freshness for playgrounds article

AB#475801

Author: msakande

articles/ai-foundry/concepts/concept-playgrounds.md

@@ -1,45 +1,45 @@
 ---
 title: Azure AI Foundry Playgrounds
 titleSuffix: Azure AI Foundry
-description: Learn to use Azure AI Foundry playgrounds for exploration, experimentation, and iteration with different models.
+description: Learn how to use Azure AI Foundry playgrounds for rapid prototyping, experimentation, and validation with AI models before production deployment.
 ms.service: azure-ai-foundry
 ms.topic: concept-article
-ms.date: 06/09/2025
+ms.date: 09/22/2025
 ms.author: mopeakande
 author: msakande
 ms.reviewer: tgokal
 manager: nitinme
 reviewer: tgokal
 ms.custom: build-2025 ai-assisted
-#customer intent: I'm a developer and want to use Azure AI Foundry Playground for quick experimentation and prototyping with models and agents before going to code.
+#CustomerIntent: As a developer, I want to use Azure AI Foundry playgrounds for rapid prototyping and experimentation with AI models and agents so that I can validate ideas, test API behavior, and optimize prompts before writing production code.
 ---
 
 # Azure AI Foundry Playgrounds
 
 [!INCLUDE [feature-preview](../includes/feature-preview.md)]
 
-As you build with state-of-the-art models and build agents and apps with them, Azure AI Foundry playgrounds provide an on-demand, zero-setup environment designed for rapid prototyping, API exploration, and technical validation before you commit a single line of code to your production codebase.
+As you build with state-of-the-art models and create agents and apps with them, Azure AI Foundry playgrounds provide an on-demand, zero-setup environment designed for rapid prototyping, API exploration, and technical validation before you commit a single line of code to your production codebase.
 
 ## Highlights of the Azure AI Foundry playgrounds experience
 
 Some highlights of the Azure AI Foundry playgrounds experience include:
 
 - **AgentOps support** for Evaluations and Tracing in the **Agents playground.**
-- **Open in VS Code** for Chat and Agents playground. This feature saves you time by automatically importing your endpoint and key from Azure AI Foundry to VS Code for multi-lingual code samples.
+- **Open in VS Code** for Chat and Agents playground. This feature saves you time by automatically importing your endpoint and key from Azure AI Foundry to VS Code for multilingual code samples.
 - **Images Playground 2.0** for [gpt-image-1](https://ai.azure.com/explore/models/gpt-image-1/version/2025-04-15/registry/azure-openai/?cid=learnDocs), [Stable Diffusion 3.5 Large](https://ai.azure.com/explore/models/Stable-Diffusion-3.5-Large/version/1/registry/azureml-stabilityai/?cid=learnDocs), and [Bria 2.3 Fast](https://ai.azure.com/explore/models/Bria-2.3-Fast/version/1/registry/azureml-bria/?cid=learnDocs) models.
 - **Audio playground** for [gpt-4o-audio](https://ai.azure.com/explore/models/gpt-4o-transcribe/version/2025-03-20/registry/azure-openai/?cid=learnDocs), [gpt-4o-transcribe](https://ai.azure.com/explore/models/gpt-4o-transcribe/version/2025-03-20/registry/azure-openai/?cid=learnDocs), and [gpt-4o-mini-tts](https://ai.azure.com/explore/models/gpt-4o-mini-tts/version/2025-03-20/registry/azure-openai/?cid=learnDocs) models.
 - **Video playground** for Azure OpenAI Sora.
 
 :::image type="content" source="../media/concept-playgrounds/playground-landing-page.png" alt-text="Screenshot of the Azure AI Foundry playground landing page showcasing features for rapid prototyping and experimentation. The left pane of the portal has been customized to show the Playgrounds tab." lightbox="../media/concept-playgrounds/playground-landing-page.png":::
 
 > [!TIP]
-> In the screenshot of the playground landing page, the left pane of the portal has been customized to show the Playgrounds tab. To learn more about seeing the other items in the left pane, see [Customize the left pane](../what-is-azure-ai-foundry.md#left-pane).
+> In the screenshot of the playground landing page, the left pane of the portal is customized to show the Playgrounds tab. To learn more about seeing the other items in the left pane, see [Customize the left pane](../what-is-azure-ai-foundry.md#left-pane).
 
 ## Playgrounds as the prelude to production
 
-Modern development involves working across multiple systems—APIs, services, SDKs, and data models—often before you're ready to fully commit to a framework, write tests, or spin up infrastructure. As the complexity of software ecosystems increases, the need for safe, lightweight environments to validate ideas becomes critical. The playgrounds were built to meet this need.
+Modern development involves working across multiple systems—APIs, services, SDKs, and data models—often before you're ready to fully commit to a framework, write tests, or spin up infrastructure. As the complexity of software ecosystems increases, the need for safe, lightweight environments to validate ideas becomes critical. The playgrounds are built to meet this need.
 
-The Azure AI Foundry playgrounds provide ready-to-use environments with all the necessary tools and features pre-installed, eliminating the need to set up projects, manage dependencies, or solve compatibility issues. The playgrounds can *accelerate developer velocity* by validating API behavior, going quicker to code, reducing cost of experimentation and time to ship, accelerating integration, optimizing prompts, and more.
+The Azure AI Foundry playgrounds provide ready-to-use environments with all the necessary tools and features preinstalled, so you don't need to set up projects, manage dependencies, or solve compatibility issues. The playgrounds can *accelerate developer velocity* by validating API behavior, going quicker to code, reducing cost of experimentation and time to ship, accelerating integration, optimizing prompts, and more.
 
 Playgrounds also *provide clarity quickly* when you have questions, by providing answers in seconds—rather than hours—and allowing you to test and validate ideas before you commit to building at scale. For example, the playgrounds are ideal for quickly answering questions like:
 
@@ -50,60 +50,60 @@ Playgrounds also *provide clarity quickly* when you have questions, by providing
 
 ## Open in VS Code capability
 
-The **Chat playground** and **Agents playground** allow you to work in VS Code, by using the **Open in VS Code** button that's available through the Azure AI Foundry extension in VS Code. 
+The **Chat playground** and **Agents playground** let you work in VS Code by using the **Open in VS Code** button. You can find this button through the Azure AI Foundry extension in VS Code. 
 
-Available on the multi-lingual sample code samples, "Open in VS Code" enables the automatic import of your code sample, API endpoint, and key to a VS Code workspace in an `/azure` environment. This functionality makes it easy to work in the VS Code IDE from the Azure AI Foundry portal.
+Available on the multilingual sample code samples, **Open in VS Code** automatically imports your code sample, API endpoint, and key to a VS Code workspace in an `/azure` environment. This functionality makes it easy to work in the VS Code IDE from the Azure AI Foundry portal.
 
-Follow these steps to use the "Open in VS Code" functionality from the chat and agents playgrounds:
+To use the **Open in VS Code** functionality from the chat and agents playgrounds, follow these steps:
 
-1. Select **Try the Chat playground** to open it. Alternatively, you could follow these steps in the Agents playground by selecting **Let's go** on the Agents playground card.
+1. Select **Try the Chat playground** to open it. Alternatively, you can follow these steps in the Agents playground by selecting **Let's go** on the Agents playground card.
 1. If you don't have a deployment already, select **Create new deployment** and deploy a model such as `gpt-4o-mini`.
-1. Ensure that your deployment is selected in the Deployment box.
+1. Make sure your deployment is selected in the Deployment box.
 1. Select **View code** to see the code sample.
 1. Select **Open in VS Code** to open VS Code in a new tab of your browser window.
 
     :::image type="content" source="../media/concept-playgrounds/open-in-vs-code-foundry.png" alt-text="Screenshot showing the Open in VS Code button in Azure AI Foundry playground for seamless code integration." lightbox="../media/concept-playgrounds/open-in-vs-code-foundry.png":::
 
-1. You're redirected to the `/azure` environment of VS Code where your code sample, API endpoint and key are already imported from the Azure AI Foundry playground.
+1. You're redirected to the `/azure` environment of VS Code where your code sample, API endpoint, and key are already imported from the Azure AI Foundry playground.
 
     :::image type="content" source="../media/concept-playgrounds/open-in-vs-code-vscode.png" alt-text="Screenshot of the VS Code environment showing imported code sample, API endpoint, and key from the Azure AI Foundry playground." lightbox="../media/concept-playgrounds/open-in-vs-code-vscode.png":::
 
-1. Browse the `READ.ME` file for instructions to run your model.
-1. View your code sample in the `run_model.py`.
+1. Browse the `README.md` file for instructions to run your model.
+1. View your code sample in the `run_model.py` file.
 1. View relevant dependencies in the `requirements.txt` file.
 
 
 ## Agents playground
 
-The agents playground allows you to explore, prototype, and test agents without needing to run any code. From this page, you can quickly iterate and experiment with new ideas. To get started with the Agents playground, see the [Quickstart: Create a new agent](../../ai-services/agents/quickstart.md).
+The agents playground lets you explore, prototype, and test agents without running any code. From this page, you can quickly iterate and experiment with new ideas. To get started with the Agents playground, see the [Quickstart: Create a new agent](../../ai-services/agents/quickstart.md).
 
 :::image type="content" source="../media/concept-playgrounds/agents-playground.png" alt-text="Screenshot of the agents playground interface for exploring, prototyping, and testing agents without code." lightbox="../media/concept-playgrounds/agents-playground.png":::
 
 ## Chat playground
 
 The chat playground is the place to test the latest reasoning models from Azure OpenAI, DeepSeek, and Meta. To learn more about the chat playground, see the [Quickstart: Use the chat playground in Azure AI Foundry portal](../quickstarts/get-started-playground.md).
 
-For all reasoning models, the chat playground provides a chain-of-thought summary drop-down that lets you see how the model was thinking through its response ahead of sharing the output.
+For all reasoning models, the chat playground provides a chain-of-thought summary drop-down that lets you see how the model thinks through its response before sharing the output.
 
 :::image type="content" source="../media/concept-playgrounds/chat-playground-cot-summary.png" alt-text="Screenshot of the Chat playground interface for exploring, prototyping, and testing chat models without code." lightbox="../media/concept-playgrounds/chat-playground-cot-summary.png":::
 
 ## Audio playground
 
 The audio playground (preview) lets you use text-to-speech and transcription capabilities with the latest audio models from Azure OpenAI.
 
-Follow these steps to try the text to speech capability:
+To try the text-to-speech capability, follow these steps:
 
 1. Select **Try the Audio playground** to open it.
 1. If you don't have a deployment already, select **Create new deployment** and deploy a model such as `gpt-4o-mini-tts`.
-1. Ensure that your deployment is selected in the Deployment box.
+1. Make sure your deployment is selected in the Deployment box.
 1. Input a text prompt.
 1. Adjust model parameters such as voice and response format.
 1. Select **Generate** to receive a speech output with playback controls that include play, rewind, forward, adjust speed, and volume.
 1. Download the audio file to your local computer.
 
     :::image type="content" source="../media/concept-playgrounds/audio-playground-text-to-speech.png" alt-text="Screenshot of the Audio playground interface showcasing text-to-speech capabilities with playback controls." lightbox="../media/concept-playgrounds/audio-playground-text-to-speech.png":::
 
-Follow these steps to try the transcription capability:
+To try the transcription capability, follow these steps:
 
 1. If you don't have a deployment already, select **Create new deployment** and deploy a model such as `gpt-4o-transcribe`.
 1. (Optional) Include a phrase list as a text mechanism to guide your audio input.
@@ -115,9 +115,9 @@ Follow these steps to try the transcription capability:
 
 ## Video playground
 
-The video playground (preview) is your rapid iteration environment for exploring, refining, and validating generative video workflows—designed for developers who need to go from idea to prototype with precision, control, and speed. The playground gives you a low-friction interface to test prompt structures, assess motion fidelity, evaluate model consistency across frames, and compare outputs across models—without writing boilerplate or wasting compute cycles. It's also a great demo interface for your Chief Product Officer and Engineering VP.
+The video playground (preview) is your rapid iteration environment for exploring, refining, and validating generative video workflows. It's designed for developers who need to go from idea to prototype with precision, control, and speed. The playground gives you a low-friction interface to test prompt structures, assess motion fidelity, evaluate model consistency across frames, and compare outputs across models—without writing boilerplate or wasting compute cycles. It's also a great demo interface for your chief product officer and engineering VP.
 
-All model endpoints are integrated with **Azure AI Content Safety**. As a result, harmful and unsafe images are filtered out before being surfaced in the video playground. If your text prompt and video generation are flagged by content moderation policies, you get a warning notification.
+All model endpoints are integrated with **Azure AI Content Safety**. As a result, harmful and unsafe images are filtered out before they appear in the video playground. If content moderation policies flag your text prompt or video generation, you get a warning notification.
 
 You can use the video playground with the **Azure OpenAI Sora** model.
 
@@ -127,7 +127,7 @@ You can use the video playground with the **Azure OpenAI Sora** model.
 Follow these steps to use the video playground:
 
 > [!CAUTION]
-> Videos generated are retained for 24 hours due to data privacy. Download videos to your local computer for longer retention.
+> Videos you generate are retained for 24 hours due to data privacy. Download videos to your local computer for longer retention.
 
 1. Select **Try the Video playground** to open it.
 1. If you don't have a deployment already, select **Deploy now** from the top right side of the homepage and deploy the `sora` model.
@@ -155,33 +155,33 @@ Follow these steps to use the video playground:
 
 ### What to validate when experimenting in video playground
 
-When using the video playground as you plan your production workload, you can explore and validate the following attributes:
+When you use the video playground to plan your production workload, explore and validate the following attributes:
 
 - **Prompt-to-Motion Translation**
-    - Does the video model interpret my prompt in a way that makes logical and temporal sense?
+    - Does the video model interpret your prompt in a way that makes logical and temporal sense?
     - Is motion coherent with the described action or scene?
 - **Frame Consistency**
     - Do characters, objects, and styles remain consistent across frames?
     - Are there visual artifacts, jitter, or unnatural transitions?
 - **Scene Control**
-    - How well can I control scene composition, subject behavior, or camera angles?
-    - Can I guide scene transitions or background environments?
+    - How well can you control scene composition, subject behavior, or camera angles?
+    - Can you guide scene transitions or background environments?
 
 - **Length and Timing**
     - How do different prompt structures affect video length and pacing?
     - Does the video feel too fast, too slow, or too short?
 
 - **Multimodal Input Integration**
-    - What happens when I provide a reference image, pose data, or audio input?
-    - Can I generate video with lip-sync to a given voiceover?
+    - What happens when you provide a reference image, pose data, or audio input?
+    - Can you generate video with lip-sync to a given voiceover?
 
 - **Post-Processing Needs**
-    - What level of raw fidelity can I expect before I need editing tools?
-    - Do I need to upscale, stabilize, or retouch the video before using it in production?
+    - What level of raw fidelity can you expect before you need editing tools?
+    - Do you need to upscale, stabilize, or retouch the video before using it in production?
 
-- **Latency & Performance**
+- **Latency and Performance**
     - How long does it take to generate video for different prompt types or resolutions?
-    - What's the cost-performance tradeoff of generating 5s vs. 15s clips?
+    - What's the cost-performance tradeoff of generating 5-second versus 15-second clips?
 
 
 ## Images playground
@@ -209,7 +209,7 @@ Follow these steps to use the images playground:
 
 ### What to validate when experimenting in images playground
 
-By using the images playground, you can explore and validate the following as you plan your production workload:
+By using the images playground, you can explore and validate the following aspects as you plan your production workload:
 
 - **Prompt Effectiveness**
     - What kind of visual output does this prompt generate for my enterprise use case?
@@ -221,12 +221,12 @@ By using the images playground, you can explore and validate the following as yo
     - Can I iterate on variations of the same base prompt with minimal drift?
 
 - **Parameter Tuning**
-    - What's the effect of changing model parameters like guidance scale, seed, steps, etc.?
-    - How can I balance creativity vs. prompt fidelity?
+    - What's the effect of changing model parameters like guidance scale, seed, steps, and others?
+    - How can I balance creativity versus prompt fidelity?
 
 - **Model Comparison**
-    - How do results differ between models (for example, SDXL vs. DALL·E)?
-    - Which model performs better for realistic faces vs. artistic compositions?
+    - How do results differ between models, such as SDXL versus DALL·E?
+    - Which model performs better for realistic faces versus artistic compositions?
 
 - **Composition Control**
     - What happens when I use spatial constraints like bounding boxes or inpainting masks?
@@ -237,7 +237,7 @@ By using the images playground, you can explore and validate the following as yo
     - What's the best way to prompt for symmetry, specific camera angles, or emotions?
 
 - **Integration Readiness**
-    - Will this image meet the constraints of my product's UI (aspect ratio, resolution, content safety)?
+    - Will this image meet the constraints of my product's UI, including aspect ratio, resolution, and content safety?
     - Does the output conform to brand guidelines or customer expectations?