langchain4j-testing-strategies

Testing LangChain4j applications requires a layered strategy: start with unit tests using mock models for fast feedback, then add integration tests with Testcontainers for real service validation. Cover unit testing, integration testing, mock-based testing, streaming scenarios, RAG workflows, and end-to-end AI workflows to ensure comprehensive guardrail coverage.

Use langchain4j-test and Mockito to create mock model pipelines in unit tests. Mock models provide fast feedback without external dependencies, and should be combined with AssertJ for assertion validation to test core logic in isolation before running integration tests.

Yes, use Testcontainers for integration testing to run real services in isolated containers. Testcontainers work with LangChain4j to validate streaming handlers, async scenarios, and RAG workflows against actual external services without modifying production configurations.

Test RAG workflows by combining mock retrieval components with integration tests that validate end-to-end data flow. Mock the retrieval step during unit testing for speed, then layer Testcontainers-based integration tests to verify real vector stores, knowledge bases, and guardrail coverage.

Validate tool execution through mock-based unit tests that verify function calls and parameters, then use integration tests with Testcontainers to confirm tool behavior against real endpoints. Include streaming and async validation to cover edge cases in tool chaining and execution order.

Yes, both are essential. Unit tests with mocks provide fast feedback for core logic; integration tests with Testcontainers validate real-world behavior, streaming handlers, and guardrails. Start with unit tests, then layer integration coverage as complexity increases.