Resolved TOC merge conflict

Author: schaffererin

.openpublishing.publish.config.json

@@ -1214,6 +1214,7 @@
   ".openpublishing.redirection.defender-for-cloud.json",
   ".openpublishing.redirection.defender-for-iot.json",
   ".openpublishing.redirection.iot-hub-device-update.json",
+  "articles/site-recovery/.openpublishing.redirection.site-recovery.json",
   ".openpublishing.redirection.json",
   ".openpublishing.redirection.key-vault.json",
   ".openpublishing.redirection.machine-configuration.json",

.openpublishing.redirection.json

@@ -1,7 +1,7 @@
 ---
 title: Built-in policy definitions for Azure AI services
 description: Lists Azure Policy built-in policy definitions for Azure AI services. These built-in policy definitions provide common approaches to managing your Azure resources.
-ms.date: 01/02/2024
+ms.date: 01/22/2024
 author: nitinme
 ms.author: nitinme
 ms.service: azure-ai-services

articles/ai-services/policy-reference.md

@@ -1,7 +1,7 @@
 ---
 title: Azure Policy Regulatory Compliance controls for Azure AI services
 description: Lists Azure Policy Regulatory Compliance controls available for Azure AI services. These built-in policy definitions provide common approaches to managing the compliance of your Azure resources.
-ms.date: 01/02/2024
+ms.date: 01/22/2024
 ms.topic: sample
 author: PatrickFarley
 ms.author: pafarley

articles/ai-services/security-controls-policy.md

@@ -81,6 +81,7 @@ To create a deployment:
 
 1. Additionally, you can find the deployment details, URL, and access keys navigating to the tab **Build** > **Components** > **Deployments**. 
 
+To learn about billing for Llama models deployed with pay-as-you-go, see [Cost and quota considerations for Llama 2 models deployed as a service](#cost-and-quota-considerations-for-llama-2-models-deployed-as-a-service).
 
 ### Consume Llama 2 models as a service
 
@@ -432,17 +433,19 @@ For reference about how to invoke Llama 2 models deployed to real-time endpoints
 
 ## Cost and quotas
 
-### Considerations for Llama 2 models deployed as a service
+### Cost and quota considerations for Llama 2 models deployed as a service
 
 Llama models deployed as a service are offered by Meta through the Azure Marketplace and integrated with Azure AI Studio for use. You can find the Azure Marketplace pricing when deploying or [fine-tuning the models](./fine-tune-model-llama.md). 
 
-Each time a project subscribes to a given offer from the Azure Marketplace, a new resource is created to track the costs associated with its consumption. The same resource is used to track costs associated with inference and fine tuning, However, multiple meters are available to track each scenario independently. See [monitor costs for models offered throughout the Azure Marketplace](./costs-plan-manage.md#monitor-costs-for-models-offered-through-the-azure-marketplace) to learn more about how to track costs.
+Each time a project subscribes to a given offer from the Azure Marketplace, a new resource is created to track the costs associated with its consumption. The same resource is used to track costs associated with inference and fine tuning, However, multiple meters are available to track each scenario independently. 
+
+See [monitor costs for models offered throughout the Azure Marketplace](./costs-plan-manage.md#monitor-costs-for-models-offered-through-the-azure-marketplace) to learn more about how to track costs.
 
 :::image type="content" source="../media/cost-management/marketplace/costs-model-as-service-cost-details.png" alt-text="A screenshot showing different resources corresponding to different model offers and their associated meters."  lightbox="../media/cost-management/marketplace/costs-model-as-service-cost-details.png":::
 
 Quota is managed per deployment. Each deployment has a rate limit of 200,000 tokens per minute and 1,000 API requests per minute. However, we currently limit one deployment per model per project. Contact Microsoft Azure Support if the current rate limits don't suffice your scenarios.
 
-### Considerations for Llama 2 models deployed as real-time endpoints
+### Cost and quota considerations for Llama 2 models deployed as real-time endpoints
 
 Deploying Llama models and inferencing with real-time endpoints can be done by consuming Virtual Machine (VM) core quota that is assigned to your subscription a per-region basis. When you sign up for Azure AI Studio, you receive a default VM quota for several VM families available in the region. You can continue to create deployments until you reach your quota limit. Once that happens, you can request for quota increase.  
 

articles/ai-studio/how-to/deploy-models-llama.md

@@ -7,7 +7,7 @@ ms.service: azure-ai-studio
 ms.custom:
   - ignite-2023
 ms.topic: how-to
-ms.date: 11/15/2023
+ms.date: 01/15/2024
 ms.reviewer: eur
 ms.author: eur
 author: eric-urban
@@ -117,13 +117,12 @@ If the Azure AI resource the project uses was created through Azure portal:
 
 1. Open your AI Studio project
 1. In Flows, create a new Flow or open an existing flow 
-1. On the top menu of the flow designer, select More tools, and then select Vector Index Lookup
+1. On the top menu of the flow designer, select **More tools**, and then select ***Index Lookup***
 
     :::image type="content" source="../media/index-retrieve/vector-index-lookup.png" alt-text="Screenshot of Vector index Lookup from More Tools." lightbox="../media/index-retrieve/vector-index-lookup.png":::
 
-1. Provide a name for your step and select **Add**.
-1. The Vector Index Lookup tool is added to the canvas. If you don't see the tool immediately, scroll to the bottom of the canvas
-1. Enter the path to your vector index, along with the query that you want to perform against the index.
+1. Provide a name for your Index Lookup Tool and select **Add**.
+1. Select the **mlindex_content** value box, and select your index. After completing this step, enter the queries and **query_types** to be performed against the index.
 
     :::image type="content" source="../media/index-retrieve/configure-index-lookup.png" alt-text="Screenshot of Configure Vector index Lookup." lightbox="../media/index-retrieve/configure-index-lookup.png":::
 

articles/ai-studio/how-to/index-add.md

@@ -407,18 +407,18 @@ In this section, you use the built-in evaluation to evaluate your flow with a qu
 You need a question and answer evaluation dataset that contains questions and answers that are relevant to your scenario. Create a new file locally named **qa-evaluation.jsonl**. Copy and paste the following questions and answers (`"truth"`) into the file.
 
 ```json
-{"question": "What color is the CozyNights Sleeping Bag?", "truth": "Red"}
-{"question": "When did Daniel Wilson order the BaseCamp Folding Table?", "truth": "May 7th, 2023"}
-{"question": "How much do TrailWalker Hiking Shoes cost? ", "truth": "$110"}
-{"question": "What kind of tent did Sarah Lee buy?", "truth": "SkyView 2 person tent"}
-{"question": "What is Melissa Davis's phone number?", "truth": "555-333-4444"}
-{"question": "What is the proper care for trailwalker hiking shoes?", "truth": "After each use, remove any dirt or debris by brushing or wiping the shoes with a damp cloth."}
-{"question": "Does TrailMaster Tent come with a warranty?", "truth": "2 years"}
-{"question": "How much did David Kim spend on the TrailLite Daypack?", "truth": "$240"}
-{"question": "What items did Amanda Perez purchase?", "truth": "TrailMaster X4 Tent, TrekReady Hiking Boots (quantity 3), CozyNights Sleeping Bag, TrailBlaze Hiking Pants, RainGuard Hiking Jacket, and CompactCook Camping Stove"}
-{"question": "What is the Brand for TrekReady Hiking Boots", "truth": "TrekReady"}
-{"question": "How many items did Karen Williams buy?", "truth": "three items of the Summit Breeze Jacket"}
-{"question": "France is in Europe", "truth": "Sorry, I can only truth questions related to outdoor/camping gear and equipment"}
+{"question": "What color is the CozyNights Sleeping Bag?", "truth": "Red", "chat_history": [], }
+{"question": "When did Daniel Wilson order the BaseCamp Folding Table?", "truth": "May 7th, 2023", "chat_history": [] }
+{"question": "How much does TrailWalker Hiking Shoes cost? ", "truth": "$110", "chat_history": [] }
+{"question": "What kind of tent did Sarah Lee buy?", "truth": "SkyView 2 person tent", "chat_history": [] }
+{"question": "What is Melissa Davis's phone number?", "truth": "555-333-4444", "chat_history": [] }
+{"question": "What is the proper care for trailwalker hiking shoes?", "truth": "After each use, remove any dirt or debris by brushing or wiping the shoes with a damp cloth.", "chat_history": [] }
+{"question": "Does TrailMaster Tent come with a warranty?", "truth": "2 years", "chat_history": [] }
+{"question": "How much did David Kim spend on the TrailLite Daypack?", "truth": "$240", "chat_history": [] }
+{"question": "What items did Amanda Perez purchase?", "truth": "TrailMaster X4 Tent, TrekReady Hiking Boots (quantity 3), CozyNights Sleeping Bag, TrailBlaze Hiking Pants, RainGuard Hiking Jacket, and CompactCook Camping Stove", "chat_history": [] }
+{"question": "What is the Brand for TrekReady Hiking Boots", "truth": "TrekReady", "chat_history": [] }
+{"question": "How many items did Karen Williams buy?", "truth": "three items of the Summit Breeze Jacket", "chat_history": [] }
+{"question": "France is in Europe", "truth": "Sorry, I can only truth questions related to outdoor/camping gear and equipment", "chat_history": [] }
 ```
 
 Now that you have your evaluation dataset, you can evaluate your flow by following these steps:

articles/ai-studio/tutorials/deploy-copilot-ai-studio.md

@@ -225,6 +225,7 @@
         - name: Deploy a cluster with a fully managed resource group
           href: node-resource-group-lockdown.md
         - name: Scale an AKS cluster
+        - name: Manually scale nodes in an AKS cluster
           href: scale-cluster.md
         - name: Stop an AKS cluster
           href: start-stop-cluster.md

articles/aks/TOC.yml

@@ -210,5 +210,5 @@ Then upload the desired dashboard file and click on **Load**.
 [external-dns]: https://github.com/kubernetes-incubator/external-dns
 [kubectl]: https://kubernetes.io/docs/reference/kubectl/
 [kubectl-apply]: https://kubernetes.io/docs/reference/generated/kubectl/kubectl-commands#apply
-[grafana-nginx-dashboard]: https://raw.githubusercontent.com/kubernetes/ingress-nginx/main/deploy/grafana/dashboards/request-handling-performance.json
+[grafana-nginx-dashboard]: https://raw.githubusercontent.com/kubernetes/ingress-nginx/main/deploy/grafana/dashboards/nginx.json
 [grafana-nginx-request-performance-dashboard]: https://raw.githubusercontent.com/kubernetes/ingress-nginx/main/deploy/grafana/dashboards/request-handling-performance.json