update

Author: mrbullwinkle

articles/ai-services/openai/concepts/use-your-data.md

@@ -315,7 +315,7 @@ Azure OpenAI on your data provides several search options you can use when you a
 * [Keyword search](/azure/search/search-lucene-query-architecture)
 
 * [Semantic search](/azure/search/semantic-search-overview)
-* [Vector search](/azure/search/vector-search-overview) using Ada [embedding](./understand-embeddings.md) models, available in [select regions](models.md#embeddings-models-1). 
+* [Vector search](/azure/search/vector-search-overview) using Ada [embedding](./understand-embeddings.md) models, available in [select regions](models.md#embeddings-models). 
 
     To enable vector search, you will need a `text-embedding-ada-002` deployment in your Azure OpenAI resource. Select your embedding deployment when connecting your data, then select one of the vector search types under **Data management**.  
 

articles/ai-services/openai/reference.md

@@ -398,7 +398,7 @@ The following parameters can be used inside of the `parameters` field inside of
 | `filter` | string | Optional | null | The filter pattern used for [restricting access to sensitive documents](./concepts/use-your-data.md#document-level-access-control)
 | `embeddingEndpoint` | string | Optional | null | The endpoint URL for an Ada embedding model deployment, generally of the format `https://YOUR_RESOURCE_NAME.openai.azure.com/openai/deployments/YOUR_DEPLOYMENT_NAME/embeddings?api-version=2023-05-15`. Use with the `embeddingKey` parameter  for [vector search](./concepts/use-your-data.md#search-options) outside of private networks and private endpoints. | 
 | `embeddingKey` | string | Optional | null | The API key for an Ada embedding model deployment. Use with `embeddingEndpoint` for [vector search](./concepts/use-your-data.md#search-options) outside of private networks and private endpoints. | 
-| `embeddingDeploymentName` | string | Optional | null | The Ada embedding model deployment name within the same Azure OpenAI resource. Used instead of `embeddingEndpoint` and `embeddingKey` for [vector search](./concepts/use-your-data.md#search-options). Should only be used when both the `embeddingEndpoint` and `embeddingKey` parameters are defined. When this parameter is provided, Azure OpenAI on your data will use an internal call to evaluate the Ada embedding model, rather than calling  the Azure OpenAI endpoint. This enables you to use vector search in private networks and private endpoints. Billing remains the same whether this parameter is defined or not. Available in regions where embedding models are [available](./concepts/models.md#embeddings-models-1) starting in API versions `2023-06-01-preview` and later.|
+| `embeddingDeploymentName` | string | Optional | null | The Ada embedding model deployment name within the same Azure OpenAI resource. Used instead of `embeddingEndpoint` and `embeddingKey` for [vector search](./concepts/use-your-data.md#search-options). Should only be used when both the `embeddingEndpoint` and `embeddingKey` parameters are defined. When this parameter is provided, Azure OpenAI on your data will use an internal call to evaluate the Ada embedding model, rather than calling  the Azure OpenAI endpoint. This enables you to use vector search in private networks and private endpoints. Billing remains the same whether this parameter is defined or not. Available in regions where embedding models are [available](./concepts/models.md#embeddings-models) starting in API versions `2023-06-01-preview` and later.|
 
 ### Start an ingestion job