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Azure AI Search provides a powerful search engine that can search through a large collection of documents. Copilot Studio supports adding an Azure AI Search connector to use as a knowledge source.
To complete the connection, you need an Azure account. If you don't have an Azure account, you can create an account at Microsoft Azure.
After you create the Azure account, use the following Azure articles to setup and configure Azure AI Search. These articles provide information on the setup and configuration needed to use the Azure AI Search connector as a knowledge source:
- Create an Azure AI Search service in the portal
- Connect to Azure AI Search using keys
- Create a vector index
- Quickstart: Vectorize text and images using the Azure portal
- Integrated data chunking and embedding in Azure AI Search
Note
Currently, you must create vectorized indexes using integrated vectorization. Prepare your data and choose an embedded model, then use Import and vectorize data from Azure AI Search to create vector indexes. This method enables the system to use the same embedded model used to vectorize the data to also vectorize the incoming prompt at runtime, which reduces the need to write special functions to do the same.
Add an Azure AI Search connector
Open the agent.
Select Add knowledge from either the Overview or Knowledge pages, or the Properties of a generative answers node.
From the Add knowledge dialog, select Advanced.
Select Azure AI Search as the connector.
Enter a name and description for the connector. The name must be unique.
Select Create and enter the Authentication type, Azure AI Search Endpoint URL, and Azure AI Search Admin Key.
Select Create again to complete the connection to the connector. A green check mark appears to confirm the connection to the connector.
Select Next.
Enter the Azure AI Search vector index to be used for the connector. Only one vector index can be added.
Select Add to complete the connection.
After you add the connector, it appears in the knowledge sources table. The status displays as In progress while Copilot Studio indexes the metadata in the tables. After the indexing is complete, the status is updated to Ready, and then you can begin testing the knowledge source. During testing, you can verify that proper references were called by reviewing the files and citations cited by the agent.