langchain4j-testing-strategies

📁 giuseppe-trisciuoglio/developer-kit 📅 10 days ago
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npx skills add https://github.com/giuseppe-trisciuoglio/developer-kit --skill langchain4j-testing-strategies

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Skill 文档

LangChain4J Testing Strategies

Overview

LangChain4J testing requires specialized strategies due to the non-deterministic nature of LLM responses and the complexity of AI workflows. This skill provides comprehensive patterns for unit testing with mocks, integration testing with Testcontainers, and end-to-end testing for RAG systems, AI Services, and tool execution.

When to Use This Skill

Use this skill when:

  • Building AI-powered applications with LangChain4J
  • Writing unit tests for AI services and guardrails
  • Setting up integration tests with real LLM models
  • Creating mock-based tests for faster test execution
  • Using Testcontainers for isolated testing environments
  • Testing RAG (Retrieval-Augmented Generation) systems
  • Validating tool execution and function calling
  • Testing streaming responses and async operations
  • Setting up end-to-end tests for AI workflows
  • Implementing performance and load testing

Instructions

To test LangChain4J applications effectively, follow these key strategies:

1. Start with Unit Testing

Use mock models for fast, isolated testing of business logic. See references/unit-testing.md for detailed examples.

// Example: Mock ChatModel for unit tests
ChatModel mockModel = mock(ChatModel.class);
when(mockModel.generate(any(String.class)))
    .thenReturn(Response.from(AiMessage.from("Mocked response")));

var service = AiServices.builder(AiService.class)
        .chatModel(mockModel)
        .build();

2. Configure Testing Dependencies

Setup proper Maven/Gradle dependencies for testing. See references/testing-dependencies.md for complete configuration.

Key dependencies:

  • langchain4j-test – Testing utilities and guardrail assertions
  • testcontainers – Integration testing with containerized services
  • mockito – Mock external dependencies
  • assertj – Better assertions

3. Implement Integration Tests

Test with real services using Testcontainers. See references/integration-testing.md for container setup examples.

@Testcontainers
class OllamaIntegrationTest {
    @Container
    static GenericContainer<?> ollama = new GenericContainer<>(
        DockerImageName.parse("ollama/ollama:latest")
    ).withExposedPorts(11434);

    @Test
    void shouldGenerateResponse() {
        ChatModel model = OllamaChatModel.builder()
                .baseUrl(ollama.getEndpoint())
                .build();
        String response = model.generate("Test query");
        assertNotNull(response);
    }
}

4. Test Advanced Features

For streaming responses, memory management, and complex workflows, refer to references/advanced-testing.md.

5. Apply Testing Workflows

Follow testing pyramid patterns and best practices from references/workflow-patterns.md.

  • 70% Unit Tests: Fast, isolated business logic testing
  • 20% Integration Tests: Real service interactions
  • 10% End-to-End Tests: Complete user workflows

Examples

Basic Unit Test

@Test
void shouldProcessQueryWithMock() {
    ChatModel mockModel = mock(ChatModel.class);
    when(mockModel.generate(any(String.class)))
        .thenReturn(Response.from(AiMessage.from("Test response")));

    var service = AiServices.builder(AiService.class)
            .chatModel(mockModel)
            .build();

    String result = service.chat("What is Java?");
    assertEquals("Test response", result);
}

Integration Test with Testcontainers

@Testcontainers
class RAGIntegrationTest {
    @Container
    static GenericContainer<?> ollama = new GenericContainer<>(
        DockerImageName.parse("ollama/ollama:latest")
    );

    @Test
    void shouldCompleteRAGWorkflow() {
        // Setup models and stores
        var chatModel = OllamaChatModel.builder()
                .baseUrl(ollama.getEndpoint())
                .build();

        var embeddingModel = OllamaEmbeddingModel.builder()
                .baseUrl(ollama.getEndpoint())
                .build();

        var store = new InMemoryEmbeddingStore<>();
        var retriever = EmbeddingStoreContentRetriever.builder()
                .chatModel(chatModel)
                .embeddingStore(store)
                .embeddingModel(embeddingModel)
                .build();

        // Test complete workflow
        var assistant = AiServices.builder(RagAssistant.class)
                .chatLanguageModel(chatModel)
                .contentRetriever(retriever)
                .build();

        String response = assistant.chat("What is Spring Boot?");
        assertNotNull(response);
        assertTrue(response.contains("Spring"));
    }
}

Best Practices

Test Isolation

  • Each test must be independent
  • Use @BeforeEach and @AfterEach for setup/teardown
  • Avoid sharing state between tests

Mock External Dependencies

  • Never call real APIs in unit tests
  • Use mocks for ChatModel, EmbeddingModel, and external services
  • Test error handling scenarios

Performance Considerations

  • Unit tests should run in < 50ms
  • Integration tests should use container reuse
  • Include timeout assertions for slow operations

Quality Assertions

  • Test both success and error scenarios
  • Validate response coherence and relevance
  • Include edge case testing (empty inputs, large payloads)

Reference Documentation

For comprehensive testing guides and API references, see the included reference documents:

Common Patterns

Mock Strategy

// For fast unit tests
ChatModel mockModel = mock(ChatModel.class);
when(mockModel.generate(anyString())).thenReturn(Response.from(AiMessage.from("Mocked")));

// For specific responses
when(mockModel.generate(eq("Hello"))).thenReturn(Response.from(AiMessage.from("Hi")));
when(mockModel.generate(contains("Java"))).thenReturn(Response.from(AiMessage.from("Java response")));

Test Configuration

// Use test-specific profiles
@TestPropertySource(properties = {
    "langchain4j.ollama.base-url=http://localhost:11434"
})
class TestConfig {
    // Test with isolated configuration
}

Assertion Helpers

// Custom assertions for AI responses
assertThat(response).isNotNull().isNotEmpty();
assertThat(response).containsAll(expectedKeywords);
assertThat(response).doesNotContain("error");

Performance Requirements

  • Unit Tests: < 50ms per test
  • Integration Tests: Use container reuse for faster startup
  • Timeout Tests: Include @Timeout for external service calls
  • Memory Management: Test conversation window limits and cleanup

Security Considerations

  • Never use real API keys in tests
  • Mock external API calls completely
  • Test prompt injection detection
  • Validate output sanitization

Testing Pyramid Implementation

70% Unit Tests
  ├─ Business logic validation
  ├─ Guardrail testing
  ├─ Mock tool execution
  └─ Edge case handling

20% Integration Tests
  ├─ Testcontainers with Ollama
  ├─ Vector store testing
  ├─ RAG workflow validation
  └─ Performance benchmarking

10% End-to-End Tests
  ├─ Complete user journeys
  ├─ Real model interactions
  └─ Performance under load

Related Skills

  • spring-boot-test-patterns
  • unit-test-service-layer
  • unit-test-boundary-conditions

References

Constraints and Warnings

  • AI model responses are non-deterministic; tests should use mocks for reliability.
  • Real API calls in tests should be avoided to prevent costs and rate limiting issues.
  • Integration tests with Testcontainers require Docker to be available.
  • Memory management tests should verify proper cleanup between test runs.
  • Tool execution tests should validate both success and failure scenarios.
  • Streaming response tests require proper handling of partial data.
  • RAG tests need properly seeded embedding stores for consistent results.
  • Performance tests may have high variance due to LLM response times.
  • Always use test-specific configuration profiles to avoid affecting production data.
  • Mock-based tests cannot guarantee actual LLM behavior; supplement with integration tests.