vizra-adk-evaluation-framework

name	Vizra ADK Evaluation Framework
description	Test and evaluate AI agents with automated evaluations, assertions, and LLM-as-a-Judge patterns

Vizra ADK Evaluation Framework

The evaluation framework enables automated testing of AI agents at scale, including LLM-as-a-Judge evaluation patterns.

Core Concepts

Component	Purpose
Evaluation	Test suite containing test cases for an agent
Test Case	Input/expected output pair for testing
Assertion	Validation rule for agent responses
Judge	LLM-based evaluation of response quality

Creating Evaluations

Basic Evaluation

<?php

namespace App\Evaluations;

use Vizra\VizraADK\Evaluations\BaseEvaluation;

class CustomerServiceEvaluation extends BaseEvaluation
{
    /**
     * The agent being evaluated
     */
    protected string $agent = 'customer_service';

    /**
     * Evaluation description
     */
    protected string $description = 'Evaluates customer service agent responses';

    /**
     * Define test cases
     */
    public function testCases(): array
    {
        return [
            [
                'name' => 'greeting_response',
                'input' => 'Hello, I need help with my order',
                'assertions' => [
                    'contains_greeting',
                    'offers_assistance',
                    'professional_tone',
                ],
            ],
            [
                'name' => 'refund_request',
                'input' => 'I want a refund for order #12345',
                'context' => [
                    'order_id' => '12345',
                    'order_status' => 'delivered',
                ],
                'assertions' => [
                    'acknowledges_request',
                    'asks_for_reason',
                    'explains_policy',
                ],
            ],
            [
                'name' => 'complaint_handling',
                'input' => 'This is terrible service! I\'ve been waiting for weeks!',
                'assertions' => [
                    'empathetic_response',
                    'apologizes',
                    'offers_solution',
                    'no_defensive_language',
                ],
            ],
        ];
    }
}

With Expected Outputs

public function testCases(): array
{
    return [
        [
            'name' => 'specific_answer',
            'input' => 'What are your business hours?',
            'expected' => 'Monday to Friday, 9 AM to 5 PM',
            'assertions' => [
                'exact_match', // or 'contains', 'semantic_match'
            ],
        ],
    ];
}

Creating Assertions

Basic Assertion

<?php

namespace App\Evaluations\Assertions;

use Vizra\VizraADK\Evaluations\BaseAssertion;

class ContainsGreetingAssertion extends BaseAssertion
{
    /**
     * Assertion description
     */
    protected string $description = 'Response should contain a greeting';

    /**
     * Evaluate the assertion
     */
    public function evaluate(string $response, array $context = []): bool
    {
        $greetings = ['hello', 'hi', 'good morning', 'good afternoon', 'welcome'];

        $lowercaseResponse = strtolower($response);

        foreach ($greetings as $greeting) {
            if (str_contains($lowercaseResponse, $greeting)) {
                return true;
            }
        }

        return ;
    }

    
     {
         ;
    }
}

Parameterized Assertion

class ContainsKeywordAssertion extends BaseAssertion
{
    protected string $description = 'Response should contain specific keyword';

    public function __construct(
        protected string $keyword,
        protected bool $caseSensitive = false
    ) {}

    public function evaluate(string $response, array $context = []): bool
    {
        if ($this->caseSensitive) {
            return str_contains($response, $this->keyword);
        }

        return str_contains(
            strtolower($response),
            strtolower($this->keyword)
        );
    }

    public function failureMessage(): string
    {
        return "Response did not contain keyword: {$this->keyword}";
    }
}


 => [
     (),
     (),
],

JSON Schema Assertion

use Vizra\VizraADK\Evaluations\Assertions\JsonSchemaAssertion;

'assertions' => [
    new JsonSchemaAssertion([
        'type' => 'object',
        'required' => ['status', 'message'],
        'properties' => [
            'status' => ['type' => 'string', 'enum' => ['success', 'error']],
            'message' => ['type' => 'string'],
            'data' => ['type' => 'object'],
        ],
    ]),
],

LLM-as-a-Judge

Use an LLM to evaluate response quality:

Basic Judge

use Vizra\VizraADK\Evaluations\Assertions\LlmJudgeAssertion;

'assertions' => [
    new LlmJudgeAssertion(
        criteria: 'The response should be helpful, accurate, and professional',
        model: 'gpt-4o'
    ),
],

Detailed Rubric

new LlmJudgeAssertion(
    criteria: <<<'CRITERIA'
        Evaluate the customer service response on these dimensions:

        1. Empathy (0-3): Does the response acknowledge the customer's feelings?
        2. Helpfulness (0-3): Does it provide actionable assistance?
        3. Accuracy (0-3): Is the information correct?
        4. Professionalism (0-3): Is the tone appropriate?

        Total score should be at least 9/12 to pass.
        CRITERIA,
    model: 'gpt-4o',
    threshold: 0.75
),

Comparative Judge

new LlmComparativeAssertion(
    referenceResponse: $idealResponse,
    criteria: 'Response should be as helpful as or better than the reference',
    model: 'gpt-4o'
),

Running Evaluations

CLI Commands

# Run all evaluations
php artisan vizra:eval:run

# Run specific evaluation
php artisan vizra:eval:run --evaluation=CustomerServiceEvaluation

# Run with verbose output
php artisan vizra:eval:run --verbose

# Run specific test case
php artisan vizra:eval:run --evaluation=CustomerServiceEvaluation --case=greeting_response

# Output results as JSON
php artisan vizra:eval:run --format=json

# Save results to file
php artisan vizra:eval:run --output=results.json

Programmatic Execution

use Vizra\VizraADK\Services\EvaluationRunner;

$runner = app(EvaluationRunner::class);

// Run evaluation
$results = $runner->run(CustomerServiceEvaluation::class);

// Check results
foreach ($results->testCases as $testCase) {
    echo "{$testCase->name}: " . ($testCase->passed ? 'PASSED' : 'FAILED') . "\n";

    foreach ($testCase->assertions as $assertion) {
        if (!$assertion->passed) {
            echo "  - {$assertion->name}: {$assertion->message}\n";
        }
    }
}

// Get summary
echo "Passed: {$results->passedCount}/{$results->totalCount}\n";

Advanced Evaluation Patterns

Context Setup

class OrderEvaluation extends BaseEvaluation
{
    protected string $agent = 'order_assistant';

    /**
     * Setup context before each test
     */
    protected function setUp(): void
    {
        // Create test data
        $this->testOrder = Order::factory()->create([
            'status' => 'processing',
            'total' => 99.99,
        ]);
    }

    /**
     * Cleanup after each test
     */
    protected function tearDown(): void
    {
        $this->testOrder->delete();
    }

    public function testCases(): array
    {
        return [
            [
                'name' => 'order_status_query',
                'input' => "What's the status of my order?",
                'context' => [
                    'order_id' => fn() => $this->testOrder->id,
                ],
                 => [],
            ],
        ];
    }
}

Dynamic Test Cases

public function testCases(): array
{
    $testCases = [];

    // Generate test cases from data
    $scenarios = json_decode(file_get_contents('test_scenarios.json'), true);

    foreach ($scenarios as $scenario) {
        $testCases[] = [
            'name' => $scenario['id'],
            'input' => $scenario['input'],
            'expected' => $scenario['expected'],
            'assertions' => $this->buildAssertions($scenario['checks']),
        ];
    }

    return $testCases;
}

Regression Testing

class RegressionEvaluation extends BaseEvaluation
{
    public function testCases(): array
    {
        // Load historical test cases that previously failed
        $regressions = EvaluationResult::where('status', 'failed')
            ->where('fixed', true)
            ->get();

        return $regressions->map(fn($r) => [
            'name' => "regression_{$r->id}",
            'input' => $r->input,
            'assertions' => ['should_not_regress'],
            'context' => ['original_failure' => $r->failure_reason],
        ])->toArray();
    }
}

Built-in Assertions

Assertion	Purpose
ExactMatchAssertion	Response exactly matches expected
ContainsAssertion	Response contains substring
RegexAssertion	Response matches regex pattern
JsonSchemaAssertion	Response matches JSON schema
LengthAssertion	Response length within bounds
SentimentAssertion	Response has expected sentiment
LlmJudgeAssertion	LLM evaluates response quality
NoHallucinationAssertion	Response doesn't contain made-up facts
SafetyAssertion	Response doesn't contain harmful content

Custom Assertion Example

class NoHallucinationAssertion extends BaseAssertion
{
    protected string $description = 'Response should not contain hallucinated facts';

    public function __construct(
        protected array $knownFacts
    ) {}

    public function evaluate(string $response, array $context = []): bool
    {
        // Use LLM to check for hallucinations
        $judge = app(LlmJudge::class);

        return $judge->evaluate(
            prompt: "Does this response contain any facts not supported by the known facts?",
            response: $response,
            context: ['known_facts' => $this->knownFacts]
        );
    }
}

Evaluation Reports

Generate HTML Report

php artisan vizra:eval:run --report=html --output=report.html

Report Contents

• Overall pass/fail statistics
• Per-test-case results
• Assertion details
• Response comparisons
• Timing metrics
• Failure analysis

CI/CD Integration

GitHub Actions Example

- name: Run Agent Evaluations
  run: |
    php artisan vizra:eval:run --format=junit --output=results.xml

- name: Upload Results
  uses: actions/upload-artifact@v3
  with:
    name: evaluation-results
    path: results.xml

Artisan Commands

# Create new evaluation
php artisan vizra:make:eval CustomerServiceEvaluation

# Create new assertion
php artisan vizra:make:assertion ContainsGreetingAssertion

# Run evaluations
php artisan vizra:eval:run

# List evaluations
php artisan vizra:eval:list

Best Practices

1. Test edge cases - Include difficult scenarios, not just happy paths
2. Use multiple assertions - Combine rule-based and LLM-based checks
3. Version test cases - Track changes to test expectations over time
4. Automate in CI/CD - Run evaluations on every deploy
5. Monitor trends - Track pass rates over time to detect regressions