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【新增】AI 知识库:支持读取 PDF、DOC/DOCX、PPT/PPTX 和 HTML等格式
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@ -10,11 +10,18 @@ import cn.iocoder.yudao.framework.ai.core.model.xinghuo.XingHuoChatModel;
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import cn.iocoder.yudao.framework.ai.core.model.xinghuo.XingHuoChatOptions;
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import com.alibaba.cloud.ai.tongyi.TongYiAutoConfiguration;
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import lombok.extern.slf4j.Slf4j;
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import org.springframework.ai.autoconfigure.vectorstore.redis.RedisVectorStoreProperties;
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import org.springframework.ai.document.MetadataMode;
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import org.springframework.ai.transformer.splitter.TokenTextSplitter;
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import org.springframework.ai.transformers.TransformersEmbeddingModel;
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import org.springframework.ai.vectorstore.RedisVectorStore;
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import org.springframework.boot.autoconfigure.AutoConfiguration;
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import org.springframework.boot.autoconfigure.condition.ConditionalOnProperty;
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import org.springframework.boot.autoconfigure.data.redis.RedisProperties;
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import org.springframework.boot.context.properties.EnableConfigurationProperties;
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import org.springframework.context.annotation.Bean;
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import org.springframework.context.annotation.Import;
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import redis.clients.jedis.JedisPooled;
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/**
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* 芋道 AI 自动配置
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@ -73,4 +80,33 @@ public class YudaoAiAutoConfiguration {
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return new SunoApi(yudaoAiProperties.getSuno().getBaseUrl());
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}
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// ========== rag 相关 ==========
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@Bean
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public TransformersEmbeddingModel transformersEmbeddingClient() {
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return new TransformersEmbeddingModel(MetadataMode.EMBED);
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}
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/**
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* 我们启动有加载很多 Embedding 模型,不晓得取哪个好,先 new 个 TransformersEmbeddingModel 跑
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*/
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@Bean
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public RedisVectorStore vectorStore(TransformersEmbeddingModel transformersEmbeddingModel, RedisVectorStoreProperties properties,
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RedisProperties redisProperties) {
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var config = RedisVectorStore.RedisVectorStoreConfig.builder()
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.withIndexName(properties.getIndex())
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.withPrefix(properties.getPrefix())
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.build();
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RedisVectorStore redisVectorStore = new RedisVectorStore(config, transformersEmbeddingModel,
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new JedisPooled(redisProperties.getHost(), redisProperties.getPort()),
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properties.isInitializeSchema());
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redisVectorStore.afterPropertiesSet();
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return redisVectorStore;
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}
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@Bean
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public TokenTextSplitter tokenTextSplitter() {
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return new TokenTextSplitter(500, 100, 5, 10000, true);
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}
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}
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