpClient.builder()
+                .fromEnv()
+                .build();
+```
+
+**Microsoft Entra ID**:
+
+```java
+Credential tokenCredential = BearerTokenCredential.create(
+        AuthenticationUtil.getBearerTokenSupplier(
+                new DefaultAzureCredentialBuilder().build(),
+                "https://cognitiveservices.azure.com/.default"));
+OpenAIClient client = OpenAIOkHttpClient.builder()
+        .baseUrl("https://YOUR-RESOURCE-NAME.openai.azure.com/openai/v1/")
+        .credential(tokenCredential)
+        .build();
+```
+
+# [REST](#tab/rest)
+
+### v1 API
 
 **API Key**:
 
 ```bash
-curl -X POST https://YOUR-RESOURCE-NAME.openai.azure.com/openai/v1/responses?api-version=preview \
+curl -X POST https://YOUR-RESOURCE-NAME.openai.azure.com/openai/v1/responses \
   -H "Content-Type: application/json" \
   -H "api-key: $AZURE_OPENAI_API_KEY" \
   -d '{
@@ -188,7 +260,7 @@ curl -X POST https://YOUR-RESOURCE-NAME.openai.azure.com/openai/v1/responses?api
 **Microsoft Entra ID**:
 
 ```bash
-curl -X POST https://YOUR-RESOURCE-NAME.openai.azure.com/openai/v1/responses?api-version=preview \
+curl -X POST https://YOUR-RESOURCE-NAME.openai.azure.com/openai/v1/responses \
   -H "Content-Type: application/json" \
   -H "Authorization: Bearer $AZURE_OPENAI_AUTH_TOKEN" \
   -d '{

articles/ai-foundry/openai/azure-government.md

@@ -56,6 +56,27 @@ To request quota increases for these models, submit a request at [https://aka.ms
 
 <br>
 
+### Model Retirements
+In some cases, models are retired in Azure Governmen ahead of dates in the commercial cloud. General information on model retirement policies, dates, and other details can be found at [Azure OpenAI in Azure AI Foundry model deprecations and retirements](/azure/ai-foundry/openai/concepts/model-retirements). The following shows model retirement differences in Azure Government. 
+
+| Model                     | Version			      | Azure Government Status	  | Public Retirement date             |
+| --------------------------|-------------------|:--------------------------|------------------------------------|
+| `gpt-35-turbo`            | 1106				      | Retired                   | November 11, 2025                  |
+| `gpt-4`                   | turbo-2024-04-09	| Retired                   | November 11, 2025                  |
+
+<br>
+
+### Deafault Model Versions 
+In some cases, new model versions are designated as default in Azure Governmen ahead of dates in the commercial cloud. General information on model upgrades can be found at [Working with Azure OpenAI models](/azure/ai-foundry/openai/how-to/working-with-models?tabs=powershell&branch=main#model-deployment-upgrade-configuration)
+
+The following shows default model differences in Azure Government. 
+
+| Model     | Azure Government Default Version | Public Default Version | Default upgrade date          |
+|-----------|----------------------------------|------------------------|-------------------------------|
+|  `gpt-4o` | 2024-11-20                       | 2024-08-06             | Starting on October 13, 2025  |
+
+<br>
+
 ## Azure OpenAI features
 
 The following feature differences exist when comparing Azure OpenAI in Azure Government vs commercial cloud.

articles/ai-foundry/responsible-ai/agents/transparency-note.md

@@ -110,7 +110,8 @@ Developers can connect an Agent to external systems, APIs, and services through
 * **Model Context Protocol tools** (a custom service connected via Model Context Protocol through an existing remote MCP server to an Agent).
 * **Deep Research tool**: (a tool that enables multi-step web-based research with the o3-deep-research model and Grounding with Bing Search.).
 * **Computer Use**: (a tool to perform tasks by interacting with computer systems and applications through their UIs)   
-* **Browser Automation Tool** (a tool that can perform real-world browser tasks through natural language prompts, enabling automated browsing activities without human intervention in the middle) 
+* **Browser Automation Tool** (a tool that can perform real-world browser tasks through natural language prompts, enabling automated browsing activities without human intervention in the middle)
+* **Image Generation** (a tool to generate and edit images)
 
 #### Orchestrating multi-agent systems
 
@@ -131,8 +132,9 @@ Azure AI Agent Service is **flexible and use-case agnostic.** This presents mult
 * **Government: Citizen Request Triage and Community Event Coordination:** A city clerk uses an agent to categorize incoming service requests (for example, pothole repairs), assign them to the right departments, and compile simple status updates; officials review and finalize communications to maintain transparency and accuracy.
 * **Education: Assisting with Research and Reference Gathering:** A teacher relies on an agent to gather age-appropriate articles and resources from reputable sources for a planetary science lesson; the teacher verifies the materials for factual accuracy and adjusts them to fit the curriculum, ensuring students receive trustworthy content.
 * **Manufacturing: Inventory Oversight and Task Scheduling:** A factory supervisor deploys an agent to monitor inventory levels, schedule restocking when supplies run low, and optimize shift rosters; management confirms the agent’s suggestions and retains final decision-making authority.
-* **Deep Research Tool**: Learn more about intended uses, capabilities, limitations, risks, and considerations when choosing a use case model with deep research technology in the [Azure OpenAI transparency note](../openai/transparency-note.md?tabs=text).
+* **Deep Research Tool**: Learn more about intended uses, capabilities, limitations, risks, and considerations when choosing a use case model with deep research technology in the [Azure OpenAI transparency note](/azure/ai-foundry/responsible-ai/openai/transparency-note?tabs=text).
 * **Computer Use**:  The Computer Use tool comes with additional significant security and privacy risks, including prompt injection attacks. Learn more about intended uses, capabilities, limitations, risks, and considerations when choosing a use case in the [Azure OpenAI transparency note](../openai/transparency-note.md?tabs=image). 
+* **Image Generation Tool**: The Image Generation tool is empowered by the gpt-image-1 model. Learn more about intended uses, capabilities, limitations, risks, and considerations when choosing a use case model in the [Azure OpenAI transparency note](/azure/ai-foundry/responsible-ai/openai/transparency-note?branch=main&tabs=image).
 
 Agent code samples have specific intended uses that are configurable by developers to carefully build upon, implement, and deploy agents. See [list of Agent code samples](/azure/ai-foundry/agents/overview#agent-catalog).
 

articles/ai-foundry/responsible-ai/openai/data-privacy.md

@@ -1,53 +1,52 @@
 ---
-title: Data, privacy, and security for Azure OpenAI Service
+title: Data, privacy, and security for Azure Direct Models in Azure AI Foundry 
 titleSuffix: Azure AI services
 description: This document details issues for data, privacy, and security for Azure OpenAI Service
 author: mrbullwinkle
 ms.author: mbullwin
 manager: nitinme
 ms.service: azure-ai-openai
 ms.topic: article
-ms.date: 02/23/2024
+ms.date: 10/01/2025
 ---
 
-# Data, privacy, and security for Azure OpenAI Service
+# Data, privacy, and security for Azure Direct Models in Azure AI Foundry 
 
 [!INCLUDE [non-english-translation](../includes/non-english-translation.md)]
 
+This article provides details regarding how data provided by you to Azure Direct Models in Azure AI Foundry are processed, used, and stored. Azure Direct Model means an AI model designated and deployed as an “Azure Direct Model” in Azure AI Foundry, and includes Azure OpenAI models. Azure Direct Models store and process data to provide the service and to monitor for uses that violate the applicable product terms. Please also see [Microsoft Products and Services Data Protection Addendum](https://aka.ms/DPA), which governs data processing by Azure Direct Models. Azure AI Foundry is an Azure service; [learn more](/compliance/regulatory/offering-home) about applicable Azure compliance offerings. 
 
-This article provides details regarding how data provided by you to the Azure OpenAI service is processed, used, and stored. Azure OpenAI stores and processes data to provide the service and to monitor for uses that violate the applicable product terms. Also see the [Microsoft Products and Services Data Protection Addendum](https://aka.ms/DPA), which governs data processing by the Azure OpenAI Service. Azure OpenAI is an Azure service; [learn more](/compliance/regulatory/offering-home) about applicable Azure compliance offerings.
 
 > [!IMPORTANT] 
 > Your prompts (inputs) and completions (outputs), your embeddings, and your training data:
-> - are NOT available to other customers.
-> - are NOT available to OpenAI.
-> - are NOT used to improve OpenAI models. 
-> - are NOT used to train, retrain, or improve Azure OpenAI Service foundation models.
-> - are NOT used to improve any Microsoft or third party products or services without your permission or instruction.
-> - Your fine-tuned Azure OpenAI models are available exclusively for your use.
+> - are NOT available to other customers. 
+> - are NOT available to OpenAI or other Azure Direct Model providers. 
+> - are NOT used by Azure Direct Model providers to improve their models or services. 
+> - are NOT used to train any generative AI foundation models without your permission or instruction. 
+>
+> Your fine-tuned Azure OpenAI models are available exclusively for your use.
 >
 > The Azure OpenAI Service is operated by Microsoft as an Azure service; Microsoft hosts the OpenAI models in Microsoft's Azure environment and the Service does NOT interact with any services operated by OpenAI (e.g. ChatGPT, or the OpenAI API).
 
-## What data does the Azure OpenAI Service process?
-
-Azure OpenAI processes the following types of data:
+## What data does Azure AI Foundry process to provide Azure Direct Models? 
 
-- **Prompts and generated content**. Prompts are submitted by the user, and content is generated by the service, via the completions, chat completions, images, and embeddings operations.
-- **Uploaded data**. You can provide your own data for use with certain service features (e.g., [fine-tuning](/azure/ai-foundry/openai/how-to/fine-tuning?pivots=programming-language-studio), [assistants API](/azure/ai-foundry/openai/how-to/batch?tabs=standard-input&pivots=programming-language-ai-studio), [batch processing](/azure/ai-foundry/openai/how-to/batch?tabs=standard-input&pivots=programming-language-ai-studio)) using the Files API or vector store.
-- **Data for stateful entities**. When you use certain optional features of Azure OpenAI, such as the [Responses API](/azure/ai-foundry/openai/how-to/responses), the Threads feature of the [Assistants API](/azure/ai-foundry/openai/how-to/assistant), and Stored completions, the service creates a data store to persist message history and other content, in accordance with how you configure the feature.
+Azure AI Foundry processes the following types of data to provide Azure Direct Models:
+- **Prompts and generated content**. When prompts are submitted by the user, content is generated by the service, via the completions, chat completions, images, and embeddings operations. 
+- **Uploaded data**. You can upload your own data for use with certain service features (e.g., [fine-tuning](/azure/ai-foundry/openai/how-to/fine-tuning?pivots=programming-language-studio), [assistants API](/azure/ai-foundry/openai/how-to/batch?tabs=standard-input&pivots=programming-language-ai-studio), [batch processing](/azure/ai-foundry/openai/how-to/batch?tabs=standard-input&pivots=programming-language-ai-studio)) using the Files API or vector store.
+- **Data for stateful entities**. When you use certain optional features of Azure Direct Models and Agents, such as the [Responses API](/azure/ai-foundry/openai/how-to/responses), the Threads feature of the [Assistants API](/azure/ai-foundry/openai/how-to/assistant), and Stored completions, the service creates a data store to persist message history and other content, in accordance with how you configure the feature.
 - **Augmented data included with or via prompts**. When you use data associated with stateful entities, the service retrieves relevant data from a configured data store and augments the prompt to produce generations that are grounded with your data. Prompts may also be augmented with data retrieved from a source included in the prompt itself, such as a URL.   
 - **Training & validation data**. You can provide your own training data consisting of prompt-completion pairs for the purposes of [fine-tuning an OpenAI model](/azure/ai-foundry/openai/how-to/fine-tuning?pivots=programming-language-studio).
 
-## How does the Azure OpenAI Service process data?
+## How does Azure AI Foundry process data to provide Azure Direct Models?
 
 The diagram below illustrates how your data is processed. This diagram covers several types of processing: 
 
-1. How the Azure OpenAI Service processes your prompts via inferencing to generate content (including when additional data from a designated data source is added to a prompt using Azure OpenAI on your data, Assistants, or batch processing). 
+1. How Azure AI Foundry processes your prompts via inferencing with Azure Direct Models to generate content (including when additional data from a designated data source is added to a prompt using Azure OpenAI on your data, Assistants, or batch processing). 
 1. How the Assistants feature stores data in connection with Messages, Threads, and Runs.  
 1. How the Responses API feature stores data to persist message history.  
 1. How the Batch feature processes your uploaded data. 
-1. How the Azure OpenAI Service creates a fine-tuned (custom) model with your uploaded data. 
-1. How the Azure OpenAI Service and Microsoft personnel analyze prompts and completions (text and image) for harmful content and for patterns suggesting the use of the service in a manner that violates the Code of Conduct or other applicable product terms. 
+1. How Azure AI Foundry creates a fine-tuned (custom) model with your uploaded data. 
+1. How Azure AI Foundry and Microsoft personnel analyze prompts and completions (text and image) for harmful content and for patterns suggesting the use of the service in a manner that violates the Code of Conduct or other applicable product terms. 
 
 :::image type="content" source="media\flow-2.jpg" alt-text="Data flow diagram for the service." lightbox="media\flow-2.jpg":::