Merge pull request #285258 from MicrosoftDocs/main

Merge main to live, 4 AM

Author: v-ccolin

articles/ai-services/openai/concepts/understand-embeddings.md

@@ -39,3 +39,5 @@ An alternative method of identifying similar documents is to count the number of
 
 * Learn more about using Azure OpenAI and embeddings to perform document search with our [embeddings tutorial](../tutorials/embeddings.md).
 * Store your embeddings and perform vector (similarity) search using [Azure Cosmos DB for MongoDB vCore](/azure/cosmos-db/mongodb/vcore/vector-search), [Azure Cosmos DB for NoSQL](/azure/cosmos-db/rag-data-openai) ,  [Azure SQL Database](/azure/azure-sql/database/ai-artificial-intelligence-intelligent-applications?view=azuresql&preserve-view=true#vector-search) or [Azure Database for PostgreSQL - Flexible Server](/azure/postgresql/flexible-server/how-to-use-pgvector).
+* Use an Eventhouse in Real-Time Intelligence in Microsoft Fabric as a [Vector database](/fabric/real-time-intelligence/vector-database)
+    * Use the [series_cosine_similarity](/kusto/query/series-cosine-similarity-function?view=microsoft-fabric&preserve-view=true) function for similarity search.

articles/ai-services/openai/how-to/embeddings.md

@@ -139,11 +139,12 @@ Our embedding models may be unreliable or pose social risks in certain cases, an
 
 * Learn more about using Azure OpenAI and embeddings to perform document search with our [embeddings tutorial](../tutorials/embeddings.md).
 * Learn more about the [underlying models that power Azure OpenAI](../concepts/models.md).
-* Store your embeddings and perform vector (similarity) search using your choice of Azure service:
+* Store your embeddings and perform vector (similarity) search using your choice of service:
   * [Azure AI Search](../../../search/vector-search-overview.md)
   * [Azure Cosmos DB for MongoDB vCore](/azure/cosmos-db/mongodb/vcore/vector-search)
   * [Azure SQL Database](/azure/azure-sql/database/ai-artificial-intelligence-intelligent-applications?view=azuresql&preserve-view=true#vector-search)
   * [Azure Cosmos DB for NoSQL](/azure/cosmos-db/vector-search)
   * [Azure Cosmos DB for PostgreSQL](/azure/cosmos-db/postgresql/howto-use-pgvector)
   * [Azure Database for PostgreSQL - Flexible Server](/azure/postgresql/flexible-server/how-to-use-pgvector)  
   * [Azure Cache for Redis](../../../azure-cache-for-redis/cache-tutorial-vector-similarity.md)
+  * [Use Eventhouse as a vector database - Real-Time Intelligence in Microsoft Fabric](/fabric/real-time-intelligence/vector-database)

articles/ai-services/speech-service/how-to-lower-speech-synthesis-latency.md

@@ -318,16 +318,18 @@ For Linux and Windows, `GStreamer` is required to enable this feature.
 Refer [this instruction](how-to-use-codec-compressed-audio-input-streams.md) to install and configure `GStreamer` for Speech SDK.
 For Android, iOS and macOS, no extra configuration is needed starting version 1.20.
 
-## Text streaming
+## Input text streaming
 
 Text streaming allows real-time text processing for rapid audio generation. It's perfect for dynamic text vocalization, such as reading outputs from AI models like GPT in real-time. This feature minimizes latency and improves the fluidity and responsiveness of audio outputs, making it ideal for interactive applications, live events, and responsive AI-driven dialogues.
 
 ### How to use text streaming
 
-To use the text streaming feature, connect to the websocket V2 endpoint: `wss://{region}.tts.speech.microsoft.com/cognitiveservices/websocket/v2`
+Currently, only C#, C++ and Python are supported in the SDK. Support for Java and Objective-C is planned for future releases.
 
 ::: zone pivot="programming-language-csharp"
 
+To use the text streaming feature, connect to the websocket V2 endpoint: `wss://{region}.tts.speech.microsoft.com/cognitiveservices/websocket/v2`
+
 See the sample code for setting the endpoint:
 
 ```csharp
@@ -360,6 +362,8 @@ For detailed implementation, see the [sample code on GitHub](https://github.com/
 
 ::: zone pivot="programming-language-python"
 
+To use the text streaming feature, connect to the websocket V2 endpoint: `wss://{region}.tts.speech.microsoft.com/cognitiveservices/websocket/v2`
+
 See the sample code for setting the endpoint:
 
 ```python
@@ -385,6 +389,33 @@ For detailed implementation, see the [sample code on GitHub](https://github.com/
 
 ::: zone-end
 
+::: zone pivot="programming-language-cpp"
+
+The C++ sample code isn't available now. For the sample code that shows how to use text streaming, see:
+
+- [C# sample code](https://github.com/Azure-Samples/cognitive-services-speech-sdk/tree/master/samples/csharp/tts-text-stream)
+- [Python sample code](https://github.com/Azure-Samples/cognitive-services-speech-sdk/tree/master/samples/python/tts-text-stream)
+
+::: zone-end
+
+::: zone pivot="programming-language-java"
+
+For the sample code that shows how to use text streaming, see:
+
+- [C# sample code](https://github.com/Azure-Samples/cognitive-services-speech-sdk/tree/master/samples/csharp/tts-text-stream)
+- [Python sample code](https://github.com/Azure-Samples/cognitive-services-speech-sdk/tree/master/samples/python/tts-text-stream)
+
+::: zone-end
+
+::: zone pivot="programming-language-objectivec"
+
+For the sample code that shows how to use text streaming, see:
+
+- [C# sample code](https://github.com/Azure-Samples/cognitive-services-speech-sdk/tree/master/samples/csharp/tts-text-stream)
+- [Python sample code](https://github.com/Azure-Samples/cognitive-services-speech-sdk/tree/master/samples/python/tts-text-stream)
+
+::: zone-end
+
 ## Others tips
 
 ### Cache CRL files

articles/ai-services/speech-service/includes/quickstarts/openai-speech/csharp.md

@@ -230,7 +230,7 @@ Here are some more considerations:
 
 - To change the speech recognition language, replace `en-US` with another [supported language](~/articles/ai-services/speech-service/language-support.md). For example, `es-ES` for Spanish (Spain). The default language is `en-US`. For details about how to identify one of multiple languages that might be spoken, see [language identification](~/articles/ai-services/speech-service/language-identification.md).
 - To change the voice that you hear, replace `en-US-JennyMultilingualNeural` with another [supported voice](~/articles/ai-services/speech-service/language-support.md#prebuilt-neural-voices). If the voice doesn't speak the language of the text returned from Azure OpenAI, the Speech service doesn't output synthesized audio.
-- To reduce latency for text to speech output, use the text streaming feature, which enables real-time text processing for fast audio generation and minimizes latency, enhancing the fluidity and responsiveness of real-time audio outputs. Refer to [how to use text streaming](~/articles/ai-services/speech-service/how-to-lower-speech-synthesis-latency.md#text-streaming).
+- To reduce latency for text to speech output, use the text streaming feature, which enables real-time text processing for fast audio generation and minimizes latency, enhancing the fluidity and responsiveness of real-time audio outputs. Refer to [how to use text streaming](~/articles/ai-services/speech-service/how-to-lower-speech-synthesis-latency.md#input-text-streaming).
 - To enable [TTS Avatar](~/articles/ai-services/speech-service/text-to-speech-avatar/what-is-text-to-speech-avatar.md) as a visual experience of speech output, refer to [real-time synthesis for text to speech avatar](~/articles/ai-services/speech-service/text-to-speech-avatar/real-time-synthesis-avatar.md) and [sample code](https://github.com/Azure-Samples/cognitive-services-speech-sdk/tree/master/samples/js/browser/avatar#chat-sample) for chat scenario with avatar.
 - To use a different [model](/azure/ai-services/openai/concepts/models#model-summary-table-and-region-availability), replace `gpt-35-turbo-instruct` with the ID of another [deployment](/azure/ai-services/openai/how-to/create-resource?pivots=web-portal#deploy-a-model). The deployment ID isn't necessarily the same as the model name. You named your deployment when you created it in [Azure OpenAI Studio](https://oai.azure.com/).
 - Azure OpenAI also performs content moderation on the prompt inputs and generated outputs. The prompts or responses might be filtered if harmful content is detected. For more information, see the [content filtering](/azure/ai-services/openai/concepts/content-filter) article.

articles/ai-services/speech-service/includes/quickstarts/openai-speech/python.md

@@ -177,7 +177,7 @@ Here are some more considerations:
 
 - To change the speech recognition language, replace `en-US` with another [supported language](~/articles/ai-services/speech-service/language-support.md). For example, `es-ES` for Spanish (Spain). The default language is `en-US`. For details about how to identify one of multiple languages that might be spoken, see [language identification](~/articles/ai-services/speech-service/language-identification.md).
 - To change the voice that you hear, replace `en-US-JennyMultilingualNeural` with another [supported voice](~/articles/ai-services/speech-service/language-support.md#prebuilt-neural-voices). If the voice doesn't speak the language of the text returned from Azure OpenAI, the Speech service doesn't output synthesized audio.
-- To reduce latency for text to speech output, use the text streaming feature, which enables real-time text processing for fast audio generation and minimizes latency, enhancing the fluidity and responsiveness of real-time audio outputs. Refer to [how to use text streaming](~/articles/ai-services/speech-service/how-to-lower-speech-synthesis-latency.md#text-streaming).
+- To reduce latency for text to speech output, use the text streaming feature, which enables real-time text processing for fast audio generation and minimizes latency, enhancing the fluidity and responsiveness of real-time audio outputs. Refer to [how to use text streaming](~/articles/ai-services/speech-service/how-to-lower-speech-synthesis-latency.md#input-text-streaming).
 - To enable [TTS Avatar](~/articles/ai-services/speech-service/text-to-speech-avatar/what-is-text-to-speech-avatar.md) as a visual experience of speech output, refer to [real-time synthesis for text to speech avatar](~/articles/ai-services/speech-service/text-to-speech-avatar/real-time-synthesis-avatar.md) and [sample code](https://github.com/Azure-Samples/cognitive-services-speech-sdk/tree/master/samples/js/browser/avatar#chat-sample) for chat scenario with avatar.
 - To use a different [model](/azure/ai-services/openai/concepts/models#model-summary-table-and-region-availability), replace `gpt-35-turbo-instruct` with the ID of another [deployment](/azure/ai-services/openai/how-to/create-resource#deploy-a-model). Keep in mind that the deployment ID isn't necessarily the same as the model name. You named your deployment when you created it in [Azure OpenAI Studio](https://oai.azure.com/).
 - Azure OpenAI also performs content moderation on the prompt inputs and generated outputs. The prompts or responses might be filtered if harmful content is detected. For more information, see the [content filtering](/azure/ai-services/openai/concepts/content-filter) article.

articles/ai-services/speech-service/speech-synthesis-markup-voice.md

@@ -445,7 +445,7 @@ The following table describes the usage of the `mstts:audioduration` element's a
 
 | Attribute | Description | Required or optional |
 | ---------- | ---------- | ---------- |
-| `value` | The requested duration of the output audio in either seconds, such as `2s`, or milliseconds, such as `2000ms`.<br/><br/>This value should be within `0.5` to `2` times the original audio without any other rate settings. For example, if the requested duration of your audio is `30s`, then the original audio must otherwise be between 15 and 60 seconds. If you set a value outside of these boundaries, the duration is set according to the respective minimum or maximum multiple.<br/><br/>Given your requested output audio duration, the Speech service adjusts the speaking rate accordingly. Use the [voice list](rest-text-to-speech.md#get-a-list-of-voices) API and check the `WordsPerMinute` attribute to find out the speaking rate of the neural voice that you're using. You can divide the number of words in your input text by the value of the `WordsPerMinute` attribute to get the approximate original output audio duration. The output audio sounds most natural when you set the audio duration closest to the estimated duration.| Required |
+| `value` | The requested duration of the output audio in either seconds, such as `2s`, or milliseconds, such as `2000ms`.<br/><br/>The maximum value for output audio duration is 300 seconds. This value should be within `0.5` to `2` times the original audio without any other rate settings. For example, if the requested duration of your audio is `30s`, then the original audio must otherwise be between 15 and 60 seconds. If you set a value outside of these boundaries, the duration is set according to the respective minimum or maximum multiple. For output audio longer than 300 seconds, first generate the original audio without any other rate settings, then calculate the rate to adjust using the prosody rate to achieve the desired duration. | Required |
 
 ### mstts audio duration examples
 

articles/azure-app-configuration/rest-api.md

@@ -29,8 +29,3 @@ The documentation on the [control plane](../azure-resource-manager/management/co
 - [Common Headers](./rest-api-headers.md)
 - [Throttling](./rest-api-throttling.md)
 - [Versioning](./rest-api-versioning.md)
-
-## Development
-
-- [Fiddler](./rest-api-fiddler.md)
-- [Postman](./rest-api-postman.md)

articles/azure-monitor/logs/basic-logs-azure-tables.md

@@ -37,8 +37,8 @@ All custom tables created with or migrated to the [Logs ingestion API](logs-inge
  Cosmos DB | [CDBDataPlaneRequests](/azure/azure-monitor/reference/tables/cdbdataplanerequests)<br>[CDBPartitionKeyStatistics](/azure/azure-monitor/reference/tables/cdbpartitionkeystatistics)<br>[CDBPartitionKeyRUConsumption](/azure/azure-monitor/reference/tables/cdbpartitionkeyruconsumption)<br>[CDBQueryRuntimeStatistics](/azure/azure-monitor/reference/tables/cdbqueryruntimestatistics)<br>[CDBMongoRequests](/azure/azure-monitor/reference/tables/cdbmongorequests)<br>[CDBCassandraRequests](/azure/azure-monitor/reference/tables/cdbcassandrarequests)<br>[CDBGremlinRequests](/azure/azure-monitor/reference/tables/cdbgremlinrequests)<br>[CDBControlPlaneRequests](/azure/azure-monitor/reference/tables/cdbcontrolplanerequests)<br>CDBTableApiRequests |
 | Cosmos DB for MongoDB (vCore) | [VCoreMongoRequests](/azure/azure-monitor/reference/tables/VCoreMongoRequests) |
 |  Kubernetes clusters - Azure Arc | [ArcK8sAudit](/azure/azure-monitor/reference/tables/ArcK8sAudit)<br>[ArcK8sAuditAdmin](/azure/azure-monitor/reference/tables/ArcK8sAuditAdmin)<br>[ArcK8sControlPlane](/azure/azure-monitor/reference/tables/ArcK8sControlPlane) |
-| Data Manager for Energy | [OEPDataplaneLogs](/azure/azure-monitor/reference/tables/OEPDataplaneLogs) |
-| Dedicated SQL Pool | [SynapseSqlPoolSqlRequests](/azure/azure-monitor/reference/tables/synapsesqlpoolsqlrequests)<br>[SynapseSqlPoolRequestSteps](/azure/azure-monitor/reference/tables/synapsesqlpoolrequeststeps)<br>[SynapseSqlPoolExecRequests](/azure/azure-monitor/reference/tables/synapsesqlpoolexecrequests)<br>[SynapseSqlPoolDmsWorkers](/azure/azure-monitor/reference/tables/synapsesqlpooldmsworkers)<br>[SynapseSqlPoolWaits](/azure/azure-monitor/reference/tables/synapsesqlpoolwaits) |
+| De-identification Services | [AHDSDeidAuditLogs](/azure/azure-monitor/reference/tables/AHDSDeidAuditLogs) |
+| Data Manager for Energy | [OEPDataplaneLogs](/azure/azure-monitor/reference/tables/OEPDataplaneLogs) | Dedicated SQL Pool | [SynapseSqlPoolSqlRequests](/azure/azure-monitor/reference/tables/synapsesqlpoolsqlrequests)<br>[SynapseSqlPoolRequestSteps](/azure/azure-monitor/reference/tables/synapsesqlpoolrequeststeps)<br>[SynapseSqlPoolExecRequests](/azure/azure-monitor/reference/tables/synapsesqlpoolexecrequests)<br>[SynapseSqlPoolDmsWorkers](/azure/azure-monitor/reference/tables/synapsesqlpooldmsworkers)<br>[SynapseSqlPoolWaits](/azure/azure-monitor/reference/tables/synapsesqlpoolwaits) |
 | DNS Security Policies | [DNSQueryLogs](/azure/azure-monitor/reference/tables/DNSQueryLogs) |
 | Dev Centers | [DevCenterDiagnosticLogs](/azure/azure-monitor/reference/tables/DevCenterDiagnosticLogs)<br>[DevCenterResourceOperationLogs](/azure/azure-monitor/reference/tables/DevCenterResourceOperationLogs)<br>[DevCenterBillingEventLogs](/azure/azure-monitor/reference/tables/DevCenterBillingEventLogs) |
 | Data Transfer | [DataTransferOperations](/azure/azure-monitor/reference/tables/DataTransferOperations) |

articles/data-factory/scenario-ssis-migration-overview.md

@@ -53,7 +53,7 @@ It is also a practical way to use [SSIS DevOps Tools](/sql/integration-services/
 
 | **Package storage type** |How to migrate SSIS packages|How to migrate SSIS jobs|
 |-|-|-|
-|SSISDB|Redeploy packages via SSDT/SSMS to SSISDB hosted in Azure Managed Instance. For more info, see [Deploying SSIS packages in Azure](/sql/integration-services/lift-shift/ssis-azure-deploy-run-monitor-tutorial). |<li> Migrate from SQL Server Agent on premises to SQL Managed Instance agent via scripts/manual copy. For more info, see [run SSIS packages via Azure SQL Managed Instance Agent](how-to-invoke-ssis-package-managed-instance-agent.md) <li>Convert them into ADF pipelines/activities/triggers via scripts/SSMS/ADF portal. For more info, see [SSMS scheduling feature](/sql/integration-services/lift-shift/ssis-azure-schedule-packages-ssms).|
+|SSISDB|Redeploy packages via SSDT/SSMS to SSISDB hosted in Azure SQL or SQL Managed Instance. For more info, see [Deploying SSIS packages in Azure](/sql/integration-services/lift-shift/ssis-azure-deploy-run-monitor-tutorial). |<li> Migrate from SQL Server Agent on premises to SQL Managed Instance agent via scripts/manual copy. For more info, see [run SSIS packages via Azure SQL Managed Instance Agent](how-to-invoke-ssis-package-managed-instance-agent.md) <li>Convert them into ADF pipelines/activities/triggers via scripts/SSMS/ADF portal. For more info, see [SSMS scheduling feature](/sql/integration-services/lift-shift/ssis-azure-schedule-packages-ssms).|
 |File System|Redeploy them to file shares/Azure Files via dtinstall/dtutil/manual copy, or to keep in file systems to access via VNet/Self-Hosted IR. For more info, see [dtutil utility](/sql/integration-services/dtutil-utility).|<li>Migrate from SQL Server Agent on premises to SQL Managed Instance agent via scripts/manual copy. For more info, see [run SSIS packages via Azure SQL Managed Instance Agent](how-to-invoke-ssis-package-managed-instance-agent.md) <li> Migrate with [SSIS Job Migration Wizard in SSMS](how-to-migrate-ssis-job-ssms.md) <li>Convert them into ADF pipelines/activities/triggers via scripts/SSMS/ADF portal. For more info, see [SSMS scheduling feature](/sql/integration-services/lift-shift/ssis-azure-schedule-packages-ssms).|
 |SQL Server (MSDB)|Export them to file systems/file shares/Azure Files via SSMS/dtutil. For more info, see [Exporting SSIS packages](/sql/integration-services/service/package-management-ssis-service#import-and-export-packages).|Convert them into ADF pipelines/activities/triggers via scripts/SSMS/ADF portal. For more info, see [SSMS scheduling feature](/sql/integration-services/lift-shift/ssis-azure-schedule-packages-ssms).|
 |Package Store|Export them to package store via SSMS/dtutil or redeploy them to package store via dtinstall/dtutil/manual copy. For more info, see [Manage packages with Azure-SSIS Integration Runtime package store](azure-ssis-integration-runtime-package-store.md).|<li>Migrate from SQL Server Agent on premises to SQL Managed Instance agent via scripts/manual copy. For more info, see [run SSIS packages via Azure SQL Managed Instance Agent](how-to-invoke-ssis-package-managed-instance-agent.md) <li> Convert them into ADF pipelines/activities/triggers via scripts/SSMS/ADF portal. For more info, see [SSMS scheduling feature](/sql/integration-services/lift-shift/ssis-azure-schedule-packages-ssms).|
@@ -79,4 +79,4 @@ It is also a practical way to use [SSIS DevOps Tools](/sql/integration-services/
 - [Validate SSIS packages deployed to Azure](/sql/integration-services/lift-shift/ssis-azure-validate-packages)
 - [Run SSIS packages deployed in Azure](/sql/integration-services/lift-shift/ssis-azure-run-packages)
 - [Monitor Azure-SSIS Integration Runtime](./monitor-integration-runtime.md#azure-ssis-integration-runtime)
-- [Schedule SSIS package executions in Azure](/sql/integration-services/lift-shift/ssis-azure-schedule-packages)
+- [Schedule SSIS package executions in Azure](/sql/integration-services/lift-shift/ssis-azure-schedule-packages)