package com.kcnf.ai.tool;

import org.springframework.stereotype.Component;
import org.springframework.util.StringUtils;

import java.util.function.Function;

@Component
public class MenuRecommendTool implements Function<MenuRecommendRequest, String> {

    @Override
    public String apply(MenuRecommendRequest taste) {
        if (taste == null || !StringUtils.hasLength(taste.getTaste())) {
            return "请告诉我你的口味偏好，比如：辣、甜、酸。";
        }

        if (taste.getTaste().contains("辣")) {
            return "🌶️ 推荐菜单：麻辣香锅、水煮牛肉、酸辣粉。";
        } else if (taste.getTaste().contains("甜")) {
            return "🍰 推荐菜单：糖醋排骨、拔丝地瓜、杨枝甘露。";
        } else if (taste.getTaste().contains("清淡")) {
            return "🥬 推荐菜单：白灼菜心、山药排骨汤、清蒸鲈鱼。";
        } else {
            return "🥢 推荐菜单：宫保鸡丁、番茄炒蛋、家常豆腐。";
        }
    }
}

package com.kcnf.ai.config;

import com.alibaba.cloud.ai.dashscope.api.DashScopeApi;
import com.alibaba.cloud.ai.dashscope.chat.DashScopeChatModel;
import com.alibaba.cloud.ai.graph.agent.ReactAgent;
import com.alibaba.cloud.ai.graph.checkpoint.savers.MemorySaver;
import com.kcnf.ai.tool.MenuRecommendRequest;
import com.kcnf.ai.tool.MenuRecommendTool;
import org.springframework.ai.support.ToolCallbacks;
import org.springframework.ai.tool.ToolCallback;
import org.springframework.ai.tool.function.FunctionToolCallback;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;

@Configuration
public class AgentConfig {

    @Value("${spring.ai.dashscope.api-key}")
    private String apiKey;

    @Bean
    public DashScopeChatModel chatModel() {
        DashScopeApi dashScopeApi = DashScopeApi.builder()
                .apiKey(apiKey)
                .build();
        return DashScopeChatModel.builder()
                .dashScopeApi(dashScopeApi)
                .build();
    }


    @Bean
    public ToolCallback menuRecommendToolCallback(MenuRecommendTool menuTool) {
        return FunctionToolCallback.builder("recommend_menu", menuTool)
                .description("根据用户的口味偏好推荐合适的菜品")
                .inputType(MenuRecommendRequest.class)
                .build();
    }

    @Bean
    public ReactAgent reactAgent(DashScopeChatModel chatModel, ToolCallback menuRecommendToolCallback) {
        return ReactAgent.builder()
                .name("点餐助手")
                .model(chatModel)
                .tools(menuRecommendToolCallback)
                .systemPrompt("你是一个友好的餐厅点餐助手。你有推荐菜品的工具。当用户询问吃什么时，你需要调用工具来推荐。如果用户没有说明口味，请主动询问。")
                .saver(new MemorySaver())
                .build();
    }
}

package com.kcnf.ai.controller;


import com.alibaba.cloud.ai.graph.RunnableConfig;
import com.alibaba.cloud.ai.graph.agent.ReactAgent;
import lombok.SneakyThrows;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RequestParam;
import org.springframework.web.bind.annotation.RestController;

@RestController
public class ChatController {

    @Autowired
    private ReactAgent reactAgent;

    @SneakyThrows
    @GetMapping("/ai/chat")
    public String chat(@RequestParam String message, @RequestParam(defaultValue = "default-user") String userId) {
        // 通过 threadId 隔离不同用户的会话，实现连续对话
        RunnableConfig config = RunnableConfig.builder()
                .threadId(userId)
                .build();

        // 调用 Agent 并返回结果
        return reactAgent.call(message, config).getText();
    }
}