【功能新增】AI:百川模型的接入
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@ -4,6 +4,7 @@ import cn.hutool.core.util.StrUtil;
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import cn.hutool.extra.spring.SpringUtil;
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import cn.iocoder.yudao.framework.ai.core.factory.AiModelFactory;
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import cn.iocoder.yudao.framework.ai.core.factory.AiModelFactoryImpl;
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import cn.iocoder.yudao.framework.ai.core.model.baichuan.BaiChuanChatModel;
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import cn.iocoder.yudao.framework.ai.core.model.deepseek.DeepSeekChatModel;
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import cn.iocoder.yudao.framework.ai.core.model.doubao.DouBaoChatModel;
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import cn.iocoder.yudao.framework.ai.core.model.hunyuan.HunYuanChatModel;
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@ -193,6 +194,33 @@ public class YudaoAiAutoConfiguration {
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return new XingHuoChatModel(openAiChatModel);
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}
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@Bean
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@ConditionalOnProperty(value = "yudao.ai.baichuan.enable", havingValue = "true")
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public BaiChuanChatModel baiChuanChatClient(YudaoAiProperties yudaoAiProperties) {
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YudaoAiProperties.BaiChuanProperties properties = yudaoAiProperties.getBaichuan();
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return buildBaiChuanChatClient(properties);
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}
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public BaiChuanChatModel buildBaiChuanChatClient(YudaoAiProperties.BaiChuanProperties properties) {
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if (StrUtil.isEmpty(properties.getModel())) {
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properties.setModel(BaiChuanChatModel.MODEL_DEFAULT);
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}
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OpenAiChatModel openAiChatModel = OpenAiChatModel.builder()
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.openAiApi(OpenAiApi.builder()
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.baseUrl(BaiChuanChatModel.BASE_URL)
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.apiKey(properties.getApiKey())
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.build())
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.defaultOptions(OpenAiChatOptions.builder()
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.model(properties.getModel())
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.temperature(properties.getTemperature())
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.maxTokens(properties.getMaxTokens())
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.topP(properties.getTopP())
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.build())
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.toolCallingManager(getToolCallingManager())
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.build();
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return new BaiChuanChatModel(openAiChatModel);
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}
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@Bean
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@ConditionalOnProperty(value = "yudao.ai.midjourney.enable", havingValue = "true")
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public MidjourneyApi midjourneyApi(YudaoAiProperties yudaoAiProperties) {
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@ -43,6 +43,12 @@ public class YudaoAiProperties {
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@SuppressWarnings("SpellCheckingInspection")
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private XingHuoProperties xinghuo;
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/**
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* 百川
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*/
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@SuppressWarnings("SpellCheckingInspection")
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private BaiChuanProperties baichuan;
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/**
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* Midjourney 绘图
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*/
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@ -122,6 +128,19 @@ public class YudaoAiProperties {
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}
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@Data
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public static class BaiChuanProperties {
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private String enable;
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private String apiKey;
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private String model;
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private Double temperature;
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private Integer maxTokens;
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private Double topP;
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}
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@Data
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public static class MidjourneyProperties {
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@ -27,6 +27,7 @@ public enum AiPlatformEnum implements ArrayValuable<String> {
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SILICON_FLOW("SiliconFlow", "硅基流动"), // 硅基流动
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MINI_MAX("MiniMax", "MiniMax"), // 稀宇科技
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MOONSHOT("Moonshot", "月之暗灭"), // KIMI
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BAI_CHUAN("BaiChuan", "百川智能"), // 百川智能
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// ========== 国外平台 ==========
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@ -11,6 +11,7 @@ import cn.hutool.extra.spring.SpringUtil;
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import cn.iocoder.yudao.framework.ai.config.YudaoAiAutoConfiguration;
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import cn.iocoder.yudao.framework.ai.config.YudaoAiProperties;
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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.baichuan.BaiChuanChatModel;
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import cn.iocoder.yudao.framework.ai.core.model.deepseek.DeepSeekChatModel;
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import cn.iocoder.yudao.framework.ai.core.model.doubao.DouBaoChatModel;
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import cn.iocoder.yudao.framework.ai.core.model.hunyuan.HunYuanChatModel;
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@ -150,6 +151,8 @@ public class AiModelFactoryImpl implements AiModelFactory {
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return buildMoonshotChatModel(apiKey, url);
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case XING_HUO:
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return buildXingHuoChatModel(apiKey);
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case BAI_CHUAN:
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return buildBaiChuanChatModel(apiKey);
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case OPENAI:
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return buildOpenAiChatModel(apiKey, url);
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case AZURE_OPENAI:
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@ -186,6 +189,8 @@ public class AiModelFactoryImpl implements AiModelFactory {
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return SpringUtil.getBean(MoonshotChatModel.class);
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case XING_HUO:
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return SpringUtil.getBean(XingHuoChatModel.class);
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case BAI_CHUAN:
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return SpringUtil.getBean(AzureOpenAiChatModel.class);
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case OPENAI:
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return SpringUtil.getBean(OpenAiChatModel.class);
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case AZURE_OPENAI:
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@ -441,6 +446,15 @@ public class AiModelFactoryImpl implements AiModelFactory {
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return new YudaoAiAutoConfiguration().buildXingHuoChatClient(properties);
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}
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/**
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* 可参考 {@link YudaoAiAutoConfiguration#baiChuanChatClient(YudaoAiProperties)}
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*/
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private BaiChuanChatModel buildBaiChuanChatModel(String apiKey) {
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YudaoAiProperties.BaiChuanProperties properties = new YudaoAiProperties.BaiChuanProperties()
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.setApiKey(apiKey);
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return new YudaoAiAutoConfiguration().buildBaiChuanChatClient(properties);
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}
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/**
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* 可参考 {@link OpenAiAutoConfiguration} 的 openAiChatModel 方法
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*/
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@ -0,0 +1,45 @@
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package cn.iocoder.yudao.framework.ai.core.model.baichuan;
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import lombok.RequiredArgsConstructor;
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import lombok.extern.slf4j.Slf4j;
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import org.springframework.ai.chat.model.ChatModel;
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import org.springframework.ai.chat.model.ChatResponse;
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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.openai.OpenAiChatModel;
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import reactor.core.publisher.Flux;
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/**
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* 百川 {@link ChatModel} 实现类
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*
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* @author 芋道源码
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*/
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@Slf4j
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@RequiredArgsConstructor
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public class BaiChuanChatModel implements ChatModel {
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public static final String BASE_URL = "https://api.baichuan-ai.com";
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public static final String MODEL_DEFAULT = "Baichuan4-Turbo";
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/**
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* 兼容 OpenAI 接口,进行复用
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*/
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private final OpenAiChatModel openAiChatModel;
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@Override
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public ChatResponse call(Prompt prompt) {
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return openAiChatModel.call(prompt);
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}
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@Override
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public Flux<ChatResponse> stream(Prompt prompt) {
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return openAiChatModel.stream(prompt);
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}
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@Override
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public ChatOptions getDefaultOptions() {
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return openAiChatModel.getDefaultOptions();
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}
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}
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@ -149,7 +149,7 @@ public class SiliconFlowImageModel implements ImageModel {
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.batchSize(ModelOptionsUtils.mergeOption(runtimeOptionsForProvider.getN(), defaultOptions.getN()))
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.width(ModelOptionsUtils.mergeOption(runtimeOptionsForProvider.getWidth(), defaultOptions.getWidth()))
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.height(ModelOptionsUtils.mergeOption(runtimeOptionsForProvider.getHeight(), defaultOptions.getHeight()))
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// Handle OpenAI specific image options
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// Handle SiliconFlow specific image options
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.negativePrompt(ModelOptionsUtils.mergeOption(runtimeOptionsForProvider.getNegativePrompt(), defaultOptions.getNegativePrompt()))
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.numInferenceSteps(ModelOptionsUtils.mergeOption(runtimeOptionsForProvider.getNumInferenceSteps(), defaultOptions.getNumInferenceSteps()))
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.guidanceScale(ModelOptionsUtils.mergeOption(runtimeOptionsForProvider.getGuidanceScale(), defaultOptions.getGuidanceScale()))
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@ -50,6 +50,7 @@ public class AiUtils {
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case HUN_YUAN: // 复用 OpenAI 客户端
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case XING_HUO: // 复用 OpenAI 客户端
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case SILICON_FLOW: // 复用 OpenAI 客户端
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case BAI_CHUAN: // 复用 OpenAI 客户端
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return OpenAiChatOptions.builder().model(model).temperature(temperature).maxTokens(maxTokens)
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.toolNames(toolNames).build();
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case AZURE_OPENAI:
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@ -0,0 +1,68 @@
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package cn.iocoder.yudao.framework.ai.chat;
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import cn.iocoder.yudao.framework.ai.core.model.baichuan.BaiChuanChatModel;
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import cn.iocoder.yudao.framework.ai.core.model.deepseek.DeepSeekChatModel;
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import org.junit.jupiter.api.Disabled;
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import org.junit.jupiter.api.Test;
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import org.springframework.ai.chat.messages.Message;
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import org.springframework.ai.chat.messages.SystemMessage;
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import org.springframework.ai.chat.messages.UserMessage;
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import org.springframework.ai.chat.model.ChatResponse;
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import org.springframework.ai.chat.prompt.Prompt;
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import org.springframework.ai.openai.OpenAiChatModel;
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import org.springframework.ai.openai.OpenAiChatOptions;
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import org.springframework.ai.openai.api.OpenAiApi;
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import reactor.core.publisher.Flux;
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import java.util.ArrayList;
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import java.util.List;
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/**
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* {@link BaiChuanChatModel} 集成测试
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*
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* @author 芋道源码
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*/
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public class BaiChuanChatModelTests {
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private final OpenAiChatModel openAiChatModel = OpenAiChatModel.builder()
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.openAiApi(OpenAiApi.builder()
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.baseUrl(BaiChuanChatModel.BASE_URL)
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.apiKey("sk-61b6766a94c70786ed02673f5e16af3c") // apiKey
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.build())
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.defaultOptions(OpenAiChatOptions.builder()
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.model("Baichuan4-Turbo") // 模型(https://platform.baichuan-ai.com/docs/api)
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.temperature(0.7)
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.build())
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.build();
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private final DeepSeekChatModel chatModel = new DeepSeekChatModel(openAiChatModel);
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@Test
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@Disabled
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public void testCall() {
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// 准备参数
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List<Message> messages = new ArrayList<>();
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messages.add(new SystemMessage("你是一个优质的文言文作者,用文言文描述着各城市的人文风景。"));
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messages.add(new UserMessage("1 + 1 = ?"));
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// 调用
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ChatResponse response = chatModel.call(new Prompt(messages));
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// 打印结果
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System.out.println(response);
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}
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@Test
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@Disabled
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public void testStream() {
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// 准备参数
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List<Message> messages = new ArrayList<>();
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messages.add(new SystemMessage("你是一个优质的文言文作者,用文言文描述着各城市的人文风景。"));
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messages.add(new UserMessage("1 + 1 = ?"));
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// 调用
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Flux<ChatResponse> flux = chatModel.stream(new Prompt(messages));
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// 打印结果
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flux.doOnNext(System.out::println).then().block();
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}
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}
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