google-agents-cli-scaffold
Project scaffolding, deployment configuration, and CI/CD setup for Google ADK agents.
langchain4j-testing-strategies
Testing strategies for LangChain4j-powered applications. Mock LLM responses, test retrieval chains, and validate AI workflows. Use when testing AI-powered features reliably.
Full skill instructions
Use this skill when:
To test LangChain4J applications effectively, follow these key strategies:
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();
Setup proper Maven/Gradle dependencies for testing. See references/testing-dependencies.md for complete configuration.
Key dependencies:
langchain4j-test - Testing utilities and guardrail assertionstestcontainers - Integration testing with containerized servicesmockito - Mock external dependenciesassertj - Better assertionsTest 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);
}
}
For streaming responses, memory management, and complex workflows, refer to references/advanced-testing.md.
Follow testing pyramid patterns and best practices from references/workflow-patterns.md.
@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);
}
@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"));
}
}
@BeforeEach and @AfterEach for setup/teardownFor comprehensive testing guides and API references, see the included reference documents:
// 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")));
// Use test-specific profiles
@TestPropertySource(properties = {
"langchain4j.ollama.base-url=http://localhost:11434"
})
class TestConfig {
// Test with isolated configuration
}
// Custom assertions for AI responses
assertThat(response).isNotNull().isNotEmpty();
assertThat(response).containsAll(expectedKeywords);
assertThat(response).doesNotContain("error");
@Timeout for external service calls70% 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
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