ChatModel chatModel = ChatModel.of("http://127.0.0.1:11434/api/chat") .provider("ollama") //Need to specify vendor, used to identify interface style (also called dialect) .model("qwen2.5:1.5b") .defaultSkillAdd(new ToolGatewaySkill()) .build(); // Synchronize the call and print the response message AssistantMessage result = ChatchatModel.prompt("The weather in Hangzhou today？") .options(op->op.toolAdd(new WeatherTools())) //Adding tools .call() .getMessage(); System.out.println(result); // Stream call chatModel.prompt("hello").stream(); //Publisher<ChatResponse>

Skill skill = new SkillDesc("order_expert") .description("Order Assistant") // Dynamic admission: Activated only when "order" is mentioned .isSupported(prompt -> prompt.getUserMessageContent().contains("order")) // Dynamic instructions: Inject different Sops depending on whether the user is a VIP or not .instruction(prompt -> { if ("VIP".equals(prompt.getMeta("user_level"))) { return "This is a VIP customer, please call fast_track_tool first."; } return "Process the order inquiry according to the normal process."; }) .toolAdd(new OrderTools()); chatModel.prompt("Where is my order from yesterday？") .options(o->o.skillAdd(skill)) .call();

//Building a Knowledge Warehouse EmbeddingModel embeddingModel = EmbeddingModel.of(apiUrl).apiKey(apiKey).provider(provider).model(model).batchSize(10).build(); RerankingModel rerankingModel = RerankingModel.of(apiUrl).apiKey(apiKey).provider(provider).model(model).build(); InMemoryRepository repository = new InMemoryRepository(TestUtils.getEmbeddingModel()); //3.初始化知识库 repository.insert(new PdfLoader(pdfUri).load()); //retrieval List<Document> docs = repository.search(query); //You can rearrange it if you want docs = rerankingModel.rerank(query, docs); //Cue enhancement is ChatMessage message = ChatMessage.ofUserAugment(query, docs); //Calling the llm chatModel.prompt(message) .call();

//server @McpServerEndpoint(channel = McpChannel.STREAMABLE, mcpEndpoint = "/mcp") public class MyMcpServer { @ToolMapping(description = "Checking the weather") public String getWeather(@Param(description = "city") String location) { return "It's sunny, 25 degrees"; } } //client McpClientProvider clientProvider = McpClientProvider.builder() .channel(McpChannel.STREAMABLE) .url("http://localhost:8080/mcp") .build();

//Reflective intelligent agent: ReActAgent agent = ReActAgent.of(chatModel) // 或者用 SimpleAgent.of(chatModel) .name("weather_expert") .description("Check the weather and provide advice") .defaultToolAdd(weatherTool) // Inject MCP or local tools .build(); agent.prompt("What to wear in Beijing today？").call(); // Autocomplete: Think -> Call tool -> Observe -> Summarize // Constructing a team agent: Automatically arranging member roles through protocols TeamAgent team = TeamAgent.of(chatModel) .name("marketing_team") .protocol(TeamProtocols.HIERARCHICAL) // Hierarchical collaboration (6 preset protocols) .agentAdd(copywriterAgent) // Copywriter expert .agentAdd(illustratorAgent) // Illustrator expert .build(); team.prompt("Plan a promotion scheme for deep-sea mineral water").call(); // Supervisor automatically decomposes tasks and assigns them to corresponding experts .defaultToolAdd(weatherTool) // Inject MCP or local tools