Documentation

You can access this dialog as part of the connector configuration, if the connector has Azure AI Search as target.

1. Document index name: this is the name of the document index.

2. Principal index name: this is the name of the principal index. The principal index is where the connector stores user-group relationships.

3. Service name: This is the name of the service as part of https://[service name].search.windows.net.

4. API Key: is the API key as extracted in Step 2 in the prerequisites above.

5. Response timeout: determines the timeout when waiting for Azure AI Search responses in milliseconds.

6. Connection timeout: determines the timeout when waiting for connections to Azure AI Search in milliseconds.

7. Socket timeout: determines the timeout when waiting for connections to Azure AI Search in milliseconds.

8. Vector field for body. If you use vector search, then this field is used to push the vectorized body into.

9. Vector field for title. If you use vector search for the vectorization stages), then this field is used to push the vectorized title into.

When finished with setting these fields, click on validate and save. If you observe any issues, then the validator will let you know or you can find more insights in the log files.

Vector Search Dimensions

When using vector search, you need to make sure that the embeddings you use in the query, as well as in the content transformation pipeline have exactly the same dimension as the index fields vector body and vector title. Otherwise indexing or querying the index will fail.