What is the ModerationModel interface in LangChain4j and how can you implement a custom one?

The ModerationModel interface in LangChain4j defines the contract for content moderation checks. It takes a String input and returns a Response<Moderation> — where Moderation contains a boolean flagged() result and optionally category-level scores. LangChain4j's @Moderate AI Services annotation uses whichever ModerationModel you register on the builder.

The built-in implementation is OpenAiModerationModel, which calls OpenAI's text-moderation-latest API. But for custom moderation logic — rule-based keyword filtering, an internal ML model, or a different provider's moderation API — you implement the interface directly:

public class KeywordModerationModel implements ModerationModel {

    private static final Set<String> BLOCKED = Set.of(
        "badword1", "badword2", "competitor-brand"
    );

    @Override
    public Response<Moderation> moderate(String text) {
        boolean flagged = BLOCKED.stream()
            .anyMatch(word -> text.toLowerCase().contains(word));

        return Response.from(
            flagged ? Moderation.flagged(text) : Moderation.notFlagged()
        );
    }
}

// Plug in as the moderation model
SafeAssistant assistant = AiServices.builder(SafeAssistant.class)
    .chatLanguageModel(chatModel)
    .moderationModel(new KeywordModerationModel())
    .build();

Custom implementations are particularly useful for on-premise deployments that cannot use external APIs, for organizations with specific terminology blocklists, or for domain-specific moderation where generic toxicity models produce too many false positives. The interface is small and straightforward — moderate(String) is the only method you must implement.