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

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# Understand embeddings in Azure OpenAI Service
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An embedding is a special format of data representation that machine learning models and algorithms can easily use. The embedding is an information dense representation of the semantic meaning of a piece of text. Each embedding is a vector of floating-point numbers, such that the distance between two embeddings in the vector space is correlated with semantic similarity between two inputs in the original format. For example, if two texts are similar, then their vector representations should also be similar. Embeddings power vector similarity search in Azure Databases such as [Azure Cosmos DB for MongoDB vCore](../../../cosmos-db/mongodb/vcore/vector-search.md) or [Azure Database for PostgreSQL - Flexible Server](../../../postgresql/flexible-server/how-to-use-pgvector.md).
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An embedding is a special format of data representation that machine learning models and algorithms can easily use. The embedding is an information dense representation of the semantic meaning of a piece of text. Each embedding is a vector of floating-point numbers, such that the distance between two embeddings in the vector space is correlated with semantic similarity between two inputs in the original format. For example, if two texts are similar, then their vector representations should also be similar. Embeddings power vector similarity search in Azure Databases such as [Azure Cosmos DB for MongoDB vCore](../../../cosmos-db/mongodb/vcore/vector-search.md) , [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](../../../postgresql/flexible-server/how-to-use-pgvector.md).
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## Embedding models
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## Next steps
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* Learn more about using Azure OpenAI and embeddings to perform document search with our [embeddings tutorial](../tutorials/embeddings.md).
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* Store your embeddings and perform vector (similarity) search using [Azure Cosmos DB for MongoDB vCore](../../../cosmos-db/mongodb/vcore/vector-search.md), [Azure Cosmos DB for NoSQL](../../../cosmos-db/rag-data-openai.md) or [Azure Database for PostgreSQL - Flexible Server](../../../postgresql/flexible-server/how-to-use-pgvector.md).
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* Store your embeddings and perform vector (similarity) search using [Azure Cosmos DB for MongoDB vCore](../../../cosmos-db/mongodb/vcore/vector-search.md), [Azure Cosmos DB for NoSQL](../../../cosmos-db/rag-data-openai.md) , [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](../../../postgresql/flexible-server/how-to-use-pgvector.md).

articles/ai-services/openai/tutorials/embeddings.md

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* Store your embeddings and perform vector (similarity) search using your choice of Azure service:
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* [Azure AI Search](../../../search/vector-search-overview.md)
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* [Azure Cosmos DB for MongoDB vCore](../../../cosmos-db/mongodb/vcore/vector-search.md)
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* [Azure SQL Database](/azure/azure-sql/database/ai-artificial-intelligence-intelligent-applications?view=azuresql&preserve-view=true#vector-search)
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* [Azure Cosmos DB for NoSQL](../../../cosmos-db/vector-search.md)
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* [Azure Cosmos DB for PostgreSQL](../../../cosmos-db/postgresql/howto-use-pgvector.md)
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* [Azure Cache for Redis](../../../azure-cache-for-redis/cache-tutorial-vector-similarity.md)

articles/app-service/environment/how-to-migrate.md

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@@ -305,7 +305,7 @@ This step takes three to six hours for v2 to v3 migrations and up to six hours f
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>
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> :::image type="content" source="./media/migration/migration-error-2.png" alt-text="Screenshot that shows the potential error notification after migration starts.":::
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At this time, detailed migration statuses are available only when you're using the Azure CLI. For more information, see the [Azure CLI section for migrating to App Service Environment v3](#8-migrate-to-app-service-environment-v3-and-check-status).
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At this time, detailed migration statuses are available only when you're using the Azure CLI. For more information, see the Azure CLI section for migrating to App Service Environment v3. You can check the status of the migration with the CLI even if you use the portal to do the migration.
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When migration is complete, you have an App Service Environment v3 resource, and all of your apps are running in your new environment. You can confirm the environment's version by checking the **Configuration** page for your App Service Environment.
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articles/app-service/environment/migrate.md

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- If you can't support downtime, see the [side-by-side migration feature](side-by-side-migrate.md) or the [migration-alternatives](migration-alternatives.md#migrate-manually).
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- The public addresses that are used by the App Service Environment change to the IPs generated during the IP generation step.
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The following statuses are available during the migration process:
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|Status |Description |
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|------------|-------------|
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|Validating and preparing the migration. |The platform is validating migration support and performing necessary checks. |
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|Deploying App Service Environment v3 infrastructure. |Your new App Service Environment v3 infrastructure is provisioning. |
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|Waiting for infrastructure to complete. |The platform is validating your new infrastructure and performing necessary checks. |
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|Setting up networking. Migration downtime period has started. Applications are not accessible. |The platform is deleting your old infrastructure and moving all of your apps to your new App Service Environment v3. Your apps are down and aren't accepting traffic. |
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|Running post migration validations. |The platform is performing necessary checks to ensure the migration succeeded. |
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|Finalizing migration. |The platform is finalizing the migration. |
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As in the IP generation step, you can't scale, modify your App Service Environment, or deploy apps to it during this process. When migration is complete, the apps that were on the old App Service Environment are running on the new App Service Environment v3.
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## Pricing

articles/communication-services/quickstarts/voice-video-calling/includes/get-started/get-started-android.md

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:::image type="content" source="../../media/android/studio-new-project.png" alt-text="Screenshot showing the 'Start a new Android Studio Project' button selected in Android Studio.":::
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Select "Empty Activity" project template under "Phone and Tablet".
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Select "Empty Views Activity" project template under "Phone and Tablet".
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:::image type="content" source="../../media/android/studio-blank-activity.png" alt-text="Screenshot showing the 'Empty Activity' option selected in the Project Template Screen.":::
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### Install the package
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<!-- TODO: update with instructions on how to download, install and add package to project -->
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Locate your project level build.gradle and make sure to add `mavenCentral()` to the list of repositories under `buildscript` and `allprojects`
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Locate your project `settings.gradle.kts` and make sure to see `mavenCentral()` at the list of repositories under `pluginManagement` and `dependencyResolutionManagement`
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```groovy
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buildscript {
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pluginManagement {
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repositories {
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...
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mavenCentral()
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...
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}
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}
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```
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```groovy
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allprojects {
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dependencyResolutionManagement {
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repositoriesMode.set(RepositoriesMode.FAIL_ON_PROJECT_REPOS)
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repositories {
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...
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mavenCentral()
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...
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}
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}
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```
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```groovy
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android {
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...
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packagingOptions {
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pickFirst 'META-INF/*'
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}
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compileOptions {
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sourceCompatibility JavaVersion.VERSION_1_8
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dependencies {
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implementation 'com.azure.android:azure-communication-calling:1.0.0-beta.8'
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implementation ("com.azure.android:azure-communication-calling:2.6.0")
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}
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```
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android:ems="10"
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android:hint="Callee Id"
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android:minHeight="48dp"
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app:layout_constraintBottom_toTopOf="@+id/call_button"
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app:layout_constraintEnd_toEndOf="parent"
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app:layout_constraintStart_toStartOf="parent"
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import java.util.ArrayList;
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public class MainActivity extends AppCompatActivity {
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* Request each required permission if the app doesn't already have it.
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private void getAllPermissions() {
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String[] requiredPermissions = new String[]{Manifest.permission.RECORD_AUDIO, Manifest.permission.CAMERA, Manifest.permission.WRITE_EXTERNAL_STORAGE, Manifest.permission.READ_PHONE_STATE};
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String[] requiredPermissions = new String[]{android.Manifest.permission.RECORD_AUDIO, android.Manifest.permission.CAMERA, android.Manifest.permission.WRITE_EXTERNAL_STORAGE, Manifest.permission.READ_PHONE_STATE};
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ArrayList<String> permissionsToAskFor = new ArrayList<>();
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for (String permission : requiredPermissions) {
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}
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if (!permissionsToAskFor.isEmpty()) {
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try {
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CommunicationTokenCredential credential = new CommunicationTokenCredential(userToken);
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callAgent = new CallClient().createCallAgent(getApplicationContext(), credential).get();
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CommunicationTokenCredential credential = new CommunicationTokenCredential(userToken);
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callAgent = new CallClient().createCallAgent(getApplicationContext(), credential).get();
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getApplicationContext(),
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options);
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getApplicationContext(),
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Arrays.asList(new CommunicationUserIdentifier[]{new CommunicationUserIdentifier(calleeId)}),
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options);
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articles/communication-services/quickstarts/voice-video-calling/includes/get-started/get-started-windows.md

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#### Install the package
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Right select your project and go to `Manage Nuget Packages` to install `Azure.Communication.Calling.WindowsClient` [1.2.0-beta.1](https://www.nuget.org/packages/Azure.Communication.Calling.WindowsClient/1.2.0-beta.1) or superior. Make sure Include Preleased is checked.
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Right select your project and go to `Manage Nuget Packages` to install `Azure.Communication.Calling.WindowsClient` [1.4.0](https://www.nuget.org/packages/Azure.Communication.Calling.WindowsClient/1.4.0) or superior. Make sure `Include Prerelease` is checked if you want to see the versions for public preview.
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mc:Ignorable="d"
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<!-- Don't forget to replace ‘CallingQuickstart’ with your project’s name -->
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<Grid>
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### Make call button work
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The call state must be changed using the `OnStateChangedAsync` action.
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}
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}
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```
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### Run the code
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You can build and run the code on Visual Studio. For solution platforms, we support `ARM64`, `x64` and `x86`.
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You can build and run the code on Visual Studio. For solution platforms, we support `ARM64`, `x64`, and `x86`.
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You can make an outbound call by providing a user ID in the text field and clicking the `Start Call/Join` button. Calling `8:echo123` connects you with an echo bot, this feature is great for getting started and verifying your audio devices are working.
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private async Task<CommunicationCall> StartCallAsync(string acsCallee)
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{
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var options = new StartCallOptions();
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var call = await this.callAgent.StartCallAsync( new [] { new UserCallIdentifier(acsCallee) }, options);
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