feat(ai): 添加智能体对话功能和相关实体映射

Administrator

20 hours ago cee484403a94584ef1fb55bbac641f7bcbfaf6d8

 src/main/java/cc/mrbird/febs/ai/strategy/Impl/AliLlmStrategyServiceImpl.java

@@ -1,21 +1,26 @@
package cc.mrbird.febs.ai.strategy.Impl;

import cc.mrbird.febs.ai.req.agent.AiRequestDto;
import cc.mrbird.febs.ai.strategy.LlmStrategyService;
import cc.mrbird.febs.ai.strategy.enumerates.LlmStrategyContextEnum;
import cc.mrbird.febs.ai.strategy.param.LlmStrategyDto;
import cc.mrbird.febs.common.entity.FebsResponse;
import cc.mrbird.febs.common.exception.FebsException;
import cn.hutool.core.collection.CollUtil;
import cn.hutool.core.util.ObjectUtil;
import cn.hutool.core.util.StrUtil;
import cn.hutool.json.JSONUtil;
import com.alibaba.dashscope.aigc.generation.Generation;
import com.alibaba.dashscope.aigc.generation.GenerationParam;
import com.alibaba.dashscope.aigc.generation.GenerationResult;
import com.alibaba.dashscope.app.*;
import com.alibaba.dashscope.common.Message;
import com.alibaba.dashscope.common.Role;
import com.alibaba.dashscope.exception.InputRequiredException;
import com.alibaba.dashscope.exception.NoApiKeyException;
import com.alibaba.dashscope.utils.JsonUtils;
import io.reactivex.Flowable;
import lombok.extern.slf4j.Slf4j;
import org.springframework.stereotype.Component;
import reactor.core.publisher.Flux;

@@ -24,14 +29,21 @@
import java.util.HashMap;
import java.util.List;

@Slf4j
@Component("AliLlmStrategyService")
public class AliLlmStrategyServiceImpl implements LlmStrategyService {

    private GenerationParam generationParam;

    private static final String apiKey = "sk-babdcf8799144134915cee2683794b2f";
    private static final String apiKey = "sk-a2323eba1e584066b3a536aefa804970";
    private static final String model = "qwen-plus";
//    private static final String model = "qwen3-14b-ft-202509031002-7446";


    private ApplicationParam applicationParam;
    private ApplicationParam applicationParamSummary;

    private static final String appId = "a5d38240f6b94da6b7f1f7fbe563f50c";
    private static final String SummaryAppId = "19da84392c534db5b2e3f10e698758ab";

    @PostConstruct
    public void init() {
@@ -41,6 +53,18 @@
                // 模型列表：https://help.aliyun.com/zh/model-studio/getting-started/models
                .model(model)
                .resultFormat(GenerationParam.ResultFormat.MESSAGE)
                .build();

        this.applicationParam = ApplicationParam.builder()
                // 若没有配置环境变量，可用百炼API Key将下行替换为：.apiKey("sk-xxx")。但不建议在生产环境中直接将API Key硬编码到代码中，以减少API Key泄露风险。
                .apiKey(apiKey)
                .appId(appId)
                .build();

        this.applicationParamSummary = ApplicationParam.builder()
                // 若没有配置环境变量，可用百炼API Key将下行替换为：.apiKey("sk-xxx")。但不建议在生产环境中直接将API Key硬编码到代码中，以减少API Key泄露风险。
                .apiKey(apiKey)
                .appId(SummaryAppId)
                .build();
    }

@@ -175,4 +199,91 @@
                    throw new FebsException(StrUtil.format("百炼大模型输出失败:{}",error));
                });
    }

    @Override
    public Flux<FebsResponse> llmInvokeStreamingNoThink(AiRequestDto dto) {
        long startTime = System.currentTimeMillis();
        if (ObjectUtil.isEmpty(dto)){
            throw new FebsException("参数异常");
        }
        String talkId = dto.getTalkId();

        String rolePrompt = dto.getRolePrompt();
        List<Message> messages = dto.getMessages();
        HashMap<String, Object> userPromptParams = new HashMap<>();
        userPromptParams.put("role_prompt", rolePrompt);
        if(CollUtil.isNotEmpty( messages)){
            userPromptParams.put("message_list", messages);
        }
        HashMap<String, Object> bizParams = new HashMap<>();
        bizParams.put("user_prompt_params", userPromptParams);

        List<String> knowledgeIds = dto.getKnowledgeIds();
        List<String> fileIds = dto.getFileIds();
        String prompt = dto.getPrompt();

        Application application = new Application();
        applicationParam.setPrompt(prompt);
        applicationParam.setBizParams(JsonUtils.toJsonObject( bizParams));
        // 获取当前的系统时间
        applicationParam.setEnableSystemTime( true);
        // 增量输出
        applicationParam.setIncrementalOutput( true);
        // 思考过程
        applicationParam.setEnableThinking( false);
        // 多轮对话
//        applicationParam.setMessages(messages);
        // 上下文seesionId
//        String sessionId = (String) redisCache.getCacheObject(talkId);
//        if (ObjectUtil.isNotEmpty(sessionId)){
//            applicationParam.setSessionId(talkId);
//        }

        RagOptions ragOptions = null;
        if (CollUtil.isEmpty(fileIds)){
            ragOptions = RagOptions.builder()
                    .pipelineIds(knowledgeIds)
                    .build();
        }else{
            ragOptions = RagOptions.builder()
                    .pipelineIds(knowledgeIds)
                    .fileIds(fileIds)
                    .build();
        }
        applicationParam.setRagOptions(ragOptions);
        Flowable<ApplicationResult> result;
        try {
            result = application.streamCall(applicationParam);
        } catch (NoApiKeyException | InputRequiredException e) {

            throw new FebsException(StrUtil.format("百炼大模型输出失败:{}",e.getMessage()));
        }
        return Flux.from(result)
                .map(message -> {
                    HashMap<String, Object> stringStringHashMap = new HashMap<>();
                    if (!message.getOutput().getFinishReason().equals("stop")){
                        stringStringHashMap.put(LlmStrategyContextEnum.CONTENT.name(),message.getOutput().getText());
                    }
                    if (message.getOutput().getFinishReason().equals("stop")){
                        log.info("百炼大模型输出：{}",message.getOutput().getSessionId());
                        List<ApplicationUsage.ModelUsage> models = message.getUsage().getModels();
                        long outputTokens = models.stream().mapToLong(ApplicationUsage.ModelUsage::getOutputTokens).sum();
                        log.info("百炼大模型输出：{}",outputTokens);
                        long inputTokens = models.stream().mapToLong(ApplicationUsage.ModelUsage::getInputTokens).sum();
                        log.info("百炼大模型输出：{}",inputTokens);
                        stringStringHashMap.put("inputTokens:",inputTokens);
                        stringStringHashMap.put("outputTokens:",outputTokens);
                        stringStringHashMap.put(LlmStrategyContextEnum.CONTENT.name(),message.getOutput().getText());
                    }

                    return new FebsResponse().success().data(stringStringHashMap);
                })
                .doOnComplete(() -> {
                    long endTime = System.currentTimeMillis();
                    System.out.println("百炼大模型输出：" + (endTime - startTime) + "毫秒");
                })
                .doOnError(error -> {
                    throw new FebsException(StrUtil.format("百炼大模型输出失败:{}",error));
                });
    }
}