Files
agent-framework/dotnet/samples/02-agents/Evaluation/Evaluation_SimpleEval/Program.cs
T
Ben Thomas c79f886dc3 .NET: Align Foundry sample environment variables and credentials. (#6422)
* dotnet: refresh Foundry sample guidance

Carry forward the still-relevant sample guidance and Foundry-specific documentation fixes from the old stacked sample migration work, adapted to the current repo layout and policy.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* dotnet: rename Foundry sample env vars

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* dotnet: remove persistent provider sample

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* dotnet: drop SAMPLE_GUIDELINES.md from this PR

Defer the guidelines doc and its cross-link to a follow-on PR to avoid broken-link failures in CI.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* dotnet: add DefaultAzureCredential warning to remaining samples

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* dotnet: address PR review feedback

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

---------

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-06-11 17:26:00 +00:00

56 lines
2.4 KiB
C#

// Copyright (c) Microsoft. All rights reserved.
// Simplest possible agent evaluation: create a Foundry agent, run it against
// test questions, and use Foundry quality evaluators to score the responses.
// For custom domain-specific checks, see the Evaluation_CustomEvals sample.
using Azure.AI.Projects;
using Azure.Identity;
using Microsoft.Agents.AI;
using Microsoft.Extensions.AI.Evaluation;
using FoundryEvals = Microsoft.Agents.AI.Foundry.FoundryEvals;
string endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
string deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-4o-mini";
// 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 projectClient = new(new Uri(endpoint), new DefaultAzureCredential());
AIAgent agent = projectClient.AsAIAgent(
model: deploymentName,
instructions: "You are a helpful assistant. Provide clear, accurate answers.",
name: "SimpleAgent");
// Configure Foundry quality evaluators — runs evaluations server-side via the Foundry Evals API.
FoundryEvals evaluator = new(projectClient, deploymentName, FoundryEvals.Relevance, FoundryEvals.Coherence);
// Run the agent against test queries and evaluate in one call.
string[] queries = ["What is photosynthesis?", "How do vaccines work?"];
AgentEvaluationResults results = await agent.EvaluateAsync(queries, evaluator);
// Print results.
Console.WriteLine($"Passed: {results.Passed}/{results.Total}");
if (results.ReportUrl is not null)
{
Console.WriteLine($"Report: {results.ReportUrl}");
}
Console.WriteLine();
for (int i = 0; i < results.Items.Count; i++)
{
Console.WriteLine($"Query: {queries[i]}");
Console.WriteLine($"Response: {(results.InputItems?[i].Response is { } resp ? resp.Substring(0, Math.Min(50, resp.Length)) : "N/A")}...");
foreach (var metric in results.Items[i].Metrics)
{
string score = metric.Value is NumericMetric nm && nm.Value.HasValue
? nm.Value.Value.ToString("F1")
: "N/A";
Console.WriteLine($" {metric.Key}: {score}");
}
Console.WriteLine();
}