mirror of
https://github.com/microsoft/agent-framework.git
synced 2026-06-16 21:04:09 +08:00
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
72 lines
3.4 KiB
C#
72 lines
3.4 KiB
C#
// Copyright (c) Microsoft. All rights reserved.
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// This sample shows how to use the built in RAG capabilities that the Foundry service provides when using AI Agents provided by Foundry.
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using System.ClientModel;
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using Azure.AI.Projects;
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using Azure.AI.Projects.Agents;
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using Azure.Identity;
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using Microsoft.Agents.AI;
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using Microsoft.Agents.AI.Foundry;
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using OpenAI;
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using OpenAI.Files;
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using OpenAI.Responses;
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using OpenAI.VectorStores;
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var endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
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var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
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// Create an AI Project client and get an OpenAI client that works with the foundry service.
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// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
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// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
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// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
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AIProjectClient aiProjectClient = new(
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new Uri(endpoint),
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new DefaultAzureCredential());
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OpenAIClient openAIClient = aiProjectClient.GetProjectOpenAIClient();
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// Upload the file that contains the data to be used for RAG to the Foundry service.
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OpenAIFileClient fileClient = openAIClient.GetOpenAIFileClient();
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ClientResult<OpenAIFile> uploadResult = await fileClient.UploadFileAsync(
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filePath: "contoso-outdoors-knowledge-base.md",
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purpose: FileUploadPurpose.Assistants);
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// Create a vector store in the Foundry service using the uploaded file.
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VectorStoreClient vectorStoreClient = openAIClient.GetVectorStoreClient();
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ClientResult<VectorStore> vectorStoreCreate = await vectorStoreClient.CreateVectorStoreAsync(options: new VectorStoreCreationOptions()
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{
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Name = "contoso-outdoors-knowledge-base",
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FileIds = { uploadResult.Value.Id }
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});
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// Use the native OpenAI SDK FileSearchTool directly with the vector store ID.
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#pragma warning disable OPENAI001
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FileSearchTool fileSearchTool = new([vectorStoreCreate.Value.Id]);
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#pragma warning restore OPENAI001
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AgentVersion agentVersion = await aiProjectClient.Agents.CreateAgentVersionAsync(
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"AskContoso",
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new AgentVersionCreationOptions(
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new PromptAgentDefinition(model: deploymentName)
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{
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Instructions = "You are a helpful support specialist for Contoso Outdoors. Answer questions using the provided context and cite the source document when available.",
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Tools = { fileSearchTool }
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}));
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FoundryAgent agent = aiProjectClient.AsAIAgent(agentVersion);
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AgentSession session = await agent.CreateSessionAsync();
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Console.WriteLine(">> Asking about returns\n");
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Console.WriteLine(await agent.RunAsync("Hi! I need help understanding the return policy.", session));
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Console.WriteLine("\n>> Asking about shipping\n");
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Console.WriteLine(await agent.RunAsync("How long does standard shipping usually take?", session));
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Console.WriteLine("\n>> Asking about product care\n");
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Console.WriteLine(await agent.RunAsync("What is the best way to maintain the TrailRunner tent fabric?", session));
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// Cleanup
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await fileClient.DeleteFileAsync(uploadResult.Value.Id);
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await vectorStoreClient.DeleteVectorStoreAsync(vectorStoreCreate.Value.Id);
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await aiProjectClient.Agents.DeleteAgentAsync(agent.Name);
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