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b0613a8ceb
* 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
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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ProjectsAgentVersion agentVersion = await aiProjectClient.AgentAdministrationClient.CreateAgentVersionAsync(
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"AskContoso",
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new ProjectsAgentVersionCreationOptions(
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new DeclarativeAgentDefinition(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.AgentAdministrationClient.DeleteAgentAsync(agent.Name);
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