langchain4j-testing-strategies — Claude Code skill: tests
Guides Java tests for LangChain4j, from mocked ChatModel responses to RAG workflows and Testcontainers-based integration checks.
npx skills add giuseppe-trisciuoglio/developer-kit --skill langchain4j-testing-strategies -a claude-codeWhat langchain4j-testing-strategies does
This skill provides patterns for unit testing LangChain4j services with mocked ChatModel responses, AiServices, retrieval chains, RAG workflows, and tool execution. It also covers testing dependencies such as langchain4j-test, testcontainers, mockito, and assertj, with examples for real services running in containers.
The material is split across references for unit tests, integration tests, advanced cases, dependencies, and workflow patterns. It covers streaming, memory, error handling, health checks, timeouts, and response assertions. Unit tests should avoid real API calls because model responses are non-deterministic and external calls can add cost or hit rate limits.
Integration scenarios require Docker, so check that the Docker daemon is running before relying on Testcontainers. The skill is available for Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, and OpenCode.
What it helps with
- mock ChatModel responses for isolated unit tests
- validate
AiServiceswithout calling external APIs - test retrieval chains and RAG workflows
- run LangChain4j integration checks with Testcontainers
- cover model errors, timeouts, and edge cases
Example prompts for the agent
- Set up a unit test for
AiServiceswith a mockedChatModeland deterministic responses. - Create a RAG integration test using
OllamaChatModel,OllamaEmbeddingModel, and Testcontainers. - Add container health checks, timeouts, and error assertions to my LangChain4j tests.
How to install langchain4j-testing-strategies
1Skills CLI (Vercel)
npx skills add giuseppe-trisciuoglio/developer-kit --skill langchain4j-testing-strategies -a claude-code2Manually: put the files in place
~/.claude/skills/langchain4j-testing-strategies/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/langchain4j-testing-strategies/
1Skills CLI (Vercel)
npx skills add giuseppe-trisciuoglio/developer-kit --skill langchain4j-testing-strategies -a codex2Manually: put the files in place
.agents/skills/langchain4j-testing-strategies/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add giuseppe-trisciuoglio/developer-kit --skill langchain4j-testing-strategies -a cursor2Manually: put the files in place
.cursor/skills/langchain4j-testing-strategies/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install giuseppe-trisciuoglio/developer-kit langchain4j-testing-strategies2Manually: put the files in place
.github/skills/langchain4j-testing-strategies/SKILL.md1Skills CLI (Vercel)
npx skills add giuseppe-trisciuoglio/developer-kit --skill langchain4j-testing-strategies -a gemini-cli2Platform CLI
gemini skills install https://github.com/giuseppe-trisciuoglio/developer-kit --path plugins/developer-kit-java/skills/langchain4j-testing-strategiesManually: put the files in place
.devin/skills/langchain4j-testing-strategies/SKILL.mdThe legacy .windsurf/skills/ path still works
Skills CLI (Vercel)
npx skills add giuseppe-trisciuoglio/developer-kit --skill langchain4j-testing-strategies -a opencodeClaude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
Step by step, with commands for each platform: How to install skills in Claude Code: five ways
Questions about langchain4j-testing-strategies
How do I install langchain4j-testing-strategies in Claude Code?
Run npx skills add giuseppe-trisciuoglio/developer-kit --skill langchain4j-testing-strategies -a claude-code, run the same command again, then check ~/.claude/skills/langchain4j-testing-strategies/SKILL.md.
What does langchain4j-testing-strategies do?
It guides unit, integration, and end-to-end testing for LangChain4j applications. The patterns cover mocked AI models, RAG workflows, retrieval chains, guardrails, and container-based service tests.
What is required for LangChain4j integration tests?
Testcontainers scenarios require Docker. The testing setup can also use langchain4j-test, testcontainers, mockito, and assertj.
Source text
SKILL.md · MIT
---
name: langchain4j-testing-strategies
description: Provides unit test, integration test, and mock AI patterns for LangChain4j applications. Creates mock LLM responses, tests retrieval chains, validates RAG workflows, and implements Testcontainers-based integration tests for Java AI services. Use when unit testing AI services, integration testing LangChain4j components, mocking AI models, or testing LLM-based Java applications.
allowed-tools: Read, Write, Edit, Bash, Glob, Grep
---
# LangChain4J Testing Strategies
## Overview
Patterns for unit testing with mocks, integration testing with Testcontainers, and end-to-end validation of RAG systems, AI Services, and tool execution.
## When to Use
- **Unit testing AI services**: When you need fast, isolated tests for services using LangChain4j AiServices
- **Integration testing LangChain4j components**: When testing real ChatModel, EmbeddingModel, or RAG pipelines with Testcontainers
- **Mocking AI models**: When you need deterministic responses without calling external APIs
- **Testing LLM-based Java applications**: When validating RAG workflows, tool execution, or retrieval chains
## Instructions
### 1. Unit Testing with Mocks
Use mock models for fast, isolated testing. See `references/unit-testing.md`.
```java
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 Maven/Gradle dependencies. See `references/testing-dependencies.md`.
- `langchain4j-test` - Guardrail assertions
- `testcontainers` - Containerized testing
- `mockito` - Mock external dependencies
- `assertj` - Fluent assertions
### 3. Integration Testing with Testcontainers
Test with real services. See `references/integration-testing.md`.
```java
@Testcontainers
class OllamaIntegrationTest {
@Container
static GenericContainer<?> ollama = new GenericContainer<>(
DockerImageName.parse("ollama/ollama:0.5.4")
).withExposedPorts(11434);
@Test
void shouldGenerateResponse() {
// Verify container is healthy
assertTrue(ollama.isRunning());
await().atMost(30, TimeUnit.SECONDS)
.until(() -> ollama.getLogs().contains("API server listening"));
ChatModel model = OllamaChatModel.builder()
.baseUrl(ollama.getEndpoint())
.build();
// Verify model responds before running tests
assertDoesNotThrow(() -> model.generate("ping"));
String response = model.generate("Test query");
assertNotNull(response);
}
}
```
### 4. Advanced Features
Streaming, memory, error handling patterns in `references/advanced-testing.md`.
### 5. Testing Workflow
Follow the testing pyramid from `references/workflow-patterns.md`:
- **70% Unit Tests**: Fast, isolated with mocks
- **20% Integration Tests**: Real services with health checks
- **10% End-to-End Tests**: Complete workflows
```
70% Unit Tests ─ Mock ChatModel, guardrails, edge cases
20% Integration Tests ─ Testcontainers, vector stores, RAG
10% End-to-End Tests ─ Complete user journeys
```
### Troubleshooting
- **Container fails to start**: Check Docker daemon is running, verify image exists, increase timeout
- **Model not responding**: Verify baseUrl is correct, check container logs, ensure model is loaded
- **Test timeout**: Increase `@Timeout` duration for slow models, check container resource limits
- **Flaky tests**: Add retry logic or health checks before assertions
## Examples
### Unit Test
```java
@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
```java
@Testcontainers
class RAGIntegrationTest {
@Container
static GenericContainer<?> ollama = new GenericContainer<>(
DockerImageName.parse("ollama/ollama:0.5.4")
);
@BeforeAll
static void waitForContainerReady() {
await().atMost(60, TimeUnit.SECONDS)
.until(() -> ollama.getLogs().contains("API server listening"));
}
@Test
void shouldCompleteRAGWorkflow() {
assertTrue(ollama.isRunning());
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();
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
- Use `@BeforeEach`/`@AfterEach` for test isolation
- Never call real APIs in unit tests; use mocks
- Include `@Timeout` for external service calls
- Test both success and error handling scenarios
- Validate response coherence and edge cases
## Common Patterns
### Mock Strategy
```java
ChatModel mockModel = mock(ChatModel.class);
when(mockModel.generate(anyString())).thenReturn(Response.from(AiMessage.from("Mocked")));
when(mockModel.generate(eq("Hello"))).thenReturn(Response.from(AiMessage.from("Hi")));
when(mockModel.generate(contains("Java"))).thenReturn(Response.from(AiMessage.from("Java")));
```
### Assertion Helpers
```java
assertThat(response).isNotNull().isNotEmpty();
assertThat(response).containsAll(expectedKeywords);
assertThat(response).doesNotContain("error");
```
## Reference Documentation
- **[Testing Dependencies](references/testing-dependencies.md)** - Maven/Gradle configuration
- **[Unit Testing](references/unit-testing.md)** - Mock models, guardrails
- **[Integration Testing](references/integration-testing.md)** - Testcontainers, real services
- **[Advanced Testing](references/advanced-testing.md)** - Streaming, memory, error handling
- **[Workflow Patterns](references/workflow-patterns.md)** - Test pyramid, best practices
## Constraints and Warnings
- AI responses are non-deterministic; use mocks for reliable unit tests
- Avoid real API calls in tests to prevent costs and rate limiting
- Integration tests require Docker; use container health checks
- RAG tests need properly seeded embedding stores
- Mock-based tests cannot guarantee actual LLM behavior; supplement with integration tests
- Use test-specific configuration profiles; never affect production data
© giuseppe-trisciuoglio · MIT · giuseppe-trisciuoglio/developer-kit