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// Copyright (c) Microsoft. All rights reserved.
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// This sample demonstrates writing custom evaluation functions for domain-specific
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// checks. Custom evaluators run locally — no cloud evaluator service needed.
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// For LLM-based quality scoring (relevance, coherence), see Evaluation_SimpleEval.
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using Azure.AI.Projects;
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using Azure.Identity;
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using Microsoft.Agents.AI;
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string endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
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string deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-4o-mini";
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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 projectClient = new(new Uri(endpoint), new DefaultAzureCredential());
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AIAgent agent = projectClient.AsAIAgent(
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model: deploymentName,
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instructions: "You are a customer support agent. Help users resolve their issues "
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+ "politely and provide clear, actionable steps.",
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name: "SupportAgent");
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// Custom check: the agent should not refuse to help.
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EvalCheck noRefusal = FunctionEvaluator.Create("no_refusal", (string response) =>
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!response.Contains("I can't help", StringComparison.OrdinalIgnoreCase)
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&& !response.Contains("I'm unable to", StringComparison.OrdinalIgnoreCase)
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&& !response.Contains("outside my scope", StringComparison.OrdinalIgnoreCase));
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// Custom check: response should include actionable guidance (numbered steps or bullet points).
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EvalCheck hasActionableSteps = FunctionEvaluator.Create("has_actionable_steps", (string response) =>
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response.Contains("1.", StringComparison.Ordinal)
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|| response.Contains("- ", StringComparison.Ordinal)
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|| response.Contains("• ", StringComparison.Ordinal));
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// Custom check: response should be substantial but not excessively long.
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EvalCheck reasonableLength = FunctionEvaluator.Create("reasonable_length", (string response) =>
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response.Length >= 50 && response.Length <= 2000);
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// Combine all custom checks into a local evaluator.
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LocalEvaluator evaluator = new(noRefusal, hasActionableSteps, reasonableLength);
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string[] queries =
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[
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"My order hasn't arrived after two weeks. What should I do?",
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"I was charged twice for the same item. Can you help?",
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"How do I return a damaged product?",
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];
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AgentEvaluationResults results = await agent.EvaluateAsync(queries, evaluator);
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Console.WriteLine($"Passed: {results.Passed}/{results.Total}");
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Console.WriteLine();
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for (int i = 0; i < results.Items.Count; i++)
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{
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Console.WriteLine($"Query: {queries[i]}");
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Console.WriteLine($"Response: {(results.InputItems?[i].Response is { } resp ? resp.Substring(0, Math.Min(50, resp.Length)) : "N/A")}...");
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foreach (var metric in results.Items[i].Metrics)
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{
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string status = metric.Value.Interpretation?.Failed == true ? "FAIL" : "PASS";
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Console.WriteLine($" [{status}] {metric.Key}");
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}
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Console.WriteLine();
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}
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