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【代码优化】AI:新增 AIUtils,用于对接 spring ai 各种对象的构建
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@ -26,9 +26,10 @@ public class AiWriteController {
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private AiWriteService writeService;
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@PostMapping(value = "/generate-stream", produces = MediaType.TEXT_EVENT_STREAM_VALUE)
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@PermitAll
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@Operation(summary = "写作生成(流式)", description = "流式返回,响应较快")
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@PermitAll // 解决 SSE 最终响应的时候,会被 Access Denied 拦截的问题
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public Flux<CommonResult<String>> generateWriteContent(@RequestBody @Valid AiWriteGenerateReqVO generateReqVO) {
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return writeService.generateWriteContent(generateReqVO, getLoginUserId());
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}
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}
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@ -4,8 +4,7 @@ import cn.hutool.core.collection.CollUtil;
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import cn.hutool.core.util.ObjUtil;
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import cn.hutool.core.util.StrUtil;
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import cn.iocoder.yudao.framework.ai.core.enums.AiPlatformEnum;
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import cn.iocoder.yudao.framework.ai.core.model.xinghuo.XingHuoChatModel;
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import cn.iocoder.yudao.framework.ai.core.model.xinghuo.XingHuoOptions;
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import cn.iocoder.yudao.framework.ai.core.util.AiUtils;
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import cn.iocoder.yudao.framework.common.pojo.CommonResult;
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import cn.iocoder.yudao.framework.common.pojo.PageResult;
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import cn.iocoder.yudao.framework.common.util.object.BeanUtils;
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@ -19,7 +18,6 @@ import cn.iocoder.yudao.module.ai.dal.mysql.chat.AiChatMessageMapper;
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import cn.iocoder.yudao.module.ai.enums.ErrorCodeConstants;
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import cn.iocoder.yudao.module.ai.service.model.AiApiKeyService;
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import cn.iocoder.yudao.module.ai.service.model.AiChatModelService;
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import com.alibaba.cloud.ai.tongyi.chat.TongYiChatOptions;
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import jakarta.annotation.Resource;
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import lombok.extern.slf4j.Slf4j;
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import org.springframework.ai.chat.messages.*;
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@ -28,9 +26,6 @@ import org.springframework.ai.chat.model.ChatResponse;
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import org.springframework.ai.chat.model.StreamingChatModel;
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import org.springframework.ai.chat.prompt.ChatOptions;
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import org.springframework.ai.chat.prompt.Prompt;
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import org.springframework.ai.ollama.api.OllamaOptions;
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import org.springframework.ai.openai.OpenAiChatOptions;
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import org.springframework.ai.qianfan.QianFanChatOptions;
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import org.springframework.stereotype.Service;
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import org.springframework.transaction.annotation.Transactional;
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import reactor.core.publisher.Flux;
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@ -148,46 +143,17 @@ public class AiChatMessageServiceImpl implements AiChatMessageService {
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}
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// 1.2 history message 历史消息
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List<AiChatMessageDO> contextMessages = filterContextMessages(messages, conversation, sendReqVO);
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contextMessages.forEach(message -> {
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// TODO @芋艿:看看有没优化空间
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if (MessageType.USER.getValue().equals(message.getType())) {
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chatMessages.add(new UserMessage(message.getContent()));
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} else {
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chatMessages.add(new AssistantMessage(message.getContent()));
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}
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});
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contextMessages.forEach(message -> chatMessages.add(AiUtils.buildMessage(message.getType(), message.getContent())));
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// 1.3 user message 新发送消息
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chatMessages.add(new UserMessage(sendReqVO.getContent()));
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// 2. 构建 ChatOptions 对象
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AiPlatformEnum platform = AiPlatformEnum.validatePlatform(model.getPlatform());
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ChatOptions chatOptions = buildChatOptions(platform, model.getModel(),
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ChatOptions chatOptions = AiUtils.buildChatOptions(platform, model.getModel(),
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conversation.getTemperature(), conversation.getMaxTokens());
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return new Prompt(chatMessages, chatOptions);
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}
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private static ChatOptions buildChatOptions(AiPlatformEnum platform, String model, Double temperature, Integer maxTokens) {
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Float temperatureF = temperature != null ? temperature.floatValue() : null;
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//noinspection EnhancedSwitchMigration
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switch (platform) {
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case OPENAI:
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return OpenAiChatOptions.builder().withModel(model).withTemperature(temperatureF).withMaxTokens(maxTokens).build();
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case OLLAMA:
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return OllamaOptions.create().withModel(model).withTemperature(temperatureF).withNumPredict(maxTokens);
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case YI_YAN:
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// TODO 芋艿:貌似 model 只要一设置,就报错
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// return QianFanChatOptions.builder().withModel(model).withTemperature(temperatureF).withMaxTokens(maxTokens).build();
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return QianFanChatOptions.builder().withTemperature(temperatureF).withMaxTokens(maxTokens).build();
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case XING_HUO:
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return new XingHuoOptions().setChatModel(XingHuoChatModel.valueOfModel(model)).setTemperature(temperatureF)
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.setMaxTokens(maxTokens);
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case QIAN_WEN:
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return TongYiChatOptions.builder().withModel(model).withTemperature(temperature).withMaxTokens(maxTokens).build();
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default:
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throw new IllegalArgumentException(StrUtil.format("未知平台({})", platform));
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}
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}
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/**
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* 从历史消息中,获得倒序的 n 组消息作为消息上下文
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*
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@ -2,8 +2,7 @@ package cn.iocoder.yudao.module.ai.service.write;
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import cn.hutool.core.util.StrUtil;
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import cn.iocoder.yudao.framework.ai.core.enums.AiPlatformEnum;
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import cn.iocoder.yudao.framework.ai.core.model.xinghuo.XingHuoChatModel;
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import cn.iocoder.yudao.framework.ai.core.model.xinghuo.XingHuoOptions;
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import cn.iocoder.yudao.framework.ai.core.util.AiUtils;
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import cn.iocoder.yudao.framework.common.pojo.CommonResult;
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import cn.iocoder.yudao.framework.common.util.object.BeanUtils;
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import cn.iocoder.yudao.module.ai.controller.admin.write.vo.AiWriteGenerateReqVO;
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@ -16,16 +15,12 @@ import cn.iocoder.yudao.module.ai.enums.write.AiWriteTypeEnum;
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import cn.iocoder.yudao.module.ai.service.model.AiApiKeyService;
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import cn.iocoder.yudao.module.ai.service.model.AiChatModelService;
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import cn.iocoder.yudao.module.system.api.dict.DictDataApi;
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import com.alibaba.cloud.ai.tongyi.chat.TongYiChatOptions;
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import jakarta.annotation.Resource;
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import lombok.extern.slf4j.Slf4j;
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import org.springframework.ai.chat.model.ChatResponse;
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import org.springframework.ai.chat.model.StreamingChatModel;
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import org.springframework.ai.chat.prompt.ChatOptions;
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import org.springframework.ai.chat.prompt.Prompt;
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import org.springframework.ai.ollama.api.OllamaOptions;
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import org.springframework.ai.openai.OpenAiChatOptions;
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import org.springframework.ai.qianfan.QianFanChatOptions;
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import org.springframework.stereotype.Service;
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import reactor.core.publisher.Flux;
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@ -56,19 +51,21 @@ public class AiWriteServiceImpl implements AiWriteService {
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@Override
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public Flux<CommonResult<String>> generateWriteContent(AiWriteGenerateReqVO generateReqVO, Long userId) {
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// 1.1 校验模型 TODO 芋艿 是不是取默认的模型也ok?
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// 1.1 校验模型 TODO 芋艿 是不是取默认的模型也ok?;那可以,有限拿 chatRole 的角色;如果没有,则获取默认的;
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AiChatModelDO model = chatModalService.getRequiredDefaultChatModel();
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StreamingChatModel chatClient = apiKeyService.getChatClient(model.getKeyId());
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AiPlatformEnum platform = AiPlatformEnum.validatePlatform(model.getPlatform());
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ChatOptions chatOptions = buildChatOptions(platform, model.getModel(), model.getTemperature(), model.getMaxTokens());
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// 1.2 插入写作信息
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// TODO @xin:建议把 writeDO.setUserId(userId).setModel(model.getModel()).setPlatform(platform.getPlatform()),写在 toBean 的 consumer 里;原因是,让这个 set 保持完整性
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AiWriteDO writeDO = BeanUtils.toBean(generateReqVO, AiWriteDO.class);
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writeMapper.insert(writeDO.setUserId(userId).setModel(model.getModel()).setPlatform(platform.getPlatform()));
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// 2.1 构建提示词
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ChatOptions chatOptions = AiUtils.buildChatOptions(platform, model.getModel(), model.getTemperature(), model.getMaxTokens());
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Prompt prompt = new Prompt(buildWritingPrompt(generateReqVO), chatOptions);
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Flux<ChatResponse> streamResponse = chatClient.stream(prompt);
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// 2.2 流式返回
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StringBuffer contentBuffer = new StringBuffer();
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return streamResponse.map(chunk -> {
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@ -92,7 +89,9 @@ public class AiWriteServiceImpl implements AiWriteService {
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String tone = dictDataApi.getDictDataLabel(DictTypeConstants.AI_WRITE_TONE, generateReqVO.getFormat());
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String language = dictDataApi.getDictDataLabel(DictTypeConstants.AI_WRITE_LANGUAGE, generateReqVO.getFormat());
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String length = dictDataApi.getDictDataLabel(DictTypeConstants.AI_WRITE_LENGTH, generateReqVO.getFormat());
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// TODO @xin:建议改成 if return 哈;更简洁;
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if (Objects.equals(writeType, AiWriteTypeEnum.WRITING.getType())) {
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// TODO @xin:写成静态枚举哈
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template = "请撰写一篇关于 [{}] 的文章。文章的内容格式为:[{}],语气为:[{}],语言为:[{}],长度为:[{}]。请确保涵盖主要内容,不需要除了正文内容外的其他回复,如标题、额外的解释或道歉。";
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return StrUtil.format(template, generateReqVO.getPrompt(), format, tone, language, length);
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} else if (Objects.equals(writeType, AiWriteTypeEnum.REPLY.getType())) {
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@ -103,27 +102,4 @@ public class AiWriteServiceImpl implements AiWriteService {
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}
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}
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// TODO 芋艿:复用
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private static ChatOptions buildChatOptions(AiPlatformEnum platform, String model, Double temperature, Integer maxTokens) {
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Float temperatureF = temperature != null ? temperature.floatValue() : null;
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//noinspection EnhancedSwitchMigration
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switch (platform) {
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case OPENAI:
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return OpenAiChatOptions.builder().withModel(model).withTemperature(temperatureF).withMaxTokens(maxTokens).build();
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case OLLAMA:
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return OllamaOptions.create().withModel(model).withTemperature(temperatureF).withNumPredict(maxTokens);
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case YI_YAN:
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// TODO 芋艿:貌似 model 只要一设置,就报错
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// return QianFanChatOptions.builder().withModel(model).withTemperature(temperatureF).withMaxTokens(maxTokens).build();
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return QianFanChatOptions.builder().withTemperature(temperatureF).withMaxTokens(maxTokens).build();
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case XING_HUO:
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return new XingHuoOptions().setChatModel(XingHuoChatModel.valueOfModel(model)).setTemperature(temperatureF)
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.setMaxTokens(maxTokens);
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case QIAN_WEN:
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return TongYiChatOptions.builder().withModel(model).withTemperature(temperature).withMaxTokens(maxTokens).build();
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default:
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throw new IllegalArgumentException(StrUtil.format("未知平台({})", platform));
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}
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}
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}
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@ -0,0 +1,59 @@
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package cn.iocoder.yudao.framework.ai.core.util;
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import cn.hutool.core.util.StrUtil;
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import cn.iocoder.yudao.framework.ai.core.enums.AiPlatformEnum;
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import cn.iocoder.yudao.framework.ai.core.model.xinghuo.XingHuoChatModel;
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import cn.iocoder.yudao.framework.ai.core.model.xinghuo.XingHuoOptions;
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import com.alibaba.cloud.ai.tongyi.chat.TongYiChatOptions;
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import org.springframework.ai.chat.messages.*;
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import org.springframework.ai.chat.prompt.ChatOptions;
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import org.springframework.ai.ollama.api.OllamaOptions;
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import org.springframework.ai.openai.OpenAiChatOptions;
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import org.springframework.ai.qianfan.QianFanChatOptions;
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/**
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* Spring AI 工具类
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*
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* @author 芋道源码
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*/
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public class AiUtils {
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public static ChatOptions buildChatOptions(AiPlatformEnum platform, String model, Double temperature, Integer maxTokens) {
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Float temperatureF = temperature != null ? temperature.floatValue() : null;
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//noinspection EnhancedSwitchMigration
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switch (platform) {
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case OPENAI:
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return OpenAiChatOptions.builder().withModel(model).withTemperature(temperatureF).withMaxTokens(maxTokens).build();
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case OLLAMA:
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return OllamaOptions.create().withModel(model).withTemperature(temperatureF).withNumPredict(maxTokens);
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case YI_YAN:
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// TODO @xin:貌似 model 只要一设置,就报错;可以排查下
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// return QianFanChatOptions.builder().withModel(model).withTemperature(temperatureF).withMaxTokens(maxTokens).build();
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return QianFanChatOptions.builder().withTemperature(temperatureF).withMaxTokens(maxTokens).build();
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case XING_HUO:
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return new XingHuoOptions().setChatModel(XingHuoChatModel.valueOfModel(model)).setTemperature(temperatureF)
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.setMaxTokens(maxTokens);
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case QIAN_WEN:
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return TongYiChatOptions.builder().withModel(model).withTemperature(temperature).withMaxTokens(maxTokens).build();
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default:
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throw new IllegalArgumentException(StrUtil.format("未知平台({})", platform));
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}
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}
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public static Message buildMessage(String type, String content) {
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if (MessageType.USER.getValue().equals(type)) {
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return new UserMessage(content);
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}
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if (MessageType.ASSISTANT.getValue().equals(type)) {
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return new AssistantMessage(content);
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}
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if (MessageType.SYSTEM.getValue().equals(type)) {
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return new SystemMessage(content);
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}
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if (MessageType.FUNCTION.getValue().equals(type)) {
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return new FunctionMessage(content);
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}
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throw new IllegalArgumentException(StrUtil.format("未知消息类型({})", type));
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}
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}
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