From 9bad721754fe8bbe2e5f459d0706e0fefac569f3 Mon Sep 17 00:00:00 2001
From: 云 <2163098428@qq.com>
Date: 星期日, 20 九月 2026 09:05:41 +0800
Subject: [PATCH] feat(mes): 添加智能质检报告功能与AI导入能力
---
yudao-module-ai/src/main/java/cn/iocoder/yudao/module/ai/framework/ai/core/model/AiModelFactoryImpl.java | 34 ++++++++++++++++++----------------
1 files changed, 18 insertions(+), 16 deletions(-)
diff --git a/yudao-module-ai/src/main/java/cn/iocoder/yudao/module/ai/framework/ai/core/model/AiModelFactoryImpl.java b/yudao-module-ai/src/main/java/cn/iocoder/yudao/module/ai/framework/ai/core/model/AiModelFactoryImpl.java
index 86b307a..d004349 100644
--- a/yudao-module-ai/src/main/java/cn/iocoder/yudao/module/ai/framework/ai/core/model/AiModelFactoryImpl.java
+++ b/yudao-module-ai/src/main/java/cn/iocoder/yudao/module/ai/framework/ai/core/model/AiModelFactoryImpl.java
@@ -7,32 +7,35 @@
import cn.hutool.extra.spring.SpringUtil;
import cn.iocoder.yudao.module.ai.enums.model.AiPlatformEnum;
import cn.iocoder.yudao.module.ai.framework.ai.config.AiAutoConfiguration;
+import cn.iocoder.yudao.module.ai.framework.ai.config.YudaoAiProperties;
import lombok.extern.slf4j.Slf4j;
import org.springframework.ai.chat.model.ChatModel;
-import org.springframework.ai.embedding.BatchingStrategy;
import org.springframework.ai.embedding.EmbeddingModel;
import org.springframework.ai.embedding.TokenCountBatchingStrategy;
import org.springframework.ai.openai.OpenAiChatModel;
import org.springframework.ai.vectorstore.VectorStore;
import org.springframework.ai.vectorstore.milvus.MilvusVectorStore;
-import org.springframework.ai.vectorstore.milvus.autoconfigure.MilvusServiceClientProperties;
-import org.springframework.ai.vectorstore.milvus.autoconfigure.MilvusVectorStoreProperties;
+import java.time.Duration;
import java.util.Map;
/**
* AI Model 妯″瀷宸ュ巶瀹炵幇绫�
*
- * 浣跨敤 OpenAI 鍏煎鎺ュ彛瀵规帴閫氫箟鍗冮棶 + Milvus 鍚戦噺瀛樺偍
+ * 浣跨敤 OpenAI 鍏煎鎺ュ彛瀵规帴閫氫箟鍗冮棶 + 鍙厤缃悜閲忓瓨鍌紙Milvus锛�
*/
@Slf4j
public class AiModelFactoryImpl implements AiModelFactory {
@Override
- public ChatModel getOrCreateChatModel(AiPlatformEnum platform, String apiKey, String url, String model) {
- String cacheKey = buildCacheKey(ChatModel.class, platform, apiKey, url, model);
+ public ChatModel getOrCreateChatModel(AiPlatformEnum platform, String apiKey, String url, String model,
+ Double temperature, Integer maxTokens, Duration timeout) {
+ // 娓╁害 / maxTokens / 瓒呮椂蹇呴』涓�璧疯繘 cacheKey锛氬惁鍒欏湪搴撻噷鏀逛簡杩欎簺鍙傛暟鍚庯紝
+ // 缂撳瓨浠嶇劧杩斿洖绗竴娆℃瀯寤虹殑妯″瀷锛屾敼浜嗙瓑浜庢病鏀癸紙涓斿畬鍏ㄩ潤榛橈級
+ String cacheKey = buildCacheKey(ChatModel.class, platform, apiKey, url, model,
+ temperature, maxTokens, timeout);
return Singleton.get(cacheKey, (Func0<ChatModel>) () -> {
if (platform == AiPlatformEnum.TONG_YI) {
- return AiAutoConfiguration.buildTongYiChatModel(apiKey, model);
+ return AiAutoConfiguration.buildTongYiChatModel(apiKey, model, temperature, maxTokens, timeout);
}
throw new IllegalArgumentException(StrUtil.format("涓嶆敮鎸佺殑骞冲彴({})", platform));
});
@@ -61,7 +64,6 @@
public VectorStore getOrCreateVectorStore(Class<? extends VectorStore> type,
EmbeddingModel embeddingModel,
Map<String, Class<?>> metadataFields) {
- // metadataFields 鍙備笌缂撳瓨 key锛岀‘淇濅笉鍚岀煡璇嗗簱浣跨敤涓嶅悓閰嶇疆鏃朵笉浼氬鐢�
String cacheKey = buildCacheKey(VectorStore.class, embeddingModel, type, metadataFields.hashCode());
return Singleton.get(cacheKey, (Func0<VectorStore>) () -> {
if (type == MilvusVectorStore.class) {
@@ -72,20 +74,20 @@
}
private MilvusVectorStore buildMilvusVectorStore(EmbeddingModel embeddingModel) {
- MilvusVectorStoreProperties serverProperties = SpringUtil.getBean(MilvusVectorStoreProperties.class);
- MilvusServiceClientProperties clientProperties = SpringUtil.getBean(MilvusServiceClientProperties.class);
+ YudaoAiProperties aiProperties = SpringUtil.getBean(YudaoAiProperties.class);
+ YudaoAiProperties.VectorStore.Milvus milvusConfig = aiProperties.getVectorStore().getMilvus();
var connectParam = io.milvus.param.ConnectParam.newBuilder()
- .withHost(clientProperties.getHost())
- .withPort(clientProperties.getPort())
- .withDatabaseName(serverProperties.getDatabaseName())
+ .withHost(milvusConfig.getHost())
+ .withPort(milvusConfig.getPort())
+ .withDatabaseName(milvusConfig.getDatabaseName())
.build();
var milvusClient = new io.milvus.client.MilvusServiceClient(connectParam);
MilvusVectorStore vectorStore = MilvusVectorStore.builder(milvusClient, embeddingModel)
- .databaseName(serverProperties.getDatabaseName())
- .collectionName(serverProperties.getCollectionName())
- .initializeSchema(serverProperties.isInitializeSchema())
+ .databaseName(milvusConfig.getDatabaseName())
+ .collectionName(milvusConfig.getCollectionName())
+ .initializeSchema(milvusConfig.isInitializeSchema())
.batchingStrategy(new TokenCountBatchingStrategy())
.build();
try {
--
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