トレーニング MCP / A2A / ACP利用 AIクラウドネイティブ化 AIリモートアクセス Vector API HAT Babylon Valhalla JCuda TensorFlow for Java FFM Deep Java Library Visual Recognition Jakarta Agentic AI MicroProfile REST Client LangChain4j Jakarta Messaging Quarkus AI Spring AI LangGraph4j Embabel Jakarta Transactions Jakarta Query Jakarta Data Jakarta Security Jakarta Restful Web Services Jakarta RPC MicroProfile Fault Tolerance MicroProfile Telemetry MicroProfile Config Jakarta Websocket Jakarta Config Agentic AI
var apiKey = System.getenv("GOOGLE_API_KEY"); ChatModel model = GoogleAiGeminiChatModel.builder() .apiKey(apiKey) .modelName("gemini-2.5-flash-lite") .build(); var svc = AiServices.create(ChatService.class, model); var response = svc.chat("Tell me a joke."); ビルダーパターンで、モデルやキーを指定 19
@Decision private Result checkFraud (BankTransaction transaction) { String output = model.query( "Is this a fraudulent transaction?" + "If so, how serious is it?", transaction); boolean fraud = isFraud(output); Fraud details = null; if (fraud) details = getFraudDetails(output); return new Result (fraud, details); } 31