package cn.iocoder.yudao.module.ai.framework.ai.config;
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import cn.hutool.core.util.StrUtil;
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import cn.iocoder.yudao.module.ai.framework.ai.core.model.AiModelFactory;
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import cn.iocoder.yudao.module.ai.framework.ai.core.model.AiModelFactoryImpl;
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import io.micrometer.observation.ObservationRegistry;
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import lombok.extern.slf4j.Slf4j;
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import org.springframework.ai.document.MetadataMode;
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import org.springframework.ai.embedding.BatchingStrategy;
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import org.springframework.ai.embedding.TokenCountBatchingStrategy;
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import org.springframework.ai.model.tool.ToolCallingManager;
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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.OpenAiEmbeddingModel;
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import org.springframework.ai.openai.OpenAiEmbeddingOptions;
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import org.springframework.ai.tokenizer.JTokkitTokenCountEstimator;
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import org.springframework.ai.tokenizer.TokenCountEstimator;
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import org.springframework.boot.autoconfigure.condition.ConditionalOnMissingBean;
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import org.springframework.context.annotation.Bean;
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import org.springframework.context.annotation.Configuration;
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import org.springframework.boot.context.properties.EnableConfigurationProperties;
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import java.time.Duration;
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/**
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* 超级管理员 AI 自动配置
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*
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* 使用 OpenAI 兼容接口对接通义千问 DashScope
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* 向量库配置见 yudao.ai.vector-store 节点，不再依赖 Spring AI 的 Milvus 自动配置属性
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*/
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@Configuration
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@EnableConfigurationProperties(YudaoAiProperties.class)
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@Slf4j
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public class AiAutoConfiguration {
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private static final String DASHSCOPE_BASE_URL = "https://dashscope.aliyuncs.com/compatible-mode/v1";
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@Bean
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public AiModelFactory aiModelFactory() {
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return new AiModelFactoryImpl();
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}
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@Bean
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@ConditionalOnMissingBean
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public ObservationRegistry observationRegistry() {
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return ObservationRegistry.NOOP;
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}
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@Bean
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@ConditionalOnMissingBean
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public BatchingStrategy batchingStrategy() {
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return new TokenCountBatchingStrategy();
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}
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@Bean
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@ConditionalOnMissingBean
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public TokenCountEstimator tokenCountEstimator() {
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return new JTokkitTokenCountEstimator();
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}
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// ========== 通义千问 Chat（通过 OpenAI 兼容接口）==========
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/**
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* 构建通义千问 Chat 模型
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*
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* @param temperature 采样温度，为 null 时用 0.7（与历史行为一致）
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* @param maxTokens 单次回复的最大 token 数，为 null 时沿用模型默认值。
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* 不传会让长文档的输出被静默截断，表现为「JSON 尾部缺失、解析失败」
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* @param timeout 单次调用超时。不设超时的话，模型排队时请求会一直挂到 TCP 层超时
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*/
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public static OpenAiChatModel buildTongYiChatModel(String apiKey, String model,
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Double temperature, Integer maxTokens,
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Duration timeout) {
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return OpenAiChatModel.builder()
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.options(OpenAiChatOptions.builder()
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.baseUrl(DASHSCOPE_BASE_URL)
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.apiKey(apiKey)
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.model(StrUtil.blankToDefault(model, "qwen-plus"))
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.temperature(temperature != null ? temperature : 0.7)
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.maxTokens(maxTokens)
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.timeout(timeout)
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.build())
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.toolCallingManager(ToolCallingManager.builder().build())
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.build();
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}
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// ========== 通义千问 Embedding（通过 OpenAI 兼容接口）==========
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public static OpenAiEmbeddingModel buildTongYiEmbeddingModel(String apiKey, String model) {
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return OpenAiEmbeddingModel.builder()
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.options(OpenAiEmbeddingOptions.builder()
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.baseUrl(DASHSCOPE_BASE_URL)
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.apiKey(apiKey)
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.model(StrUtil.blankToDefault(model, "text-embedding-v3"))
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.build())
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.metadataMode(MetadataMode.EMBED)
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.build();
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}
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}
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