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perf: 收敛后端资源与健康检查开销

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- 缩小模块扫描范围并显式注册各业务模块自动配置

- 增加可配置线程池、MQ 连接池与消费线程池，降低默认资源占用

- 将 RAG 与分析库中间件探活下沉到健康检查并增加短缓存

- 补齐文档向量库生命周期释放与 SSE 断连清理
This commit is contained in:
陈子默
2026-05-28 11:22:14 +08:00
parent 72df00f25b
commit 11e595b088
43 changed files with 1343 additions and 288 deletions
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65
easyflow-api/easyflow-api-admin/src/main/java/tech/easyflow/admin/controller/ai/DocumentChunkController.java
View File

@@ -9,6 +9,7 @@ import tech.easyflow.ai.entity.Model;
import tech.easyflow.ai.service.DocumentChunkService;
import tech.easyflow.ai.service.DocumentCollectionService;
import tech.easyflow.ai.service.ModelService;
import tech.easyflow.ai.support.DocumentStoreLifecycleSupport;
import tech.easyflow.common.annotation.UsePermission;
import tech.easyflow.common.domain.Result;
import tech.easyflow.common.web.controller.BaseCurdController;
@@ -93,22 +94,26 @@ public class DocumentChunkController extends BaseCurdController<DocumentChunkSer
if (documentStore == null) {
return Result.fail(2, "知识库没有配置向量库");
}
// 设置向量模型
Model model = modelService.getModelInstance(knowledge.getVectorEmbedModelId());
if (model == null) {
return Result.fail(3, "知识库没有配置向量模型");
try {
// 设置向量模型
Model model = modelService.getModelInstance(knowledge.getVectorEmbedModelId());
if (model == null) {
return Result.fail(3, "知识库没有配置向量模型");
}
EmbeddingModel embeddingModel = model.toEmbeddingModel();
documentStore.setEmbeddingModel(embeddingModel);
StoreOptions options = StoreOptions.ofCollectionName(knowledge.getVectorStoreCollection());
Document document = Document.of(documentChunk.getContent());
document.setId(documentChunk.getId());
Map<String, Object> metadata = new HashMap<>();
metadata.put("keywords", documentChunk.getMetadataKeyWords());
metadata.put("questions", documentChunk.getMetadataQuestions());
document.setMetadataMap(metadata);
StoreResult result = documentStore.update(document, options); // 更新已有记录
return Result.ok(result);
} finally {
DocumentStoreLifecycleSupport.closeQuietly(documentStore);
}
EmbeddingModel embeddingModel = model.toEmbeddingModel();
documentStore.setEmbeddingModel(embeddingModel);
StoreOptions options = StoreOptions.ofCollectionName(knowledge.getVectorStoreCollection());
Document document = Document.of(documentChunk.getContent());
document.setId(documentChunk.getId());
Map<String, Object> metadata = new HashMap<>();
metadata.put("keywords", documentChunk.getMetadataKeyWords());
metadata.put("questions", documentChunk.getMetadataQuestions());
document.setMetadataMap(metadata);
StoreResult result = documentStore.update(document, options); // 更新已有记录
return Result.ok(result);
}
return Result.ok(false);
}
@@ -135,19 +140,23 @@ public class DocumentChunkController extends BaseCurdController<DocumentChunkSer
if (documentStore == null) {
return Result.fail(3, "知识库没有配置向量库");
}
// 设置向量模型
Model model = modelService.getModelInstance(knowledge.getVectorEmbedModelId());
if (model == null) {
return Result.fail(4, "知识库没有配置向量模型");
}
EmbeddingModel embeddingModel = model.toEmbeddingModel();
documentStore.setEmbeddingModel(embeddingModel);
StoreOptions options = StoreOptions.ofCollectionName(knowledge.getVectorStoreCollection());
List<BigInteger> deleteList = new ArrayList<>();
deleteList.add(chunkId);
documentStore.delete(deleteList, options);
documentChunkService.removeChunk(knowledge, chunkId);
try {
// 设置向量模型
Model model = modelService.getModelInstance(knowledge.getVectorEmbedModelId());
if (model == null) {
return Result.fail(4, "知识库没有配置向量模型");
}
EmbeddingModel embeddingModel = model.toEmbeddingModel();
documentStore.setEmbeddingModel(embeddingModel);
StoreOptions options = StoreOptions.ofCollectionName(knowledge.getVectorStoreCollection());
List<BigInteger> deleteList = new ArrayList<>();
deleteList.add(chunkId);
documentStore.delete(deleteList, options);
documentChunkService.removeChunk(knowledge, chunkId);
return super.remove(chunkId);
return super.remove(chunkId);
} finally {
DocumentStoreLifecycleSupport.closeQuietly(documentStore);
}
}
}

53
easyflow-api/easyflow-api-admin/src/main/java/tech/easyflow/admin/controller/ai/ShareKnowledgeController.java
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@@ -42,6 +42,7 @@ import tech.easyflow.ai.service.KnowledgeEmbeddingService;
import tech.easyflow.ai.service.KnowledgeShareAuditService;
import tech.easyflow.ai.service.KnowledgeShareService;
import tech.easyflow.ai.service.ModelService;
import tech.easyflow.ai.support.DocumentStoreLifecycleSupport;
import tech.easyflow.ai.vo.FaqImportResultVo;
import tech.easyflow.ai.vo.KnowledgeShareAuthContext;
import tech.easyflow.ai.vo.KnowledgeShareViewDetail;
@@ -520,19 +521,23 @@ public class ShareKnowledgeController {
if (documentStore == null) {
return Result.fail(2, "知识库没有配置向量库");
}
Model model = modelService.getModelInstance(context.getKnowledge().getVectorEmbedModelId());
if (model == null) {
return Result.fail(3, "知识库没有配置向量模型");
try {
Model model = modelService.getModelInstance(context.getKnowledge().getVectorEmbedModelId());
if (model == null) {
return Result.fail(3, "知识库没有配置向量模型");
}
EmbeddingModel embeddingModel = model.toEmbeddingModel();
documentStore.setEmbeddingModel(embeddingModel);
StoreOptions options = StoreOptions.ofCollectionName(context.getKnowledge().getVectorStoreCollection());
com.easyagents.core.document.Document doc = com.easyagents.core.document.Document.of(documentChunk.getContent());
doc.setId(documentChunk.getId());
StoreResult result = documentStore.update(doc, options);
audit(context, "更新分享文档 Chunk", "KNOWLEDGE_SHARE_URL_WRITE", true,
auditDetail("knowledgeId", context.getKnowledge().getId(), "chunkId", documentChunk.getId()));
return Result.ok(result);
} finally {
DocumentStoreLifecycleSupport.closeQuietly(documentStore);
}
EmbeddingModel embeddingModel = model.toEmbeddingModel();
documentStore.setEmbeddingModel(embeddingModel);
StoreOptions options = StoreOptions.ofCollectionName(context.getKnowledge().getVectorStoreCollection());
com.easyagents.core.document.Document doc = com.easyagents.core.document.Document.of(documentChunk.getContent());
doc.setId(documentChunk.getId());
StoreResult result = documentStore.update(doc, options);
audit(context, "更新分享文档 Chunk", "KNOWLEDGE_SHARE_URL_WRITE", true,
auditDetail("knowledgeId", context.getKnowledge().getId(), "chunkId", documentChunk.getId()));
return Result.ok(result);
}
return Result.ok(false);
}
@@ -559,17 +564,21 @@ public class ShareKnowledgeController {
if (documentStore == null) {
return Result.fail(2, "知识库没有配置向量库");
}
Model model = modelService.getModelInstance(context.getKnowledge().getVectorEmbedModelId());
if (model == null) {
return Result.fail(3, "知识库没有配置向量模型");
try {
Model model = modelService.getModelInstance(context.getKnowledge().getVectorEmbedModelId());
if (model == null) {
return Result.fail(3, "知识库没有配置向量模型");
}
documentStore.setEmbeddingModel(model.toEmbeddingModel());
StoreOptions options = StoreOptions.ofCollectionName(context.getKnowledge().getVectorStoreCollection());
documentStore.delete(Collections.singletonList(chunkId), options);
documentChunkService.removeById(chunkId);
audit(context, "删除分享文档 Chunk", "KNOWLEDGE_SHARE_URL_WRITE", true,
auditDetail("knowledgeId", context.getKnowledge().getId(), "chunkId", chunkId));
return Result.ok(true);
} finally {
DocumentStoreLifecycleSupport.closeQuietly(documentStore);
}
documentStore.setEmbeddingModel(model.toEmbeddingModel());
StoreOptions options = StoreOptions.ofCollectionName(context.getKnowledge().getVectorStoreCollection());
documentStore.delete(Collections.singletonList(chunkId), options);
documentChunkService.removeById(chunkId);
audit(context, "删除分享文档 Chunk", "KNOWLEDGE_SHARE_URL_WRITE", true,
auditDetail("knowledgeId", context.getKnowledge().getId(), "chunkId", chunkId));
return Result.ok(true);
}
/**

49
easyflow-api/easyflow-api-public/src/main/java/tech/easyflow/publicapi/controller/PublicKnowledgeShareController.java
View File

@@ -36,6 +36,7 @@ import tech.easyflow.ai.service.KnowledgeShareAuditService;
import tech.easyflow.ai.service.KnowledgeSharePermissionService;
import tech.easyflow.ai.service.ModelService;
import tech.easyflow.ai.service.impl.KnowledgeSharePermissionServiceImpl;
import tech.easyflow.ai.support.DocumentStoreLifecycleSupport;
import tech.easyflow.ai.vo.FaqImportResultVo;
import tech.easyflow.common.domain.Result;
import tech.easyflow.common.filestorage.FileStorageService;
@@ -342,18 +343,22 @@ public class PublicKnowledgeShareController {
if (documentStore == null) {
return Result.fail(2, "知识库没有配置向量库");
}
Model model = modelService.getModelInstance(knowledge.getVectorEmbedModelId());
if (model == null) {
return Result.fail(3, "知识库没有配置向量模型");
try {
Model model = modelService.getModelInstance(knowledge.getVectorEmbedModelId());
if (model == null) {
return Result.fail(3, "知识库没有配置向量模型");
}
EmbeddingModel embeddingModel = model.toEmbeddingModel();
documentStore.setEmbeddingModel(embeddingModel);
StoreOptions options = StoreOptions.ofCollectionName(knowledge.getVectorStoreCollection());
com.easyagents.core.document.Document doc = com.easyagents.core.document.Document.of(documentChunk.getContent());
doc.setId(current.getId());
StoreResult result = documentStore.update(doc, options);
audit(apiKey, "API更新文档 Chunk", "KNOWLEDGE_API_SHARE_WRITE", request.getRequestURI(), Map.of("knowledgeId", knowledgeId, "chunkId", documentChunk.getId()));
return Result.ok(result);
} finally {
DocumentStoreLifecycleSupport.closeQuietly(documentStore);
}
EmbeddingModel embeddingModel = model.toEmbeddingModel();
documentStore.setEmbeddingModel(embeddingModel);
StoreOptions options = StoreOptions.ofCollectionName(knowledge.getVectorStoreCollection());
com.easyagents.core.document.Document doc = com.easyagents.core.document.Document.of(documentChunk.getContent());
doc.setId(current.getId());
StoreResult result = documentStore.update(doc, options);
audit(apiKey, "API更新文档 Chunk", "KNOWLEDGE_API_SHARE_WRITE", request.getRequestURI(), Map.of("knowledgeId", knowledgeId, "chunkId", documentChunk.getId()));
return Result.ok(result);
}
return Result.ok(false);
}
@@ -376,16 +381,20 @@ public class PublicKnowledgeShareController {
if (documentStore == null) {
return Result.fail(2, "知识库没有配置向量库");
}
Model model = modelService.getModelInstance(knowledge.getVectorEmbedModelId());
if (model == null) {
return Result.fail(3, "知识库没有配置向量模型");
try {
Model model = modelService.getModelInstance(knowledge.getVectorEmbedModelId());
if (model == null) {
return Result.fail(3, "知识库没有配置向量模型");
}
documentStore.setEmbeddingModel(model.toEmbeddingModel());
StoreOptions options = StoreOptions.ofCollectionName(knowledge.getVectorStoreCollection());
documentStore.delete(Collections.singletonList(chunkId), options);
documentChunkService.removeById(chunkId);
audit(apiKey, "API删除文档 Chunk", "KNOWLEDGE_API_SHARE_WRITE", request.getRequestURI(), Map.of("knowledgeId", knowledgeId, "chunkId", chunkId));
return Result.ok(true);
} finally {
DocumentStoreLifecycleSupport.closeQuietly(documentStore);
}
documentStore.setEmbeddingModel(model.toEmbeddingModel());
StoreOptions options = StoreOptions.ofCollectionName(knowledge.getVectorStoreCollection());
documentStore.delete(Collections.singletonList(chunkId), options);
documentChunkService.removeById(chunkId);
audit(apiKey, "API删除文档 Chunk", "KNOWLEDGE_API_SHARE_WRITE", request.getRequestURI(), Map.of("knowledgeId", knowledgeId, "chunkId", chunkId));
return Result.ok(true);
}
/**