Merge branch 'main' of https://github.com/MicrosoftDocs/azure-docs-pr into tamram24-0508

Author: tamram

.openpublishing.redirection.json

@@ -1,5 +1,35 @@
 {
     "redirections": [
+    {
+      "source_path": "articles/network-watcher/network-watcher-security-group-view-powershell.md",
+      "redirect_url": "/previous-versions/azure/network-watcher/network-watcher-security-group-view-powershell",
+      "redirect_document_id": false
+    },
+    {
+      "source_path": "articles/network-watcher/network-watcher-security-group-view-cli.md",
+      "redirect_url": "/previous-versions/azure/network-watcher/network-watcher-security-group-view-cli",
+      "redirect_document_id": false
+    },
+    {
+      "source_path": "articles/storage/blobs/blob-v11-samples-dotnet.md",
+      "redirect_url": "/previous-versions/azure/storage/blobs/blob-v11-samples-dotnet",
+      "redirect_document_id": false
+    },
+    {
+      "source_path": "articles/storage/blobs/blob-v11-samples-javascript.md",
+      "redirect_url": "/previous-versions/azure/storage/blobs/blob-v11-samples-javascript",
+      "redirect_document_id": false
+    },
+    {
+      "source_path": "articles/storage/blobs/blob-v2-samples-python.md",
+      "redirect_url": "/previous-versions/azure/storage/blobs/blob-v2-samples-python",
+      "redirect_document_id": false
+    },
+    {
+      "source_path": "articles/storage/common/geo-redundant-design-legacy.md",
+      "redirect_url": "/previous-versions/azure/storage/common/geo-redundant-design-legacy",
+      "redirect_document_id": false
+    },
     {
       "source_path": "articles/germany/index.yml",
       "redirect_url": "/previous-versions/azure/germany/index",
@@ -4004,6 +4034,11 @@
             "source_path_from_root":"/articles/aks/generation-2-vm-windows.md",
             "redirect_url":"/azure/aks/generation-2-vm",
             "redirect_document_id":false
+        },
+        {
+            "source_path_from_root":"/articles/cosmos-db/high-availability.md",
+            "redirect_url":"/azure/reliability/reliability-cosmos-db-nosql.md",
+            "redirect_document_id":false
         }
     ]
 }

articles/active-directory-b2c/custom-policies-series-sign-up-or-sign-in-federation.md

@@ -225,7 +225,7 @@ Notice the claims transformations we defined in [step 3.2](#step-32---define-cla
 
 Just like in sign-in with a local account, you need to configure the [Microsoft Entra Technical Profiles](active-directory-technical-profile.md), which you use to connect to Microsoft Entra ID storage, to store or read a user social account. 
 
-1. In the `ContosoCustomPolicy.XML` file, locate the `AAD-UserRead` technical profile and then add a new technical profile by using the following code: 
+1. In the `ContosoCustomPolicy.XML` file, locate the `AAD-UserRead` technical profile and then add a new technical profile below it by using the following code: 
 
     ```xml
         <TechnicalProfile Id="AAD-UserWriteUsingAlternativeSecurityId">
@@ -517,6 +517,7 @@ Use the following steps to add a combined local and social account:
     ```xml
         <OutputClaim ClaimTypeReferenceId="authenticationSource" DefaultValue="localIdpAuthentication" AlwaysUseDefaultValue="true" />
     ```
+   Make sure you also add the `authenticationSource` claim in the output claims collection of the `UserSignInCollector` self-asserted technical profile.
 
 1. In the `UserJourneys` section, add a new user journey, `LocalAndSocialSignInAndSignUp` by using the following code: 
 

articles/active-directory-b2c/service-limits.md

@@ -8,7 +8,7 @@ manager: CelesteDG
 ms.service: active-directory
 
 ms.topic: reference
-ms.date: 01/11/2024
+ms.date: 05/11/2024
 ms.subservice: B2C
 zone_pivot_groups: b2c-policy-type
 
@@ -169,7 +169,7 @@ The following table lists the administrative configuration limits in the Azure A
 |String Limit per Attribute      |250 Chars          |
 |Number of B2C tenants per subscription      |20         |
 |Total number of objects (user accounts and applications) per tenant (default limit)|1.25 million |
-|Total number of objects (user accounts and applications) per tenant (using a verified custom domain)|5.25 million |
+|Total number of objects (user accounts and applications) per tenant (using a verified custom domain). If you want to increase this limit, please contact [Microsoft Support](find-help-open-support-ticket.md).|5.25 million |
 |Levels of [inheritance](custom-policy-overview.md#inheritance-model) in custom policies     |10         |
 |Number of policies per Azure AD B2C tenant (user flows + custom policies)     |200          |
 |Maximum policy file size      |1024 KB          |

articles/ai-services/content-moderator/includes/tool-deprecation.md

@@ -13,7 +13,7 @@ ms.author: pafarley
 
 
 > [!IMPORTANT]
-> Azure Content Moderator is being deprecated in February 2024, and will be retired by February 2027. It is being replaced by [Azure AI Content Safety](/azure/ai-services/content-safety/overview), which offers advanced AI features and enhanced performance.
+> Azure Content Moderator is deprecated as of February 2024 and will be retired by February 2027. It is replaced by [Azure AI Content Safety](/azure/ai-services/content-safety/overview), which offers advanced AI features and enhanced performance.
 >
 > Azure AI Content Safety is a comprehensive solution designed to detect harmful user-generated and AI-generated content in applications and services. Azure AI Content Safety is suitable for many scenarios such as online marketplaces, gaming companies, social messaging platforms, enterprise media companies, and K-12 education solution providers. Here's an overview of its features and capabilities:
 > 

articles/ai-services/content-moderator/index.yml

@@ -1,7 +1,7 @@
 ### YamlMime:Landing
 
 title: Content Moderator documentation # < 60 chars
-summary: "The Azure Content Moderator API checks text, image, and video content for material that is potentially offensive, risky, or otherwise undesirable. Content Moderator is being deprecated in February 2024, and will be retired by February 2027. It is being replaced by Azure AI Content Safety, which offers advanced AI features and enhanced performance. Azure AI Content Safety is a comprehensive solution designed to detect harmful user-generated and AI-generated content in applications and services. Azure AI Content Safety is suitable for many scenarios such as online marketplaces, gaming companies, social messaging platforms, enterprise media companies, and K-12 education solution providers." # < 160 chars
+summary: "Azure Content Moderator is deprecated as of February 2024 and will be retired by February 2027. It is replaced by Azure AI Content Safety, which offers advanced AI features and enhanced performance. Azure AI Content Safety is a comprehensive solution designed to detect harmful user-generated and AI-generated content in applications and services. Azure AI Content Safety is suitable for many scenarios such as online marketplaces, gaming companies, social messaging platforms, enterprise media companies, and K-12 education solution providers." # < 160 chars
 
 metadata:
   title: Content Moderator Documentation - Quickstarts, Tutorials, API Reference - Azure AI services  | Microsoft Docs

articles/ai-services/language-service/conversational-language-understanding/concepts/best-practices.md

@@ -251,3 +251,4 @@ Once the request is sent, you can track the progress of the training job in Lang
 Caveats:
 - The None Score threshold for the app (confidence threshold below which the topIntent is marked as None) when using this recipe should be set to 0. This is because this new recipe attributes a certain portion of the in domain probabiliities to out of domain so that the model is not incorrectly overconfident about in domain utterances. As a result, users may see slightly reduced confidence scores for in domain utterances as compared to the prod recipe.
 - This recipe is not recommended for apps with just two (2) intents, such as IntentA and None, for example.
+- This recipe is not recommended for apps with low number of utterances per intent. A minimum of 25 utterances per intent is highly recommended.

articles/ai-services/openai/assistants-reference-runs.md

@@ -5,7 +5,7 @@ description: Learn how to use Azure OpenAI's Python & REST API runs with Assista
 manager: nitinme
 ms.service: azure-ai-openai
 ms.topic: conceptual
-ms.date: 02/01/2024
+ms.date: 04/16/2024
 author: mrbullwinkle
 ms.author: mbullwin
 recommendations: false
@@ -585,3 +585,115 @@ Represent a step in execution of a run.
 | `failed_at`| integer or null | The Unix timestamp (in seconds) for when the run step failed.|
 | `completed_at`| integer or null | The Unix timestamp (in seconds) for when the run step completed.|
 | `metadata`| map | Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format. Keys can be a maximum of 64 characters long and values can be a maximum of 512 characters long.|
+
+## Stream a run result (preview)
+
+Stream the result of executing a Run or resuming a Run after submitting tool outputs. You can stream events after:
+* [Create Thread and Run](#create-thread-and-run) 
+* [Create Run](#create-run)
+* [Submit Tool Outputs](#submit-tool-outputs-to-run) 
+
+To stream a result, pass `"stream": true` while creating a run. The response will be a [Server-Sent events](https://html.spec.whatwg.org/multipage/server-sent-events.html#server-sent-events) stream.
+
+### Streaming example
+
+```python
+from typing_extensions import override
+from openai import AssistantEventHandler
+ 
+# First, we create a EventHandler class to define
+# how we want to handle the events in the response stream.
+ 
+class EventHandler(AssistantEventHandler):    
+  @override
+  def on_text_created(self, text) -> None:
+    print(f"\nassistant > ", end="", flush=True)
+      
+  @override
+  def on_text_delta(self, delta, snapshot):
+    print(delta.value, end="", flush=True)
+      
+  def on_tool_call_created(self, tool_call):
+    print(f"\nassistant > {tool_call.type}\n", flush=True)
+  
+  def on_tool_call_delta(self, delta, snapshot):
+    if delta.type == 'code_interpreter':
+      if delta.code_interpreter.input:
+        print(delta.code_interpreter.input, end="", flush=True)
+      if delta.code_interpreter.outputs:
+        print(f"\n\noutput >", flush=True)
+        for output in delta.code_interpreter.outputs:
+          if output.type == "logs":
+            print(f"\n{output.logs}", flush=True)
+ 
+# Then, we use the `create_and_stream` SDK helper 
+# with the `EventHandler` class to create the Run 
+# and stream the response.
+ 
+with client.beta.threads.runs.stream(
+  thread_id=thread.id,
+  assistant_id=assistant.id,
+  instructions="Please address the user as Jane Doe. The user has a premium account.",
+  event_handler=EventHandler(),
+) as stream:
+  stream.until_done()
+```
+
+
+## Message delta object
+
+Represents a message delta. For example any changed fields on a message during streaming.
+
+|Name | Type | Description |
+|---  |---   |---         |
+| `id` | string | The identifier of the message, which can be referenced in API endpoints. |
+| `object` | string | The object type, which is always `thread.message.delta`. |
+| `delta` | object | The delta containing the fields that have changed on the Message. |
+
+## Run step delta object
+
+Represents a run step delta. For example any changed fields on a run step during streaming.
+
+|Name | Type | Description |
+|---  |---   |---         |
+| `id` | string | The identifier of the run step, which can be referenced in API endpoints. |
+| `object` | string | The object type, which is always `thread.run.step.delta`. |
+| `delta` | object | The delta containing the fields that have changed on the run step.
+
+## Assistant stream events
+
+Represents an event emitted when streaming a Run. Each event in a server-sent events stream has an event and data property:
+
+```json
+event: thread.created
+data: {"id": "thread_123", "object": "thread", ...}
+```
+
+Events are emitted whenever a new object is created, transitions to a new state, or is being streamed in parts (deltas). For example, `thread.run.created` is emitted when a new run is created, `thread.run.completed` when a run completes, and so on. When an Assistant chooses to create a message during a run, we emit a `thread.message.created` event, a `thread.message.in_progress` event, many thread.`message.delta` events, and finally a `thread.message.completed` event.
+
+|Name | Type | Description |
+|---  |---   |---         |
+| `thread.created` | `data` is a thread. | Occurs when a new thread is created. |
+| `thread.run.created` | `data` is a run. | Occurs when a new run is created. |
+| `thread.run.queued` | `data` is a run. | Occurs when a run moves to a queued status. |
+| `thread.run.in_progress` | `data` is a run. | Occurs when a run moves to an in_progress status. |
+| `thread.run.requires_action` | `data` is a run. | Occurs when a run moves to a `requires_action` status. |
+| `thread.run.completed` | `data` is a run. | Occurs when a run is completed. |
+| `thread.run.failed` | `data` is a run. | Occurs when a run fails. |
+| `thread.run.cancelling` | `data` is a run. | Occurs when a run moves to a `cancelling` status. |
+| `thread.run.cancelled` | `data` is a run. | Occurs when a run is cancelled. |
+| `thread.run.expired` | `data` is a run. | Occurs when a run expires. |
+| `thread.run.step.created` | `data` is a run step. | Occurs when a run step is created. |
+| `thread.run.step.in_progress` | `data` is a run step. | Occurs when a run step moves to an `in_progress` state. | 
+| `thread.run.step.delta` | `data` is a run step delta. | Occurs when parts of a run step are being streamed. |
+| `thread.run.step.completed` | `data` is a run step. | Occurs when a run step is completed. |
+| `thread.run.step.failed` | `data` is a run step. | Occurs when a run step fails. |
+| `thread.run.step.cancelled` | `data` is a run step. | Occurs when a run step is cancelled. |
+| `thread.run.step.expired` | `data` is a run step. | Occurs when a run step expires. |
+| `thread.message.created` | `data` is a message. | Occurs when a message is created. |
+| `thread.message.in_progress` | `data` is a message. | Occurs when a message moves to an in_progress state. | 
+| `thread.message.delta` | `data` is a message delta. | Occurs when parts of a Message are being streamed. |
+| `thread.message.completed` | `data` is a message. | Occurs when a message is completed. |
+| `thread.message.incomplete` | `data` is a message. | Occurs when a message ends before it is completed. |
+| `error` | `data` is an error. | Occurs when an error occurs. This can happen due to an internal server error or a timeout. |
+| `done` | `data` is `[DONE]` | Occurs when a stream ends. |