Commit ea5b12f21e2c0eb3e9e833b12e1af3bfad0681f1

Authored by YunaiV
1 parent 39ecf5eb

fix:【AI 大模型】RedisVectorStore 支持 username、password

yudao-module-ai/src/main/java/cn/iocoder/yudao/module/ai/framework/ai/core/AiModelFactoryImpl.java
@@ -690,10 +690,9 @@ public class AiModelFactoryImpl implements AiModelFactory { @@ -690,10 +690,9 @@ public class AiModelFactoryImpl implements AiModelFactory {
690 Map<String, Class<?>> metadataFields) { 690 Map<String, Class<?>> metadataFields) {
691 // 创建 JedisPooled 对象 691 // 创建 JedisPooled 对象
692 RedisProperties redisProperties = SpringUtils.getBean(RedisProperties.class); 692 RedisProperties redisProperties = SpringUtils.getBean(RedisProperties.class);
693 - JedisPooled jedisPooled = new JedisPooled(redisProperties.getHost(), redisProperties.getPort()); 693 + JedisPooled jedisPooled = new JedisPooled(redisProperties.getHost(), redisProperties.getPort(),
  694 + redisProperties.getUsername(), redisProperties.getPassword());
694 // 创建 RedisVectorStoreProperties 对象 695 // 创建 RedisVectorStoreProperties 对象
695 - // TODO @芋艿:index-name 可能影响索引名;  
696 - RedisVectorStoreAutoConfiguration configuration = new RedisVectorStoreAutoConfiguration();  
697 RedisVectorStoreProperties properties = SpringUtil.getBean(RedisVectorStoreProperties.class); 696 RedisVectorStoreProperties properties = SpringUtil.getBean(RedisVectorStoreProperties.class);
698 RedisVectorStore redisVectorStore = RedisVectorStore.builder(jedisPooled, embeddingModel) 697 RedisVectorStore redisVectorStore = RedisVectorStore.builder(jedisPooled, embeddingModel)
699 .indexName(properties.getIndexName()).prefix(properties.getPrefix()) 698 .indexName(properties.getIndexName()).prefix(properties.getPrefix())
yudao-server/src/main/resources/application.yaml
@@ -150,7 +150,7 @@ spring: @@ -150,7 +150,7 @@ spring:
150 vectorstore: # 向量存储 150 vectorstore: # 向量存储
151 redis: 151 redis:
152 initialize-schema: true 152 initialize-schema: true
153 - index: knowledge_index # Redis 中向量索引的名称:用于存储和检索向量数据的索引标识符,所有相关的向量搜索操作都会基于这个索引进行 153 + index-name: knowledge_index # Redis 中向量索引的名称:用于存储和检索向量数据的索引标识符,所有相关的向量搜索操作都会基于这个索引进行
154 prefix: "knowledge_segment:" # Redis 中存储向量数据的键名前缀:这个前缀会添加到每个存储在 Redis 中的向量数据键名前,每个 document 都是一个 hash 结构 154 prefix: "knowledge_segment:" # Redis 中存储向量数据的键名前缀:这个前缀会添加到每个存储在 Redis 中的向量数据键名前,每个 document 都是一个 hash 结构
155 qdrant: 155 qdrant:
156 initialize-schema: true 156 initialize-schema: true