Merge pull request #267976 from mulander/flex-genai-refer-prereq

Flex genai refer prereq

Author: prmerger-automator[bot]

articles/postgresql/flexible-server/generative-ai-azure-cognitive.md

@@ -17,6 +17,7 @@ Azure AI extension gives the ability to invoke the [language services](../../ai-
 
 ## Prerequisites
 
+1. [Enable and configure](generative-ai-azure-overview.md#enable-the-azure_ai-extension) the `azure_ai` extension.
 1. [Create a Language resource](https://portal.azure.com/#create/Microsoft.CognitiveServicesTextAnalytics) in the Azure portal to get your key and endpoint.  
 1. After it deploys, select **Go to resource**.
 
@@ -66,7 +67,7 @@ For more information, see Cognitive Services Compliance and Privacy notes at htt
 
 #### Return type
 
-`azure_cognitive.sentiment_analysis_result` a result record containing the sentiment predictions of the input text. It contains the sentiment, which can be `positive`, `negative`, `neutral` and `mixed`; and the score for positive, neutral and negative found in the text represented as a real number between 0 and 1. For example in `(neutral,0.26,0.64,0.09)`, the sentiment is `neutral` with `positive` score at `0.26`, neutral at `0.64` and negative at `0.09`.
+`azure_cognitive.sentiment_analysis_result` a result record containing the sentiment predictions of the input text. It contains the sentiment, which can be `positive`, `negative`, `neutral`, and `mixed`; and the score for positive, neutral, and negative found in the text represented as a real number between 0 and 1. For example in `(neutral,0.26,0.64,0.09)`, the sentiment is `neutral` with `positive` score at `0.26`, neutral at `0.64` and negative at `0.09`.
 
 
 ### `azure_cognitive.detect_language`
@@ -99,7 +100,7 @@ For more information, see Cognitive Services Compliance and Privacy notes at htt
 
 #### Return type
 
-`azure_cognitive.language_detection_result`, a result containing the detected language name, its two-letter ISO 639-1 representation and the confidence score for the detection. For example in `(Portuguese,pt,0.97)`, the language is `Portuguese`, and detection confidence is `0.97`.
+`azure_cognitive.language_detection_result`, a result containing the detected language name, its two-letter ISO 639-1 representation, and the confidence score for the detection. For example in `(Portuguese,pt,0.97)`, the language is `Portuguese`, and detection confidence is `0.97`.
 
 ### `azure_cognitive.extract_key_phrases`
 
@@ -250,7 +251,7 @@ For more information, see Cognitive Services Compliance and Privacy notes at htt
 
 #### Return type
 
-`azure_cognitive.pii_entity_recognition_result`, a result containing the redacted text and entities as `azure_cognitive.entity[]`. Each entity contains the nonredacted text, personal data category, subcategory and a score indicating the confidence that the entity correctly matches the identified substring. For example, if invoked with a `text` set to `'My phone number is +1555555555, and the address of my office is 16255 NE 36th Way, Redmond, WA 98052.'`, and `language` set to `'en'`, it could return `("My phone number is ***********, and the address of my office is ************************************.","{""(+1555555555,PhoneNumber,\\""\\"",0.8)"",""(\\""16255 NE 36th Way, Redmond, WA 98052\\"",Address,\\""\\"",1)""}")`.
+`azure_cognitive.pii_entity_recognition_result`, a result containing the redacted text, and entities as `azure_cognitive.entity[]`. Each entity contains the nonredacted text, personal data category, subcategory, and a score indicating the confidence that the entity correctly matches the identified substring. For example, if invoked with a `text` set to `'My phone number is +1555555555, and the address of my office is 16255 NE 36th Way, Redmond, WA 98052.'`, and `language` set to `'en'`, it could return `("My phone number is ***********, and the address of my office is ************************************.","{""(+1555555555,PhoneNumber,\\""\\"",0.8)"",""(\\""16255 NE 36th Way, Redmond, WA 98052\\"",Address,\\""\\"",1)""}")`.
 
 ### `azure_cognitive.summarize_abstractive`
 

articles/postgresql/flexible-server/generative-ai-azure-openai.md

@@ -19,13 +19,14 @@ Invoke [Azure OpenAI embeddings](../../ai-services/openai/reference.md#embedding
 
 ## Prerequisites
 
+1. [Enable and configure](generative-ai-azure-overview.md#enable-the-azure_ai-extension) the `azure_ai` extension.
 1. Create an Open AI account and [request access to Azure OpenAI Service](https://aka.ms/oai/access).
 1. Grant Access to Azure OpenAI in the desired subscription.
 1. Grant permissions to [create Azure OpenAI resources and to deploy models](../../ai-services/openai/how-to/role-based-access-control.md).
 1. [Create and deploy an Azure OpenAI service resource and a model](../../ai-services/openai/how-to/create-resource.md), for example deploy the embeddings model [text-embedding-ada-002](../../ai-services/openai/concepts/models.md#embeddings-models). Copy the deployment name as it is needed to create embeddings. 
 ## Configure OpenAI endpoint and key
 
-In the Azure OpenAI resource, under **Resource Management** > **Keys and Endpoints** you can find the endpoint and the keys for your Azure OpenAI resource. Use the endpoint and one of the keys to enable `azure_ai` extension to invoke the model deployment.
+In the Azure OpenAI resource, under **Resource Management** > **Keys and Endpoints** you can find the endpoint and the keys for your Azure OpenAI resource. To invoke the model deployment, enable the `azure_ai` extension using the endpoint and one of the keys.
 
 ```postgresql
 select azure_ai.set_setting('azure_openai.endpoint','https://<endpoint>.openai.azure.com');