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

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YunaiV 2025-07-14 22:44:50 +08:00
parent 39ecf5ebe5
commit ea5b12f21e
2 changed files with 3 additions and 4 deletions
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5
yudao-module-ai/src/main/java/cn/iocoder/yudao/module/ai/framework/ai/core/AiModelFactoryImpl.java
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@ -690,10 +690,9 @@ public class AiModelFactoryImpl implements AiModelFactory {
Map<String, Class<?>> metadataFields) { Map<String, Class<?>> metadataFields) {
// 创建 JedisPooled 对象 // 创建 JedisPooled 对象
RedisProperties redisProperties = SpringUtils.getBean(RedisProperties.class); RedisProperties redisProperties = SpringUtils.getBean(RedisProperties.class);
JedisPooled jedisPooled = new JedisPooled(redisProperties.getHost(), redisProperties.getPort()); JedisPooled jedisPooled = new JedisPooled(redisProperties.getHost(), redisProperties.getPort(),
redisProperties.getUsername(), redisProperties.getPassword());
// 创建 RedisVectorStoreProperties 对象 // 创建 RedisVectorStoreProperties 对象
// TODO @芋艿：index-name 可能影响索引名；
RedisVectorStoreAutoConfiguration configuration = new RedisVectorStoreAutoConfiguration();
RedisVectorStoreProperties properties = SpringUtil.getBean(RedisVectorStoreProperties.class); RedisVectorStoreProperties properties = SpringUtil.getBean(RedisVectorStoreProperties.class);
RedisVectorStore redisVectorStore = RedisVectorStore.builder(jedisPooled, embeddingModel) RedisVectorStore redisVectorStore = RedisVectorStore.builder(jedisPooled, embeddingModel)
.indexName(properties.getIndexName()).prefix(properties.getPrefix()) .indexName(properties.getIndexName()).prefix(properties.getPrefix())

2
yudao-server/src/main/resources/application.yaml
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@ -150,7 +150,7 @@ spring:
vectorstore: # 向量存储 vectorstore: # 向量存储
redis: redis:
initialize-schema: true initialize-schema: true
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 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
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 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
qdrant: qdrant:
initialize-schema: true initialize-schema: true