feat(ai): 添加阿里百炼工作流策略实现

Administrator

2025-09-04 46a2e8027a053d4ba7a4dfe357e562c9b41a1047

 src/main/java/cc/mrbird/febs/ai/service/impl/ApiMemberTalkStreamServiceImpl.java

@@ -182,6 +182,57 @@
        return llmStrategyFactory.getCalculationStrategyMap().get(modelName).llmInvokeStreamingNoThink(llmStrategyDtoList);
    }

    @Override
    public Flux<FebsResponse> answerV2(AiTalkAnswerStreamDto dto) {


        String memberUuid = LoginUserUtil.getLoginUser().getMemberUuid();
        Integer type = dto.getType();
        String memberTalkId = dto.getId();
        AiMemberTalk aiMemberTalk = this.getById(memberTalkId);
        if (ObjectUtil.isNull(aiMemberTalk)){
            throw new FebsException("对话不存在");
        }

        LambdaQueryWrapper<AiProductRoleLink> productLinkQuery = Wrappers.lambdaQuery(AiProductRoleLink.class);
        productLinkQuery.eq(AiProductRoleLink::getProductId,aiMemberTalk.getProductId());
        productLinkQuery.last("limit 1");
        AiProductRoleLink aiProductRoleLink = aiProductRoleLinkService.getByQuery(productLinkQuery);
        if(ObjectUtil.isNull(aiProductRoleLink)){
            throw new FebsException("产品没有关联AI陪练");
        }

        String productRoleId = aiProductRoleLink.getProductRoleId();
        AiProductRole aiProductRole = aiProductRoleService.getById(productRoleId);
        if (ObjectUtil.isNull(aiProductRole)){
            throw new FebsException("产品AI陪练不存在");
        }
        LambdaQueryWrapper<AiMemberTalkItem> memberTalkItemQuery = Wrappers.lambdaQuery(AiMemberTalkItem.class);
        memberTalkItemQuery.eq(AiMemberTalkItem::getMemberId,memberUuid);
        memberTalkItemQuery.eq(AiMemberTalkItem::getMemberTalkId,memberTalkId);
        memberTalkItemQuery.eq(AiMemberTalkItem::getType,1);
        memberTalkItemQuery.orderByDesc(AiMemberTalkItem::getCreatedTime);
        memberTalkItemQuery.last("limit 1");
        AiMemberTalkItem aiMemberTalkItem = aiMemberTalkItemService.getByQuery(memberTalkItemQuery);

        String question = aiMemberTalkItem.getContext();
        String promptHead = aiProductRole.getPromptHead();
        String answer = dto.getReqContext();

        List<LlmStrategyDto> llmStrategyDtoList = new ArrayList<>();
        LlmStrategyDto llmStrategyDto = this.buildLlmStrategyDtoList(promptHead, 1);
        llmStrategyDtoList.add(llmStrategyDto);
        llmStrategyDto = this.buildLlmStrategyDtoList(question, 3);
        llmStrategyDtoList.add(llmStrategyDto);
        llmStrategyDto = this.buildLlmStrategyDtoList(answer, 2);
        llmStrategyDtoList.add(llmStrategyDto);
        llmStrategyDto = this.buildLlmStrategyDtoList(String.valueOf(type), 4);
        llmStrategyDtoList.add(llmStrategyDto);
        String modelName = LlmStrategyEnum.getName(aiService.getSystemSetAiType());

        return llmStrategyFactory.getCalculationStrategyMap().get(modelName).llmInvokeStreamingNoThink(llmStrategyDtoList);
    }

    private String buildPrompt(String question,String answer,String promptHead, String promptTemplate,Integer type){
        AiPromptJsonReq aiPromptJsonReq = new AiPromptJsonReq();
//        aiPromptJsonReq.setQuestion( question);
@@ -204,6 +255,9 @@
        if (type == 3){
            llmStrategyDto.setRole(Role.ASSISTANT.getValue());
        }
        if (type == 4){
            llmStrategyDto.setRole(Role.TOOL.getValue());
        }
        llmStrategyDto.setContent(Str);

        return llmStrategyDto;