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Roger Barreto
628bb1af48
* Update Foundry Responses as ChatClientAgent * Migrate obsolete AzureAI integration tests to versioned agent pattern Replace obsolete CreateAIAgentAsync/GetAIAgentAsync calls with Agents.CreateAgentVersionAsync() + AsAIAgent(AgentVersion) in all AzureAI integration tests. - Rename AIProjectClient* test files to FoundryVersionedAgent* - Register AIFunction tools in PromptAgentDefinition.Tools for server-side visibility via AsOpenAIResponseTool() - Skip structured output tests (AzureAIProjectChatClient clears ResponseFormat for versioned agents) - Remove all [Obsolete] attributes and #pragma warning disable CS0618 * Merge FoundryMemory package into AzureAI under Memory/ folder Move all FoundryMemory source, unit tests, and integration tests into the Microsoft.Agents.AI.AzureAI package. Change namespace from Microsoft.Agents.AI.FoundryMemory to Microsoft.Agents.AI.AzureAI. - Add [Experimental] to FoundryMemoryProviderOptions and Scope - Rename internal AIProjectClientExtensions to MemoryStoreExtensions - Update AzureAI .csproj with Compliance.Abstractions, Redaction - Remove FoundryMemory from solution and release filter - Update sample to reference AzureAI instead of FoundryMemory - Delete old Microsoft.Agents.AI.FoundryMemory project and tests * Add EnsureMemoryStoreCreatedAsync and memory existence checks to integration tests - Ensure memory store is created before testing memory operations - Add AZURE_AI_EMBEDDING_DEPLOYMENT_NAME config setting - Assert memories exist in store via SearchMemoriesAsync before cleanup - Verify scope isolation with direct memory store queries * Fix and rename AzureAI unit tests for RAPI vs Versioned clarity - Rename AsAIAgentAsync_* to AsAIAgent_* (drop Async from method group) - Add _Rapi_ prefix to non-versioned (Responses API) tests - Add _Versioned_ prefix to versioned agent tests where needed - Fix RAPI tests: assert GetService<AIProjectClient>() is null - Fix Versioned tests: assert IsType<FoundryAgent> and GetService<AIProjectClient>() returns the client instance - Fix UserAgent header tests: proper HTTP handler routing - Fix ChatClient_UsesDefaultConversationIdAsync test setup - All 153 unit tests pass with 0 failures * Rename Microsoft.Agents.AI.AzureAI to Microsoft.Agents.AI.Foundry Rename the project, namespace, folder, and all references from Microsoft.Agents.AI.AzureAI to Microsoft.Agents.AI.Foundry. Also rename Workflows.Declarative.AzureAI to .Foundry. - Rename src, unit test, integration test, and workflow folders - Update namespaces in all source and test .cs files - Update ProjectReferences in ~47 sample and test .csproj files - Update solution files (.slnx, .slnf) - Update sample using statements - Update READMEs, SKILL.md, ADRs in docs/ - Disable package validation baseline for renamed packages - Fix UTF-8 BOM encoding on all affected .cs files - AzureAI.Persistent left completely unchanged * Fix format: remove ImplicitUsings, add explicit usings, fix BOM encoding - Remove ImplicitUsings=enable from Foundry csproj to resolve IDE0005 on shared ReplacingRedactor.cs - Add explicit System usings to all source files that relied on them - Sort usings alphabetically per editorconfig rules - Fix UTF-8 BOM on 12 sample Program.cs files - Rename Azure AI Foundry Agents to Microsoft Foundry Agents in docs
628bb1af48
·
2026-04-02 01:25:24 +00:00
History
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. |
| RAG with Neo4j GraphRAG | This sample demonstrates how to create and run an agent that uses a Neo4j-backed GraphRAG context provider with graph-enriched retrieval. |