wehub-resource-sync
db620d33df
CodeQL / Analyze (csharp) (push) Waiting to run
CodeQL / Analyze (python) (push) Waiting to run
dotnet-build-and-test / dotnet-test-functions (push) Has been cancelled
dotnet-build-and-test / paths-filter (push) Has been cancelled
dotnet-build-and-test / dotnet-build (Debug, windows-latest, net9.0) (push) Has been cancelled
dotnet-build-and-test / dotnet-build (Release, ubuntu-latest, net10.0) (push) Has been cancelled
dotnet-build-and-test / dotnet-build (Release, ubuntu-latest, net8.0) (push) Has been cancelled
dotnet-build-and-test / dotnet-build (Release, windows-latest, net472) (push) Has been cancelled
dotnet-build-and-test / dotnet-test (Release, integration, true, ubuntu-latest, net10.0) (push) Has been cancelled
dotnet-build-and-test / dotnet-test (Release, integration, true, windows-latest, net472) (push) Has been cancelled
dotnet-build-and-test / dotnet-foundry-hosted-it (push) Has been cancelled
dotnet-build-and-test / dotnet-build-and-test-check (push) Has been cancelled
dotnet-build-and-test / Integration Test Report (push) Has been cancelled
72 lines
3.4 KiB
C#
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("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
|
|
var deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-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);
|