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Update to architecture diagram and Foundry naming
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docs/lab-instructions.md

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@@ -31,7 +31,7 @@ You'll implement both patterns:
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This dual approach demonstrates how serverless functions can seamlessly integrate with modern AI workflows through standard protocols.
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!IMAGE[SnippyLab-Terminal.png](https://raw.githubusercontent.com/Azure-Samples/snippy/main/images/Snippy-Architecture.png)
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!IMAGE[SnippyLab-Terminal.png](https://raw.githubusercontent.com/Azure-Samples/snippy/main/images/Snippy-Architecture-V2.png)
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Your lab environment comes pre-configured with the necessary software:
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- **Visual Studio Code** - Your primary development environment
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- **Edge** - Browser with tabs for GitHub, Azure Portal, and Azure AI Foundry
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- **Edge** - Browser with tabs for GitHub, Azure Portal, and Microsoft Foundry
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- Python 3.12
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- **uv** package manager (faster alternative to pip)
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- Git for source control
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From your lab environment's Desktop (or Taskbar), open **Edge - Snippy & Portal** shortcut, which opens three tabs you'll need:
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1. [] **Snippy Lab GitHub Repo:** Source code (*https://aka.ms/functions-mcp-lab*).
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2. [] **Azure Portal:** (*https://portal.azure.com*).
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3. [] **Azure AI Foundry:** (*https://ai.azure.com*).
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3. [] **Microsoft Foundry:** (*https://ai.azure.com*).
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> [!note]
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> When you open the Azure Portal and Azure Foundry tabs, you may see login pages. Don't worry about signing in yet - you'll receive the Azure credentials in **Step 4** when you begin the resource provisioning process. For now, you can leave these tabs open in the background.
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> When you open the Azure Portal and Microsoft Foundry tabs, you may see login pages. Don't worry about signing in yet - you'll receive the Azure credentials in **Step 4** when you begin the resource provisioning process. For now, you can leave these tabs open in the background.
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> * Azure Storage Account (for Functions operations and state)
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> * Azure Cosmos DB for NoSQL (pre-configured for vector search)
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> * Azure AI Services (with *gpt-4o-mini* and *text-embedding-3-small* models deployed)
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> * Azure AI Foundry resources (Foundry projects)
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> * Microsoft Foundry resources (Foundry projects)
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> * Azure Log Analytics & Application Insights (for monitoring)
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> * Durable Task Scheduler (for workflow orchestration)
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> * Managed Identity (for secure access to Azure resources)

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