Added video and consolidated agents

GraemeMalcolm · GraemeMalcolm · commit 733e9b5a0cb2 · 2026-02-05T13:52:21.000-08:00
diff --git a/.openpublishing.redirection.json b/.openpublishing.redirection.json
@@ -64587,6 +64587,11 @@
       "source_path": "learn-pr/azure/identify-threats-with-azure-security-center/index.yml",
       "redirect_url": "https://learn.microsoft.com/azure/defender-for-cloud/defender-for-cloud-introduction",
       "redirect_document_id": false
+    },
+    { 
+      "source_path": "learn-pr/wwl-data-ai/get-started-with-generative-ai-and-agents/5-using-an-agent.yml",
+      "redirect_url": "https://learn.microsoft.com/training/modules/get-started-with-generative-ai-and-agents/4-creating-an-agent",
+      "redirect_document_id": false
     }
   ]
 }
diff --git a/learn-pr/wwl-data-ai/get-started-with-generative-ai-and-agents/1-introduction.yml b/learn-pr/wwl-data-ai/get-started-with-generative-ai-and-agents/1-introduction.yml
@@ -4,10 +4,11 @@ title: Introduction
 metadata:
   title: Introduction
   description: "Learn about generative AI agents, their capabilities, and how to use them effectively in various applications."
-  ms.date: 1/28/2026
+  ms.date: 2/5/2026
   author: sherzyang
   ms.author: sheryang
   ms.topic: unit
+  zone_pivot_groups: video-or-text
 durationInMinutes: 2
 content: |
   [!include[](includes/1-introduction.md)]
diff --git a/learn-pr/wwl-data-ai/get-started-with-generative-ai-and-agents/2-generative-ai-models.yml b/learn-pr/wwl-data-ai/get-started-with-generative-ai-and-agents/2-generative-ai-models.yml
@@ -4,10 +4,11 @@ title: Generative AI models
 metadata:
   title: Generative AI models
   description: "Learn about generative AI models, their capabilities, and how to use them effectively in various applications."
-  ms.date: 1/28/2026
+  ms.date: 2/5/2026
   author: sherzyang
   ms.author: sheryang
   ms.topic: unit
+  zone_pivot_groups: video-or-text
 durationInMinutes: 6
 content: |
   [!include[](includes/2-generative-ai-models.md)]
diff --git a/learn-pr/wwl-data-ai/get-started-with-generative-ai-and-agents/3-using-generative-ai-models.yml b/learn-pr/wwl-data-ai/get-started-with-generative-ai-and-agents/3-using-generative-ai-models.yml
@@ -4,10 +4,11 @@ title: Using a generative AI model
 metadata:
   title: Using a generative AI model
   description: "Learn how to use a generative AI model, including examples to understand its capabilities and applications."
-  ms.date: 1/28/2026
+  ms.date: 2/5/2026
   author: sherzyang
   ms.author: sheryang
   ms.topic: unit
+  zone_pivot_groups: video-or-text
 durationInMinutes: 4
 content: |
   [!include[](includes/3-using-generative-ai-models.md)]
diff --git a/learn-pr/wwl-data-ai/get-started-with-generative-ai-and-agents/4-creating-an-agent.yml b/learn-pr/wwl-data-ai/get-started-with-generative-ai-and-agents/4-creating-an-agent.yml
@@ -4,10 +4,11 @@ title: Creating an agent
 metadata:
   title: Creating an agent
   description: "Learn how to create a generative AI agent, including examples to understand its capabilities and applications."
-  ms.date: 1/28/2026
+  ms.date: 2/5/2026
   author: sherzyang
   ms.author: sheryang
   ms.topic: unit
+  zone_pivot_groups: video-or-text
 durationInMinutes: 4
 content: |
   [!include[](includes/4-creating-an-agent.md)]
diff --git a/learn-pr/wwl-data-ai/get-started-with-generative-ai-and-agents/5-using-an-agent.yml b/learn-pr/wwl-data-ai/get-started-with-generative-ai-and-agents/5-using-an-agent.yml
diff --git a/learn-pr/wwl-data-ai/get-started-with-generative-ai-and-agents/8-summary.yml b/learn-pr/wwl-data-ai/get-started-with-generative-ai-and-agents/8-summary.yml
@@ -4,10 +4,11 @@ title: Summary
 metadata:
   title: Summary
   description: "A summary of how to get started with generative AI and agents in Foundry."
-  ms.date: 1/28/2026
+  ms.date: 2/5/2026
   author: sherzyang
   ms.author: sheryang
   ms.topic: unit
+  zone_pivot_groups: video-or-text
 durationInMinutes: 2
 content: |
   [!include[](includes/8-summary.md)]
diff --git a/learn-pr/wwl-data-ai/get-started-with-generative-ai-and-agents/includes/1-introduction.md b/learn-pr/wwl-data-ai/get-started-with-generative-ai-and-agents/includes/1-introduction.md
@@ -1,3 +1,11 @@
+::: zone pivot="video"
+
+>[!VIDEO https://learn-video.azurefd.net/vod/player?id=012dac2a-c837-4d9d-b2cc-215382dd1957]
+
+::: zone-end
+
+::: zone pivot="text"
+
 In a short few years, generative AI, a subset of artificial intelligence that focuses on creating new content, has changed the way we work and revolutionized what is possible with technology. At times, the fast-moving developments in generative AI can feel challenging to keep track of even for seasoned developers.
 
 In this module, gain a framework for understanding generative AI applications and how Microsoft Foundry supports innovation. What does today's innovation look like? Consider these use cases:
@@ -12,4 +20,9 @@ In this module, gain a framework for understanding generative AI applications an
 
 - **Personalized Learning and Tutoring**: Educational platforms use generative AI to create custom quizzes, explanations, and study guides tailored to a student’s learning style and progress.
 
-Microsoft offers an ecosystem of tools for AI use and development. This module explores the Foundry model catalog and how to discover, evaluate, and deploy an appropriate model. Learn how to test and configure the deployed model the Foundry playground, and call it from code using the OpenAI‑compatible Responses API. Finally, you’ll see how agents encapsulate a model, its instructions, and optional tools so your solution is reusable and consistent across Playground and code via the Project API.
+Microsoft offers an ecosystem of tools for AI use and development. This module explores the Foundry model catalog and how to discover, evaluate, and deploy an appropriate model. Learn how to test and configure the deployed model the Foundry playground, and call it from code using the OpenAI‑compatible Responses API. Finally, you’ll see how agents encapsulate a model, its instructions, and optional tools so your solution is reusable and consistent across Playground and code via the Project API.
+
+::: zone-end
+
+> [!NOTE]
+> We recognize that different people like to learn in different ways. You can choose to complete this module in video-based format or you can read the content as text and images. The text contains greater detail than the videos, so in some cases you might want to refer to it as supplemental material to the video presentation.
diff --git a/learn-pr/wwl-data-ai/get-started-with-generative-ai-and-agents/includes/2-generative-ai-models.md b/learn-pr/wwl-data-ai/get-started-with-generative-ai-and-agents/includes/2-generative-ai-models.md
@@ -1,3 +1,14 @@
+::: zone pivot="video"
+
+>[!VIDEO https://learn-video.azurefd.net/vod/player?id=7c40837e-776e-4097-89b0-fd224f1c6005]
+
+> [!NOTE]
+> See the **Text and images** tab for more details!
+
+::: zone-end
+
+::: zone pivot="text"
+
 Generative AI and agentic solutions are based on language models. Large language models (LLMs) form the foundation of  generative AI solutions that can provide a wide variety of responses. Today, a broad range of models exist that serve different needs. For example, the AI capabilities in a lightweight phone application may run best on a small language model, while a government application may require a domain-specialized model. 
 
 **Microsoft Foundry** provides an integrated environment for discovering, evaluating, deploying, and operating generative AI models. It brings together a rich model catalog, flexible deployment options, and built‑in governance capabilities so teams can build copilots, agents, and AI-powered applications with enterprise confidence.
@@ -108,4 +119,6 @@ When you deploy a model in Foundry, several things occur:
 - Configuration (such as model version, response style, safety settings) is locked in
 - Monitoring and logging become active: usage metrics, performance, latency, errors, and costs are tracked
 
-Next, learn how to configure these models in the Foundry portal playground and use them in a client application.
+Next, learn how to configure these models in the Foundry portal playground and use them in a client application.
+
+::: zone-end
diff --git a/learn-pr/wwl-data-ai/get-started-with-generative-ai-and-agents/includes/3-using-generative-ai-models.md b/learn-pr/wwl-data-ai/get-started-with-generative-ai-and-agents/includes/3-using-generative-ai-models.md
@@ -1,3 +1,14 @@
+::: zone pivot="video"
+
+>[!VIDEO https://learn-video.azurefd.net/vod/player?id=3dcbc522-beb9-4890-9e75-d8086bba1c2e]
+
+> [!NOTE]
+> See the **Text and images** tab for more details!
+
+::: zone-end
+
+::: zone pivot="text"
+
 The easiest way to interact with a deployed model is to use the model playground in the Foundry portal. You can use the **Foundry Playgrounds** to try prompts, compare models, and capture working settings before you write any code.
 
 ![Screenshot of the Foundry playgrounds.](../media/model-playground-example.png)
@@ -71,4 +82,6 @@ When you use a generative AI model on its own:
 - You’re experimenting in the Playground
 - You call the model via the **OpenAI Responses API**
 
-Next, learn how to create an agent in Foundry.
+Next, learn how to create an agent in Foundry.
+
+::: zone-end
diff --git a/learn-pr/wwl-data-ai/get-started-with-generative-ai-and-agents/includes/4-creating-an-agent.md b/learn-pr/wwl-data-ai/get-started-with-generative-ai-and-agents/includes/4-creating-an-agent.md
@@ -1,3 +1,14 @@
+::: zone pivot="video"
+
+>[!VIDEO https://learn-video.azurefd.net/vod/player?id=5f4b8cbc-cba8-4394-9130-e167af01d0e3]
+
+> [!NOTE]
+> See the **Text and images** tab for more details!
+
+::: zone-end
+
+::: zone pivot="text"
+
 **Agents** are *applications* built with generative AI models. Agentic AI moves beyond one‑off prompts and instead defines a consistent, workflow-like behavior that can be reused across apps, experiences, and services. 
 
 An agent in Microsoft Foundry is a packaged, reusable AI component that brings together three things:
@@ -65,5 +76,63 @@ In the Foundry portal, you can save your model, instructions, and tools as an ag
 
 ![Screenshot of the Foundry portal with the agent saved and open in the playground.](../media/continue-testing-agent.png)
 
-Next, learn how to publish an agent and use it in a client application.
+## Using an agent
+
+You can use an agent from a client application by using the **Foundry Projects SDK** to connect to the project and call it from a client using the **Project API**.
+
+The Project API enables you to:
+- Integrate agents into web apps, bots, or backend workflows
+- Orchestrate multi‑step tasks
+- Pass structured inputs or tool calls
+- Run agents at scale with your Foundry deployments
+
+### Create a client application for an agent
+
+To call the agent programmatically using Foundry’s Project API, you need the `agent-id` of your agent. You can find the `agent-id` in the Playground view of the agent when you select the *code* view and open the *.env variables*.  
+
+![Screenshot of the agent id that can be found with the environment variables.](../media/agent-id.png) 
+
+Let's take a look at a Python code sample to use an agent: 
+
+```python
+# Before running the sample, install the packages:
+#    pip install --pre azure-ai-projects>=2.0.0b1
+#    pip install azure-identity
+
+from azure.identity import DefaultAzureCredential
+from azure.ai.projects import AIProjectClient
+
+myEndpoint = "https://<resource>.services.ai.azure.com/api/projects/<resource-name>"
+
+project_client = AIProjectClient(
+    endpoint=myEndpoint,
+    credential=DefaultAzureCredential(),
+)
+
+myAgent = "learning-agent"
+# Get an existing agent
+agent = project_client.agents.get(agent_name=myAgent)
+print(f"Retrieved agent: {agent.name}")
+
+openai_client = project_client.get_openai_client()
+
+# Reference the agent to get a response
+response = openai_client.responses.create(
+    input=[{"role": "user", "content": "Tell me what you can help with."}],
+    extra_body={"agent": {"name": agent.name, "type": "agent_reference"}},
+)
+
+print(f"Response output: {response.output_text}")
+
+```
+
+### Publishing an agent
+
+**Publishing** an agent changes it from a saved development asset to a managed Azure resource with a stable endpoint. A published agent can be shared without exposing the Foundry project or source code. You can publish an agent through the Foundry portal. 
+
+![Screenshot of publishing agent in the Foundry portal.](../media/publish-agent.png)
+![Screenshot of agent after it is published in the Foundry portal with the endpoint information.](../media/agent-published.png)
+
+Publishing an agent gives you a stable endpoint to integrate the agent into applications. 
 
+::: zone-end
diff --git a/learn-pr/wwl-data-ai/get-started-with-generative-ai-and-agents/includes/5-using-an-agent.md b/learn-pr/wwl-data-ai/get-started-with-generative-ai-and-agents/includes/5-using-an-agent.md
diff --git a/learn-pr/wwl-data-ai/get-started-with-generative-ai-and-agents/includes/8-summary.md b/learn-pr/wwl-data-ai/get-started-with-generative-ai-and-agents/includes/8-summary.md
@@ -1,7 +1,25 @@
+::: zone pivot="video"
+
+>[!VIDEO https://learn-video.azurefd.net/vod/player?id=6bddab82-350b-4420-a1f3-741b9741c7b1]
+
+> [!NOTE]
+> See the **Text and images** tab for more details!
+
+::: zone-end
+
+::: zone pivot="text"
+
 In this module, you explored how Microsoft Foundry supports the full lifecycle of building generative AI and agentic solutions. You learned how language models serve as the foundation for AI applications, and how Foundry provides the tools and governance needed to use these models effectively and responsibly.
 
 You began by examining the Foundry model catalog, a centralized environment for discovering and comparing foundation models from Microsoft, partners, and open-source communities. You then learned how to deploy models to make them available as stable, scalable API endpoints. 
 
 The module also introduced lightweight client applications, which offer a simple way to connect to deployed models using the Foundry SDK. You learned how a minimal Python script can authenticate to a Foundry project, send prompts to a model, and retrieve responses.
 
-You then moved beyond raw models and learned how to build agents in Foundry. Agents package a model together with instructions, tools, and optional knowledge sources to produce workflow-oriented, repeatable behavior. The module showed how to configure and test agents in the playground, then publish them as Azure resources with stable endpoints. You now have the foundation needed to begin building scalable, secure AI applications powered by modern generative and agentic technologies.
+You then moved beyond raw models and learned how to build agents in Foundry. Agents package a model together with instructions, tools, and optional knowledge sources to produce workflow-oriented, repeatable behavior. The module showed how to configure and test agents in the playground, then publish them as Azure resources with stable endpoints. You now have the foundation needed to begin building scalable, secure AI applications powered by modern generative and agentic technologies.
+
+::: zone-end
+
+> [!TIP]
+> For more information about generative AI models in Microsoft Foundry, see [https://azure.microsoft.com/products/ai-foundry/models/](https://azure.microsoft.com/products/ai-foundry/models/).
+>
+> For more information about creating agents with Microsoft Foundry, see [https://azure.microsoft.com/products/ai-foundry/agent-service/](https://azure.microsoft.com/products/ai-foundry/agent-service/)
diff --git a/learn-pr/wwl-data-ai/get-started-with-generative-ai-and-agents/index.yml b/learn-pr/wwl-data-ai/get-started-with-generative-ai-and-agents/index.yml
@@ -39,7 +39,6 @@ units:
 - learn.wwl.get-started-with-generative-ai-and-agents.generative-ai-models
 - learn.wwl.get-started-with-generative-ai-and-agents.using-generative-ai-models
 - learn.wwl.get-started-with-generative-ai-and-agents.creating-an-agent
-- learn.wwl.get-started-with-generative-ai-and-agents.using-an-agent
 - learn.wwl.get-started-with-generative-ai-and-agents.exercise
 - learn.wwl.get-started-with-generative-ai-and-agents.knowledge-check
 - learn.wwl.get-started-with-generative-ai-and-agents.summary

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`64589`	`64589`	`"redirect_document_id": false`
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