Spring AI 集成 Graph

使用流式 ChatClient

ARGI 支持通过 ChatClient 进行流式输出。

使用流式 ChatClient

import org.springframework.ai.chat.client.ChatClient;
import org.springframework.ai.chat.model.ChatResponse;
import reactor.core.publisher.Flux;

// 使用流式输出
Flux<ChatResponse> flux = chatClient.prompt()
      .user("tell me a joke")
      .stream()
      .chatResponse();

// 订阅流式响应
flux.subscribe(
      response -> {
          String content = response.getResult().getOutput().getText();
          System.out.print(content);
      },
      error -> System.err.println("Error: " + error.getMessage()),
      () -> System.out.println("
Stream completed")
);

使用 Reactor 的阻塞式处理

使用 Reactor 的阻塞式处理

Flux<ChatResponse> flux = chatClient.prompt()
      .user("tell me a joke")
      .stream()
      .chatResponse();

// 使用 Reactor 的阻塞式处理
flux.collectList().block().forEach(response -> {
  System.out.println("Received: " + response.getResult().getOutput().getText());
});

输出示例:

Sure, here's a joke for you:

Why don't scientists trust atoms?

Because they make up everything!
Stream completed

在 Graph 节点中使用流式输出

创建带流式输出的 Graph 节点

参考 节点流式输出文档 获取完整示例。

创建带流式输出的 Graph 节点

import io.github.agentic.ai.graph.OverAllState;
import io.github.agentic.ai.graph.action.NodeAction;
import org.springframework.ai.chat.client.ChatClient;
import reactor.core.publisher.Flux;

import java.util.Map;

public class StreamingAgentNode implements NodeAction {

  private final ChatClient chatClient;

  public StreamingAgentNode(ChatClient.Builder builder) {
      this.chatClient = builder.build();
  }

  @Override
  public Map<String, Object> apply(OverAllState state) {
      String userMessage = (String) state.value("query").orElse("Hello");

      // 使用流式输出
      Flux<String> contentFlux = chatClient.prompt()
              .user(userMessage)
              .stream()
              .content();

      return Map.of("answer", contentFlux);
  }
}

配置和运行

配置和运行流式 Graph

import io.github.agentic.ai.graph.StateGraph;
import io.github.agentic.ai.graph.OverAllState;
import io.github.agentic.ai.graph.CompiledGraph;
import org.springframework.ai.chat.client.ChatClient;

// 配置 Graph
StateGraph graph = new StateGraph(keyStrategyFactory)
  .addNode("agent", new StreamingAgentNode(chatClientBuilder))
  .addEdge(StateGraph.START, "agent")
  .addEdge("agent", StateGraph.END);

CompiledGraph compiledGraph = graph.compile();

// 执行
Map<String, Object> input = Map.of("query", "Hello");
OverAllState result = compiledGraph.invoke(input);

System.out.println("Final result: " + result.value("answer").orElse(""));

相关文档

• 流式输出 - 完整的流式输出机制
• Workflow 编排指南 - Graph 基础使用
• Spring AI 文档 - Spring AI 官方文档