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‎articles/ai-foundry/agents/how-to/tools/logic-apps.md

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@@ -21,7 +21,7 @@ This article demonstrates how to integrate Logic Apps with Azure AI Agents to ex
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## Prerequisites
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1. Create a Logic App within the same resource group as your Azure AI Project in the Azure portal.
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1. Configure your Logic App to send emails by including an HTTP request trigger that accepts JSON with `to`, `subject`, and `body`. See the [Logic App Workflow guide](/azure/ai-services/agents/ai-services/openai/how-to/assistants-logic-apps) for more information.
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1. Configure your Logic App to send emails by including an HTTP request trigger that accepts JSON with `to`, `subject`, and `body`. See the [Logic App Workflow guide](../../../../ai-services/openai/how-to/assistants-logic-apps.md) for more information.
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1. Set the following environment variables:
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- `PROJECT_ENDPOINT`: The Azure AI Agents endpoint.
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- `MODEL_DEPLOYMENT_NAME`: The deployment name of the AI model.

‎articles/ai-foundry/agents/how-to/triggers.md

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1. Depending on your use-case, choose the actions you need.
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If you want to create a new [thread](../concepts/threads-runs-messages/md#threads) for each new event of your trigger, add the following in sequence:
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If you want to create a new [thread](../concepts/threads-runs-messages.md#threads) for each new event of your trigger, add the following in sequence:
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1. Create thread
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1. Create run
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1. Get run

‎articles/ai-foundry/agents/overview.md

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| **1. Visibility into conversations** | Full access to structured [threads](./concepts/threads-runs-messages.md#threads), including both user↔agent and agent↔agent messages. Ideal for UIs, debugging, and training |
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| **2. Multi-agent coordination** | Built-in support for agent-to-agent messaging. |
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| **3. Tool orchestration** | Server-side execution and retry of [tool calls](how-to\tools\overview.md) with structured logging. No manual orchestration required. |
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| **4. Trust and safety** | Integrated [content filters](/azure/ai-services/agents/ai-services/openai/how-to/content-filters) help prevent misuse and mitigate prompt injection risks (XPIA). all outputs are policy-governed. |
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| **4. Trust and safety** | Integrated [content filters](../../ai-services/openai/how-to/content-filters.md) help prevent misuse and mitigate prompt injection risks (XPIA). all outputs are policy-governed. |
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| **5. Enterprise integration** | Bring your own [storage](./how-to/use-your-own-resources.md#use-an-existing-azure-cosmos-db-for-nosql-account-for-thread-storage), [Azure AI Search index](./how-to/use-your-own-resources.md#use-an-existing-azure-ai-search-resource), and [virtual network](how-to\virtual-networks.md) to meet compliance needs. |
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| **6. Observability and debugging** | Threads, tool invocations, and message traces are [fully traceable](concepts\tracing.md); [Application Insights integration](./how-to/metrics.md) for telemetry |
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| **7. Identity and policy control** | Built on Microsoft Entra with full support for RBAC, audit logs, and enterprise conditional access. |

‎articles/ai-services/.openpublishing.redirection.ai-services.json

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‎articles/ai-services/agents/media/monitoring/dashboard.png

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