Files
agent-framework/dotnet/samples/02-agents/AgentWithRAG/AgentWithRAG_Step04_FoundryServiceRAG/Program.cs
T
Roger Barreto b0613a8ceb .NET: Bump Azure.AI.Projects to 2.0.0 GA (#5060)
* Bump Azure.AI.Projects to 2.0.0 GA

- Update Azure.AI.Projects from 2.0.0-beta.2 to 2.0.0 in CPM
- Update Azure.Identity from 1.19.0 to 1.20.0 (transitive dep)
- Update System.ClientModel from 1.9.0 to 1.10.0 (transitive dep)
- Rename types per Azure.AI.Projects.Agents 2.0.0 breaking changes:
  - AgentVersion -> ProjectsAgentVersion
  - AgentRecord -> ProjectsAgentRecord
  - AgentDefinition -> ProjectsAgentDefinition
  - AgentVersionCreationOptions -> ProjectsAgentVersionCreationOptions
  - PromptAgentDefinition -> DeclarativeAgentDefinition
  - AgentTool -> ProjectsAgentTool
  - AgentsClient -> AgentAdministrationClient
  - .Agents property -> .AgentAdministrationClient
- Add using Azure.AI.Projects.Memory namespace (types moved)
- Update AGENTS.md with BOM and output capture conventions

* Address PR review feedback

- Rename AIProjectClient parameter to aiProjectClient in AsChatClientAgent overloads
- Fix XML doc: ProjectsAgentTool namespace from Azure.AI.Projects.OpenAI to Azure.AI.Projects.Agents
- Rename test method to reflect DeclarativeAgentDefinition terminology
2026-04-02 14:02:29 +00:00

72 lines
3.4 KiB
C#

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