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Copy file name to clipboardExpand all lines: articles/search/search-get-started-portal-import-vectors.md
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@@ -81,7 +81,7 @@ In the following sections, you can assign the search service's managed identity
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## Check for semantic ranking
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This wizard supports semantic ranking, but only on the Basic tier and higher, and only if semantic ranking is already [enabled on your search service](semantic-how-to-enable-disable.md). If you're using a billable tier, check whether semantic ranking is enabled.
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The wizard supports semantic ranking, but only on the Basic tier and higher, and only if semantic ranking is already [enabled on your search service](semantic-how-to-enable-disable.md). If you're using a billable tier, check whether semantic ranking is enabled.
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## Prepare sample data
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1. Assign permissions at the workspace level:
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1. On the upper-right menu, select **Manage access**.
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1. Select **Add people or groups**.
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1. Enter the name of your search service. For example, if the URL is `https://my-demo-service.search.windows.net`, the search service name is `my-demo-service`.
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1. Select a role. The default is **Viewer**, but you need **Contributor** to pull data into a search index.
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1. Load the sample data:
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1. Make sure your Azure AI Search service is in the same region.
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1. After the service is deployed, go to the resource and select **Access control** to assign the **Cognitive Services OpenAI Contributor** role to your search service's managed identity. Optionally, you can use key-based authentication for the connection.
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1. After the service is deployed, go to the resource and select **Access control** to assign the **Cognitive Services OpenAI User** role to your search service's managed identity. Optionally, you can use key-based authentication for the connection.
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After you finish these steps, you should be able to select the Azure AI Vision vectorizer in the **Import and vectorize data** wizard.
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1. Specify the subscription.
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1. For the Azure AI Studio model catalog, specify the project and deployment. For more information, see [Setting up an embedding model](#set-up-embedding-models).
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1. For the Azure AI Studio model catalog, specify the project and deployment. For more information, see [Set up embedding models](#set-up-embedding-models) earlier in this article.
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1. Optionally, you can crack binary images (for example, scanned document files) and [use OCR](cognitive-search-skill-ocr.md) to recognize text.
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