Merge branch 'main' into release-preview-ptu

Author: v-alje

articles/ai-foundry/ai-services/content-safety-overview.md

@@ -7,7 +7,7 @@ ms.service: azure-ai-foundry
 ms.custom:
   - ignite-2024
 ms.topic: overview
-ms.date: 05/01/2025
+ms.date: 05/31/2025
 ms.author: pafarley
 author: PatrickFarley
 ---

articles/ai-foundry/concepts/content-filtering.md

@@ -9,7 +9,7 @@ ms.custom:
   - build-2024
   - ignite-2024
 ms.topic: conceptual
-ms.date: 04/29/2025
+ms.date: 05/31/2025
 ms.reviewer: eur
 ms.author: pafarley
 author: PatrickFarley
@@ -24,9 +24,9 @@ author: PatrickFarley
 
 ## How it works 
 
-The content filtering system is powered by [Azure AI Content Safety](../../ai-services/content-safety/overview.md), and it works by running both the prompt input and completion output through a set of classification models designed to detect and prevent the output of harmful content. Variations in API configurations and application design might affect completions and thus filtering behavior.
+The content filtering system is powered by [Azure AI Content Safety](../../ai-services/content-safety/overview.md), and it works by running both the model prompt input and completion output through a set of classification models designed to detect and prevent the output of harmful content. Variations in API configurations and application design might affect completions and thus filtering behavior.
 
-With Azure OpenAI model deployments, you can use the default content filter or create your own content filter (described later on). Models available through **standard deployments** have content filtering enabled by default. To learn more about the default content filter enabled for standard deployments, see [Content safety for Models Sold Directly by Azure ](model-catalog-content-safety.md).
+With Azure OpenAI model deployments, you can use the default content filter or create your own content filter (described later). Models available through **standard deployments** have content filtering enabled by default. To learn more about the default content filter enabled for standard deployments, see [Content safety for Models Sold Directly by Azure ](model-catalog-content-safety.md).
 
 ## Language support
 
@@ -73,20 +73,7 @@ You can also enable the following special output filters:
 
 ### Configurability (preview)
 
-The default content filtering configuration for the GPT model series is set to filter at the medium severity threshold for all four content harm categories (hate, violence, sexual, and self-harm) and applies to both prompts (text, multi-modal text/image) and completions (text). This means that content that is detected at severity level medium or high is filtered, while content detected at severity level low isn't filtered by the content filters. For DALL-E, the default severity threshold is set to low for both prompts (text) and completions (images), so content detected at severity levels low, medium, or high is filtered. 
-
-The configurability feature allows customers to adjust the settings, separately for prompts and completions, to filter content for each content category at different severity levels as described in the table below:
-
-| Severity filtered | Configurable for prompts | Configurable for completions | Descriptions |
-|-------------------|--------------------------|------------------------------|--------------|
-| Low, medium, high | Yes | Yes | Strictest filtering configuration. Content detected at severity levels low, medium and high is filtered.|
-| Medium, high      | Yes | Yes | Content detected at severity level low isn't filtered, content at medium and high is filtered.|
-| High              | Yes| Yes | Content detected at severity levels low and medium isn't filtered. Only content at severity level high is filtered. Requires approval<sup>1</sup>.|
-| No filters | If approved<sup>1</sup>| If approved<sup>1</sup>| No content is filtered regardless of severity level detected. Requires approval<sup>1</sup>.|
-
-<sup>1</sup> For Azure OpenAI models, only customers who have been approved for modified content filtering have full content filtering control, including configuring content filters at severity level high only or turning off content filters. Apply for modified content filters via these forms: [Azure OpenAI Limited Access Review: Modified Content Filters](https://customervoice.microsoft.com/Pages/ResponsePage.aspx?id=v4j5cvGGr0GRqy180BHbR7en2Ais5pxKtso_Pz4b1_xUMlBQNkZMR0lFRldORTdVQzQ0TEI5Q1ExOSQlQCN0PWcu), and [Modified Abuse Monitoring](https://customervoice.microsoft.com/Pages/ResponsePage.aspx?id=v4j5cvGGr0GRqy180BHbR7en2Ais5pxKtso_Pz4b1_xUOE9MUTFMUlpBNk5IQlZWWkcyUEpWWEhGOCQlQCN0PWcu).
-
-Customers are responsible for ensuring that applications integrating Azure OpenAI comply with the [Code of Conduct](/legal/ai-code-of-conduct?context=%2Fazure%2Fai-services%2Fopenai%2Fcontext%2Fcontext). 
+[!INCLUDE [content-filter-configurability](../../ai-services/openai/includes/content-filter-configurability.md)]
 
 
 ## Related content

articles/ai-foundry/how-to/evaluation-github-action.md

@@ -5,7 +5,7 @@ description: How to run evaluation in GitHub Action to streamline the evaluation
 manager: scottpolly
 ms.service: azure-ai-foundry
 ms.topic: how-to
-ms.date: 05/19/2025
+ms.date: 06/1/2025
 ms.reviewer: hanch
 ms.author: lagayhar
 author: lgayhardt
@@ -27,7 +27,7 @@ Offline evaluation involves testing AI models and agents using test datasets to
 
 ## Prerequisites
 
-[!INCLUDE [hub-only-prereq](../includes/hub-only-prereq.md)]
+Foundry project or Hubs based project. To learn more, see [Create a project](create-projects.md).
 
 Two GitHub Actions are available for evaluating AI applications: **ai-agent-evals** and **genai-evals**.
 
@@ -45,8 +45,16 @@ The input of ai-agent-evals includes:
 
 **Required:**
 
-- `azure-aiproject-connection-string`: The connection string for the Azure AI project. This is used to connect to Azure OpenAI to simulate conversations with each agent, and to connect to the Azure AI evaluation SDK to perform the evaluation.
-- `deployment-name`: the deployed model name.
+# [Foundry project](#tab/foundry-project)
+
+- `azure-ai-project-endpoint`: The endpoint of the Azure AI project. This is used to connect to your AI project to simulate conversations with each agent, and to connect to the Azure AI evaluation SDK to perform the evaluation.
+
+# [Hub based project](#tab/hub-project)
+
+- `azure-aiproject-connection-string`: The connection string of the Azure AI project. This is used to connect to your AI project to simulate conversations with each agent, and to connect to the Azure AI evaluation SDK to perform the evaluation.
+
+---
+- `deployment-name`: the deployed model name for evaluation judgement.
 - `data-path`: Path to the input data file containing the conversation starters. Each conversation starter is sent to each agent for a pairwise comparison of evaluation results.
   - `evaluators`: built-in evaluator names.
   - `data`: a set of conversation starters/queries.
@@ -55,6 +63,7 @@ The input of ai-agent-evals includes:
   - When only one `agent-id` is specified, the evaluation results include the absolute values for each metric along with the corresponding confidence intervals.
   - When multiple `agent-ids` are specified, the results include absolute values for each agent and a statistical comparison against the designated baseline agent ID.
 
+
 **Optional:**
 
 - `api-version`: the API version of deployed model.
@@ -92,6 +101,48 @@ To use the GitHub Action, add the GitHub Action to your CI/CD workflows and spec
 
 This example illustrates how Azure Agent AI Evaluation can be run when comparing different agents with agent IDs.
 
+# [Foundry project](#tab/foundry-project)
+
+```YAML
+name: "AI Agent Evaluation"
+
+on:
+  workflow_dispatch:
+  push:
+    branches:
+      - main
+
+permissions:
+  id-token: write
+  contents: read
+
+jobs:
+  run-action:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+
+      - name: Azure login using Federated Credentials
+        uses: azure/login@v2
+        with:
+          client-id: ${{ vars.AZURE_CLIENT_ID }}
+          tenant-id: ${{ vars.AZURE_TENANT_ID }}
+          subscription-id: ${{ vars.AZURE_SUBSCRIPTION_ID }}
+
+      - name: Run Evaluation
+        uses: microsoft/ai-agent-evals@v2-beta
+        with:
+          # Replace placeholders with values for your Azure AI Project
+          azure-ai-project-endpoint: "<your-ai-project-endpoint>"
+          deployment-name: "<your-deployment-name>"
+          agent-ids: "<your-ai-agent-ids>"
+          data-path: ${{ github.workspace }}/path/to/your/data-file
+
+```
+
+# [Hub based project](#tab/hub-project)
+
 ```YAML
 name: "AI Agent Evaluation"
 
@@ -130,6 +181,8 @@ jobs:
 
 ```
 
+---
+
 ### AI agent evaluations output
 
 Evaluation results are outputted to the summary section for each AI evaluation GitHub Action run under Actions in GitHub.com.

articles/ai-foundry/how-to/use-blocklists.md

@@ -7,7 +7,7 @@ ms.service: azure-ai-foundry
 ms.custom:
   - ignite-2024
 ms.topic: how-to
-ms.date: 05/01/2025
+ms.date: 05/31/2025
 ms.author: pafarley
 author: PatrickFarley
 ---

articles/ai-foundry/index.yml

@@ -104,7 +104,7 @@ productDirectory:
           text: Speech
         - url: ../ai-services/computer-vision/index.yml
           text: Vision
-        - url: ../ai-services/custom-vision-service/index.yml
+        - url: ../ai-services/translator/index.yml
           text: Translator
         - url: ../ai-services/language-service/index.yml
           text: Language

articles/ai-foundry/responsible-use-of-ai-overview.md

@@ -6,7 +6,7 @@ manager: nitinme
 keywords: Azure AI services, cognitive
 ms.service: azure-ai-foundry
 ms.topic: overview
-ms.date: 05/09/2025
+ms.date: 05/31/2025
 ms.author: pafarley
 author: PatrickFarley
 ms.custom: ignite-2024

articles/ai-foundry/whats-new-azure-ai-foundry.md

@@ -1,39 +1,22 @@
 ---
-title: "Azure AI Foundry docs: What's new for April 2025"
-description: "What's new in the Azure AI Foundry docs for April 2025."
+title: "Azure AI Foundry docs: What's new for May 2025"
+description: "What's new in the Azure AI Foundry docs for May 2025."
 ms.author: smcdowell
 author: skpmcdowell
 ms.topic: whats-new
-ms.subject: ai-studio
-ms.custom: April-2025
-ms.date: 05/03/2025
+ms.subject: ai-foundry
+ms.custom: May-2025
+ms.date: 06/02/2025
 ---
 
-# Azure AI Foundry docs: What's new for April 2025
+# Azure AI Foundry docs: What's new for May 2025
 
-Welcome to what's new in the Azure AI Foundry docs for April 2025. This article lists some of the major changes to docs during this period.
+Welcome to what's new in the Azure AI Foundry docs for May 2025. This article lists some of the major changes to docs during this period.
 
+## Updated articles
 
-## Azure AI Foundry
+- [Evaluate your Generative AI application on the cloud with Azure AI Projects SDK (preview)](../ai-foundry/how-to/develop/cloud-evaluation.md)
 
-### New articles
-
-- [AI Red Teaming Agent (preview)](../ai-foundry/concepts/ai-red-teaming-agent.md)
-- [Evaluate your AI agents locally with Azure AI Evaluation SDK (preview)](../ai-foundry/how-to/develop/agent-evaluate-sdk.md)
-- [How to use structured outputs for chat models](../ai-foundry/model-inference/how-to/use-structured-outputs.md)
-- [Run automated safety scans with AI Red Teaming Agent (preview)](../ai-foundry/how-to/develop/run-scans-ai-red-teaming-agent.md)
-- [Work with Azure AI Agent Service in Visual Studio Code (Preview)](../ai-foundry/how-to/develop/vs-code-agents.md)
-- [Work with the Azure AI Foundry for Visual Studio Code extension (Preview)](../ai-foundry/how-to/develop/get-started-projects-vs-code.md)
-
-
-### Updated articles
-
-- [Evaluate your AI agents locally with Azure AI Evaluation SDK (preview)](../ai-foundry/how-to/develop/agent-evaluate-sdk.md)  
-- [Evaluate your Generative AI application locally with the Azure AI Evaluation SDK](../ai-foundry/how-to/develop/evaluate-sdk.md) 
-- [Evaluation and monitoring metrics for generative AI](../ai-foundry/concepts/evaluation-metrics-built-in.md)  
-- [Fine-tune models using standard deployments in Azure AI Foundry](../ai-foundry/how-to/fine-tune-serverless.md) 
-- [How to configure a private link for Azure AI Foundry hubs](../ai-foundry/how-to/configure-private-link.md) 
-- [How to use MedImageParse healthcare AI models for segmentation of medical images](../ai-foundry/how-to/healthcare-ai/deploy-medimageparse.md)
 
 
 

articles/ai-services/agents/how-to/tools/logic-apps.md

@@ -143,4 +143,4 @@ print("Deleted agent")
 
 ## Next steps
 
-[See the full sample for Logic Apps integration.](https://github.com/Azure/azure-sdk-for-python/blob/main/sdk/ai/azure-ai-projects/samples/agents/sample_agents_logic_apps.py)
+[See the full sample for Logic Apps integration.](https://github.com/Azure/azure-sdk-for-python/blob/main/sdk/ai/azure-ai-agents/samples/agents_tools/sample_agents_logic_apps.py)

articles/ai-services/computer-vision/concept-face-recognition.md

@@ -10,7 +10,7 @@ ms.subservice: azure-ai-face
 ms.custom:
   - ignite-2023
 ms.topic: conceptual
-ms.date: 05/01/2025
+ms.date: 05/31/2025
 ms.author: pafarley
 feedback_help_link_url: https://learn.microsoft.com/answers/tags/156/azure-face
 ---

articles/ai-services/computer-vision/concept-object-detection-40.md

@@ -7,8 +7,9 @@ manager: nitinme
 
 ms.service: azure-ai-vision
 ms.topic: conceptual
-ms.date: 05/01/2025
+ms.date: 05/31/2025
 ms.author: pafarley
+ms.collection: "ce-skilling-fresh-tier2, ce-skilling-ai-copilot"
 ---
 
 # Object detection (version 4.0)