screenshot edits

Author: lgayhardt

articles/machine-learning/prompt-flow/get-started-prompt-flow.md

@@ -233,13 +233,13 @@ To understand how this accuracy was calculated, you can view the evaluation resu
 
 :::image type="content" source="./media/get-started-prompt-flow/check-outputs-for-each-row-of-data.png" alt-text="Screenshot of Web classification batch run detail page on the output tab." lightbox = "./media/get-started-prompt-flow/check-outputs-for-each-row-of-data.png":::
 
-You can adjust column width, hide/unhide columns, and select **Export** to download a csv file of the batch run outputs for further investigation. 
+You can adjust column width, hide/unhide columns, and select **Export** to download a csv file of the batch run outputs for further investigation.
 
 As you might know, accuracy isn't the only metric that can evaluate a classification task, for example you can also use recall to evaluate. In this case, you can select **New evaluation**, choose other evaluation methods to evaluate.
 
 ## Deployment
 
-After you build a flow and test it properly, you may want to deploy it as an endpoint so that you can invoke the endpoint for real-time inference. You can refer to [this article](how-to-deploy-for-real-time-inference.md) for a detailed guidance.
+After you build a flow and test it properly, you may want to [deploy it as an endpoint so that you can invoke the endpoint for real-time inference.](how-to-deploy-for-real-time-inference.md)
 
 ### Configure the endpoint
 

articles/machine-learning/prompt-flow/how-to-develop-a-standard-flow.md

@@ -159,9 +159,9 @@ Below are common scenarios for linking nodes together.
 2. Edit the prompt box, add an input by `{{url}}`, select **Validate and parse input**, then you'll see an input called URL is created in inputs section.
 3. In the value drop-down, select ${inputs.url}, then you'll see in the graph view that the newly created LLM node is linked to the flow input. When running the flow, the URL input of the node will be replaced by flow input on the fly.
 
-:::image type="content" source="./media/how-to-develop-a-standard-flow/link-llm-node-input-1-1.png" alt-text="picture of scenario one showing the LLM tool and editing the prompt (step1). " lightbox = "./media/how-to-develop-a-standard-flow/link-llm-node-input-1-1.png":::
+:::image type="content" source="./media/how-to-develop-a-standard-flow/link-llm-node-input-1-1.png" alt-text="Screenshot of scenario one showing the LLM tool and editing the prompt in step 1. " lightbox = "./media/how-to-develop-a-standard-flow/link-llm-node-input-1-1.png":::
 
-:::image type="content" source="./media/how-to-develop-a-standard-flow/link-llm-node-input-1-2.png" alt-text="picture of scenario one showing the LLM tool and editing the prompt (step2). " lightbox = "./media/how-to-develop-a-standard-flow/link-llm-node-input-1-2.png":::
+:::image type="content" source="./media/how-to-develop-a-standard-flow/link-llm-node-input-1-2.png" alt-text="Screenshot of scenario one showing the LLM tool and editing the prompt in step 2. " lightbox = "./media/how-to-develop-a-standard-flow/link-llm-node-input-1-2.png":::
 
 ### Scenario 2 - Link LLM node with single-output upstream node