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Chris 904a5b843e Python / .NET Samples - Restructure and Improve Samples (Feature Branc… (#4092)
* Python: .NET Samples - Restructure and Improve Samples (Feature Branch) (#4091)

* Moved by agent (#4094)

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* .NET Samples - Create `04-hosting` learning path step (#4098)

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Removed A2A section from the Getting Started README.

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* .NET Samples - Create `03-workflows` learning path step (#4102)

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* Python: Fix broken markdown links to repo resources (outside /docs) (#4105)

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* .NET Samples - Create `02-agents` learning path step (#4107)

* .NET: Fix broken relative link in GroupChatToolApproval README (#4108)

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* Update labeler configuration for workflow samples

* .NET - Reorder Agents samples to start from Step01 instead of Step04 (#4110)

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* .NET Samples - Configuration Naming Update (#4149)

* .NET: Restore AzureFunctions index parity with ConsoleApps under DurableAgents samples (#4221)

* Clean-up `05_host_your_agent`

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* AGENTS.md

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2026-02-26 00:56:10 +00:00

1.1 KiB

Agent Framework Retrieval Augmented Generation (RAG)

These samples show how to create an agent with the Agent Framework that uses Retrieval Augmented Generation (RAG) to enhance its responses with information from a knowledge base.

Sample Description
Basic Text RAG This sample demonstrates how to create and run a basic agent with simple text Retrieval Augmented Generation (RAG).
RAG with Vector Store and custom schema This sample demonstrates how to create and run an agent that uses Retrieval Augmented Generation (RAG) with a vector store. It also uses a custom schema for the documents stored in the vector store.
RAG with custom RAG data source This sample demonstrates how to create and run an agent that uses Retrieval Augmented Generation (RAG) with a custom RAG data source.
RAG with Foundry VectorStore service This sample demonstrates how to create and run an agent that uses Retrieval Augmented Generation (RAG) with the Foundry VectorStore service.