fix: 修复重试计数、误报反馈、响应式阻塞等问题，版本号更新为v1.2.1
修复 AiReplyOrchestrator.retryOrFail 使用 .then() 导致 retryCount 失效；修复误报反馈端点 .subscribe() 过早触发覆盖 AI 回复；修复 PersonaResolver 在响应式上下文使用 .block() 阻塞线程；修复 penalize/approveOriginalComment 缺少乐观锁重试；修复误报反馈端点无法重试 FAIL 状态；修复 tag-NEUTRAL 缺少样式、handleTriggerAiReply 缺少加载保护；修复 filterKeyword 未做防抖、performCleanup 逻辑错误；优化 extractChoice 优先匹配违规类别避免误判
This commit is contained in:
sunny-335
@@ -1,5 +1,28 @@
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# 更新日志
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## v1.2.1
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> 2026-07-01
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### Bug 修复
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- **修复 `AiReplyOrchestrator.retryOrFail` 重试计数失效** — `.then()` 丢弃了更新后的记录导致 `retryCount` 始终为 0，AI 生成失败时陷入无限重试。改为 `.flatMap()` 传递更新后的记录
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- **修复误报反馈"AI 回复"被空字符串覆盖** — `.subscribe()` 在异步流程中过早触发，导致 AI 回复生成完成后被空字符串覆盖。改为在 `.doOnSuccess()` 中触发异步生成
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- **修复 `PersonaResolver` 在响应式上下文中使用 `.block()`** — 调用阻塞方法会阻塞 Reactor 线程。改为返回 `Mono<String>` 并使用 `Flux.concatMap().next()` 替代 for 循环
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- **修复 `penalizeComment`/`penalizeReply` 缺少乐观锁重试** — 并发更新 Comment/Reply 时可能静默失败。添加 `Retry.backoff(3, 100ms)` 重试
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- **修复 `approveOriginalComment` 缺少乐观锁重试** — 同上，添加 `Retry.backoff(3, 100ms)` 重试
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- **修复误报反馈端点无法重试 `FAIL` 状态记录** — 仅接受 `FILTERED` 和 `FALSE_POSITIVE` 状态，AI 生成失败的记录无法重试。现接受 `FAIL` 状态
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- **修复 `tag-NEUTRAL` 缺少 CSS 样式** — 中性情感标签无样式显示。补充样式定义
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- **修复 `handleTriggerAiReply` 缺少加载保护** — 触发 AI 回复按钮可被重复点击导致重复提交。添加 loading 状态
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- **修复 `filterKeyword` 输入未做防抖** — 每次按键都触发搜索，性能开销大。添加 300ms 防抖
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- **修复 `performCleanup` 逻辑错误** — 清理逻辑存在判断错误
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### 改进
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- **优化 `extractChoice` 分类匹配优先级** — 优先匹配违规类别（advertising/abuse/sensitive/meaningless），再匹配 `normal`，避免正常评论被误判为违规类别
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---
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## v1.2.0
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> 2026-06-25
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+1
-1
@@ -1,4 +1,4 @@
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version=1.2.0
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version=1.2.1
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# Fix Windows Gradle Worker Daemon exit code 268435659 when running pnpm via Exec tasks
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org.gradle.daemon=false
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+22
-17
@@ -1060,10 +1060,13 @@ public class CommentAiAutopilotEndpoint implements CustomEndpoint {
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return client.fetch(AiCommentReply.class, name)
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.flatMap(record -> {
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if (!"FILTERED".equals(record.getSpec().getStatus())
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&& !"FALSE_POSITIVE".equals(record.getSpec().getStatus())) {
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String currentStatus = record.getSpec().getStatus();
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// 允许：FILTERED（拦截误报）、FALSE_POSITIVE（已通过但可触发AI）、FAIL（AI生成失败可重试）
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if (!"FILTERED".equals(currentStatus)
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&& !"FALSE_POSITIVE".equals(currentStatus)
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&& !"FAIL".equals(currentStatus)) {
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return ServerResponse.badRequest()
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.bodyValue(Map.of("message", "仅已拦截或误报通过状态的记录可进行误报反馈"));
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.bodyValue(Map.of("message", "仅已拦截、误报通过或AI生成失败的记录可进行此操作"));
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}
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String commentName = record.getSpec().getCommentId();
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@@ -1092,24 +1095,26 @@ public class CommentAiAutopilotEndpoint implements CustomEndpoint {
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.filter(e -> e instanceof OptimisticLockingFailureException))
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.then());
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// 3. 异步触发 AI 回复（不阻塞 HTTP 响应）
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// 3. 异步触发 AI 回复（在记录更新完成后，不阻塞 HTTP 响应）
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// 使用 processFalsePositive 跳过前置过滤和去重检查
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if ("aiReply".equals(action)) {
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boolean isConversation = Boolean.TRUE.equals(record.getSpec().getIsAiConversation());
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String recordName = record.getMetadata().getName();
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personaResolver.getPersonaNameFromComment(commentName)
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.flatMap(personaName ->
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orchestrator.processFalsePositive(commentName, replyName, isConversation, personaName, recordName)
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)
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.subscribe(
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null,
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err -> log.warn("[FalsePositive] AI reply trigger failed for {}: {}", commentName, err.getMessage()),
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() -> log.info("[FalsePositive] AI reply trigger completed for {}", commentName)
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);
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}
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final boolean isConversation = Boolean.TRUE.equals(record.getSpec().getIsAiConversation());
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final String recordName = record.getMetadata().getName();
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return approveMono
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.then(updateRecordMono)
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.doOnSuccess(v -> {
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if ("aiReply".equals(action)) {
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personaResolver.getPersonaNameFromComment(commentName)
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.flatMap(personaName ->
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orchestrator.processFalsePositive(commentName, replyName, isConversation, personaName, recordName)
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)
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.subscribe(
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null,
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err -> log.warn("[FalsePositive] AI reply trigger failed for {}: {}", commentName, err.getMessage()),
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() -> log.info("[FalsePositive] AI reply trigger completed for {}", commentName)
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);
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}
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})
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.then(ServerResponse.ok().bodyValue(Map.of(
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"message", "aiReply".equals(action) ? "已标记为误报，AI回复正在后台生成" : "已标记为误报并通过"
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)));
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@@ -127,6 +127,8 @@ class AiFoundationDelegate {
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/**
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* 从 chat 响应文本中提取匹配的分类值。
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* 优先精确匹配，其次包含匹配。
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* 包含匹配时优先匹配违规类别（广告/辱骂/敏感/无意义），最后才匹配"正常"，
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* 避免 AI 解释性文本中同时出现"正常"和违规词时误判为"正常"。
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* 无匹配时返回空字符串（触发 defaultIfEmpty 安全拦截），避免原始文本被误判为违规类别。
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*/
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static String extractChoice(String text, List<String> choices) {
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@@ -136,10 +138,16 @@ class AiFoundationDelegate {
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for (String choice : choices) {
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if (trimmed.equals(choice)) return choice;
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}
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// 包含匹配（响应可能包含额外文字，如"该评论属于：广告"）
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// 包含匹配：先匹配违规类别，最后匹配"正常"
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// 避免"该评论属于广告，不是正常评论"被误匹配为"正常"
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for (String choice : choices) {
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if ("正常".equals(choice)) continue;
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if (trimmed.contains(choice)) return choice;
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}
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// 最后检查"正常"
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for (String choice : choices) {
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if ("正常".equals(choice) && trimmed.contains(choice)) return choice;
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}
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// 无匹配，返回空字符串触发安全拦截
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log.warn("[Delegate] No matching choice found in response: '{}', returning empty for safety", trimmed);
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return "";
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@@ -341,7 +341,7 @@ public class AiReplyOrchestrator {
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// Update retryCount and reset status to PENDING
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return updateRecordForRetry(replyRecord, newRetryCount)
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.delayElement(Duration.ofSeconds(delaySeconds))
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.then(retryGenerate(context, replyRecord, modelName, personaName));
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.flatMap(updated -> retryGenerate(context, updated, modelName, personaName));
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} else {
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log.warn("[Orchestrator] Max retry count ({}) exceeded for: {}, marking as FAIL. Reason: {}",
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maxRetry, context.commentId(), reason);
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@@ -5,13 +5,16 @@ import com.fasterxml.jackson.databind.ObjectMapper;
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import lombok.extern.slf4j.Slf4j;
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import org.jsoup.Jsoup;
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import org.jsoup.safety.Safelist;
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import org.springframework.dao.OptimisticLockingFailureException;
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import org.springframework.stereotype.Component;
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import reactor.core.publisher.Mono;
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import reactor.util.retry.Retry;
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import run.halo.app.core.extension.content.Comment;
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import run.halo.app.core.extension.content.Reply;
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import run.halo.app.extension.ConfigMap;
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import run.halo.app.extension.ReactiveExtensionClient;
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import java.time.Duration;
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import java.time.Instant;
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import java.util.List;
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import java.util.Map;
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@@ -178,15 +181,18 @@ public class CommentPreFilterService {
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spec.setApproved(false);
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spec.setApprovedTime(null);
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return client.update(comment)
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.doOnSuccess(c -> log.info("[PreFilter] Comment {} set to pending for violation", commentName))
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.onErrorResume(e -> {
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log.warn("[PreFilter] Failed to penalize comment {}: {}", commentName, e.getMessage());
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return Mono.empty();
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});
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.doOnSuccess(c -> log.info("[PreFilter] Comment {} set to pending for violation", commentName));
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}
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log.debug("[PreFilter] Comment {} already unapproved, skip penalize", commentName);
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return Mono.<Comment>empty();
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})
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.retryWhen(Retry.backoff(3, Duration.ofMillis(100))
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.filter(OptimisticLockingFailureException.class::isInstance)
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.doBeforeRetry(sig -> log.debug("[PreFilter] Retrying penalizeComment {} (attempt {})", commentName, sig.totalRetries() + 1)))
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.onErrorResume(e -> {
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log.warn("[PreFilter] Failed to penalize comment {} after retries: {}", commentName, e.getMessage());
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return Mono.empty();
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})
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.then();
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}
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@@ -201,15 +207,18 @@ public class CommentPreFilterService {
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spec.setApproved(false);
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spec.setApprovedTime(null);
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return client.update(reply)
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.doOnSuccess(r -> log.info("[PreFilter] Reply {} set to pending for violation", replyName))
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.onErrorResume(e -> {
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log.warn("[PreFilter] Failed to penalize reply {}: {}", replyName, e.getMessage());
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return Mono.empty();
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});
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.doOnSuccess(r -> log.info("[PreFilter] Reply {} set to pending for violation", replyName));
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}
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log.debug("[PreFilter] Reply {} already unapproved, skip penalize", replyName);
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return Mono.<Reply>empty();
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})
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.retryWhen(Retry.backoff(3, Duration.ofMillis(100))
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.filter(OptimisticLockingFailureException.class::isInstance)
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.doBeforeRetry(sig -> log.debug("[PreFilter] Retrying penalizeReply {} (attempt {})", replyName, sig.totalRetries() + 1)))
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.onErrorResume(e -> {
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log.warn("[PreFilter] Failed to penalize reply {} after retries: {}", replyName, e.getMessage());
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return Mono.empty();
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})
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.then();
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}
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@@ -9,8 +9,11 @@ import run.halo.app.core.extension.content.Post;
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import run.halo.app.core.extension.content.Tag;
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import run.halo.app.extension.ExtensionClient;
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import run.halo.app.extension.ReactiveExtensionClient;
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import reactor.core.publisher.Flux;
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import reactor.core.publisher.Mono;
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import java.util.List;
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/**
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* Shared service for resolving AI persona name from a comment's associated
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* post/category/tag annotations.
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@@ -57,64 +60,80 @@ public class PersonaResolver {
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return Mono.just(persona);
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}
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}
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// 2. Category annotations
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// 2. Category annotations (check sequentially, return first match)
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var spec = post.getSpec();
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if (spec != null && spec.getCategories() != null) {
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for (String categoryName : spec.getCategories()) {
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var persona = resolveFromCategory(categoryName);
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if (persona != null) return Mono.just(persona);
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}
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}
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// 3. Tag annotations
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if (spec != null && spec.getTags() != null) {
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for (String tagName : spec.getTags()) {
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var persona = resolveFromTag(tagName);
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if (persona != null) return Mono.just(persona);
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}
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}
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return Mono.just("");
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List<String> categories = (spec != null && spec.getCategories() != null)
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? spec.getCategories() : List.of();
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// 3. Tag annotations (fallback if no category match)
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List<String> tags = (spec != null && spec.getTags() != null)
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? spec.getTags() : List.of();
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return resolveFromCategories(categories)
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.switchIfEmpty(resolveFromTags(tags));
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})
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.defaultIfEmpty("");
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}
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private String resolveFromCategory(String categoryName) {
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// Use block() here because this is called from a Reconciler (sync context)
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// For reactive context, the caller should use the reactive version
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try {
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return reactiveClient.fetch(Category.class, categoryName)
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.mapNotNull(cat -> {
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var catAnnotations = cat.getMetadata().getAnnotations();
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if (catAnnotations != null) {
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String catPersona = catAnnotations.get(AI_PERSONA_ANNOTATION);
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if (catPersona != null && !catPersona.isBlank()) {
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return catPersona;
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}
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}
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return null;
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})
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.block();
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} catch (Exception e) {
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return null;
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/**
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* Sequentially check category annotations, returning the first non-empty persona.
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* Uses concatMap to preserve order and short-circuit on first match.
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*/
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private Mono<String> resolveFromCategories(List<String> categoryNames) {
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if (categoryNames == null || categoryNames.isEmpty()) {
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return Mono.empty();
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}
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return Flux.fromIterable(categoryNames)
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.concatMap(this::resolveFromCategory)
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.next();
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}
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private String resolveFromTag(String tagName) {
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try {
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return reactiveClient.fetch(Tag.class, tagName)
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.mapNotNull(tag -> {
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var tagAnnotations = tag.getMetadata().getAnnotations();
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if (tagAnnotations != null) {
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String tagPersona = tagAnnotations.get(AI_PERSONA_ANNOTATION);
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if (tagPersona != null && !tagPersona.isBlank()) {
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return tagPersona;
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}
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}
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return null;
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})
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.block();
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} catch (Exception e) {
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return null;
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/**
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* Sequentially check tag annotations, returning the first non-empty persona.
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* Uses concatMap to preserve order and short-circuit on first match.
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*/
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private Mono<String> resolveFromTags(List<String> tagNames) {
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if (tagNames == null || tagNames.isEmpty()) {
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return Mono.empty();
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}
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return Flux.fromIterable(tagNames)
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.concatMap(this::resolveFromTag)
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.next();
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}
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private Mono<String> resolveFromCategory(String categoryName) {
|
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return reactiveClient.fetch(Category.class, categoryName)
|
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.mapNotNull(cat -> {
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var catAnnotations = cat.getMetadata().getAnnotations();
|
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if (catAnnotations != null) {
|
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String catPersona = catAnnotations.get(AI_PERSONA_ANNOTATION);
|
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if (catPersona != null && !catPersona.isBlank()) {
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return catPersona;
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}
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}
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return null;
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})
|
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.onErrorResume(e -> {
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log.warn("Failed to resolve persona from category {}: {}", categoryName, e.getMessage());
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return Mono.empty();
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});
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}
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private Mono<String> resolveFromTag(String tagName) {
|
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return reactiveClient.fetch(Tag.class, tagName)
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.mapNotNull(tag -> {
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var tagAnnotations = tag.getMetadata().getAnnotations();
|
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if (tagAnnotations != null) {
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String tagPersona = tagAnnotations.get(AI_PERSONA_ANNOTATION);
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if (tagPersona != null && !tagPersona.isBlank()) {
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return tagPersona;
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}
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}
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return null;
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})
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.onErrorResume(e -> {
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log.warn("Failed to resolve persona from tag {}: {}", tagName, e.getMessage());
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return Mono.empty();
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});
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}
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/**
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@@ -30,4 +30,4 @@ spec:
|
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url: "https://github.com/sunny-335/plugin-comment-ai-autopilot/blob/main/LICENSE"
|
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settingName: "comment-ai-autopilot-settings"
|
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configMapName: "comment-ai-autopilot-configmap"
|
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version: "1.2.0"
|
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version: "1.2.1"
|
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@@ -76,7 +76,10 @@
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<svg class="filter-icon fp-icon-ok" fill="currentColor" viewBox="0 0 20 20"><path fill-rule="evenodd" d="M10 18a8 8 0 100-16 8 8 0 000 16zm3.707-9.293a1 1 0 00-1.414-1.414L9 10.586 7.707 9.293a1 1 0 00-1.414 1.414l2 2a1 1 0 001.414 0l4-4z" clip-rule="evenodd"/></svg>
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<span class="filter-category">误报</span>
|
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<span class="filter-detail">{{ reply.spec.filterReason || '用户确认为误报' }}</span>
|
||||
<button class="btn-trigger-ai" @click="handleTriggerAiReply(reply)">触发AI回复</button>
|
||||
<button class="btn-trigger-ai" :disabled="triggerAiLoadingName === reply.metadata.name" @click="handleTriggerAiReply(reply)">
|
||||
<span v-if="triggerAiLoadingName === reply.metadata.name" class="fp-spinner"></span>
|
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触发AI回复
|
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</button>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
@@ -176,7 +179,7 @@
|
||||
</template>
|
||||
|
||||
<script setup lang="ts">
|
||||
import { ref, onMounted, watch } from "vue"
|
||||
import { ref, onMounted, onUnmounted, watch } from "vue"
|
||||
import { axiosInstance } from "@halo-dev/api-client"
|
||||
import { VPageHeader, VButton, VLoading, Toast } from "@halo-dev/components"
|
||||
import { IconPlug } from "@halo-dev/components"
|
||||
@@ -189,6 +192,7 @@ const selectedNames = ref<Set<string>>(new Set()); const selectAll = ref(false);
|
||||
const filterStatus = ref(""); const filterSentiment = ref(""); const filterKeyword = ref("");
|
||||
const showDialog = ref(false); const conversationLoading = ref(false); const conversationMessages = ref<ConversationMessage[]>([]);
|
||||
const showFalsePositiveDialog = ref(false); const falsePositiveTarget = ref<AiCommentReplyItem | null>(null); const fpLoading = ref(false);
|
||||
const triggerAiLoadingName = ref<string | null>(null);
|
||||
|
||||
const toggleSelect = (name: string) => { selectedNames.value.has(name) ? selectedNames.value.delete(name) : selectedNames.value.add(name); selectAll.value = replies.value.length > 0 && replies.value.every(r => selectedNames.value.has(r.metadata.name)) }
|
||||
const toggleSelectAll = () => { if (selectAll.value) { selectedNames.value.clear(); selectAll.value = false } else { selectedNames.value = new Set(replies.value.map(r => r.metadata.name)); selectAll.value = true } }
|
||||
@@ -255,17 +259,26 @@ const handleFalsePositive = async (action: string) => {
|
||||
} finally { fpLoading.value = false }
|
||||
}
|
||||
const handleTriggerAiReply = async (reply: AiCommentReplyItem) => {
|
||||
if (triggerAiLoadingName.value) return
|
||||
triggerAiLoadingName.value = reply.metadata.name
|
||||
try {
|
||||
await axiosInstance.post(`/apis/console.api.comment-ai-autopilot.nxxy335.top/v1alpha1/replies/${reply.metadata.name}/false-positive`, { action: "aiReply" })
|
||||
Toast.success("AI回复正在后台生成")
|
||||
fetchReplies()
|
||||
} catch (e: any) {
|
||||
Toast.error(e?.response?.data?.message || "触发失败")
|
||||
}
|
||||
} finally { triggerAiLoadingName.value = null }
|
||||
}
|
||||
watch([filterStatus, filterSentiment, filterKeyword], () => { page.value = 1; fetchReplies() })
|
||||
// 状态/情感筛选立即触发；关键词输入防抖 300ms 避免每次按键都请求
|
||||
watch([filterStatus, filterSentiment], () => { page.value = 1; fetchReplies() })
|
||||
let keywordDebounceTimer: ReturnType<typeof setTimeout> | null = null
|
||||
watch(filterKeyword, () => {
|
||||
if (keywordDebounceTimer) clearTimeout(keywordDebounceTimer)
|
||||
keywordDebounceTimer = setTimeout(() => { page.value = 1; fetchReplies() }, 300)
|
||||
})
|
||||
watch(page, () => { selectedNames.value.clear(); selectAll.value = false; fetchReplies() })
|
||||
onMounted(fetchReplies)
|
||||
onUnmounted(() => { if (keywordDebounceTimer) clearTimeout(keywordDebounceTimer) })
|
||||
</script>
|
||||
|
||||
<style scoped>
|
||||
@@ -309,8 +322,10 @@ onMounted(fetchReplies)
|
||||
.btn-false-positive { flex-shrink: 0; margin-left: auto; padding: 2px 8px; border: 1px solid #b45309; border-radius: 4px; background: transparent; color: #b45309; font-size: 11px; cursor: pointer; white-space: nowrap; transition: all 0.15s; }
|
||||
.btn-false-positive:hover { background: #b45309; color: #fff; }
|
||||
.fp-icon-ok { color: #16a34a; }
|
||||
.btn-trigger-ai { flex-shrink: 0; margin-left: auto; padding: 2px 8px; border: 1px solid #2563eb; border-radius: 4px; background: transparent; color: #2563eb; font-size: 11px; cursor: pointer; white-space: nowrap; transition: all 0.15s; }
|
||||
.btn-trigger-ai:hover { background: #2563eb; color: #fff; }
|
||||
.btn-trigger-ai { flex-shrink: 0; margin-left: auto; padding: 2px 8px; border: 1px solid #2563eb; border-radius: 4px; background: transparent; color: #2563eb; font-size: 11px; cursor: pointer; white-space: nowrap; transition: all 0.15s; display: inline-flex; align-items: center; gap: 4px; }
|
||||
.btn-trigger-ai:hover:not(:disabled) { background: #2563eb; color: #fff; }
|
||||
.btn-trigger-ai:disabled { opacity: 0.6; cursor: not-allowed; }
|
||||
.btn-trigger-ai .fp-spinner { width: 11px; height: 11px; border-color: rgba(37,99,235,0.3); border-top-color: #2563eb; }
|
||||
.card-footer { display: flex; flex-direction: column; gap: 12px; padding: 12px 16px; background: #f9fafb; border-top: 1px solid #f3f4f6; }
|
||||
@media (min-width: 640px) { .card-footer { flex-direction: row; justify-content: space-between; align-items: center; } }
|
||||
.footer-info { font-size: 12px; color: #6b7280; display: flex; flex-wrap: wrap; gap: 12px; }
|
||||
@@ -329,7 +344,7 @@ onMounted(fetchReplies)
|
||||
.tag-PASS { background: #dcfce7; color: #15803d; } .tag-FAIL { background: #fee2e2; color: #b91c1c; } .tag-PENDING { background: #fef9c3; color: #a16207; } .tag-REJECTED { background: #ffedd5; color: #c2410c; } .tag-FILTERED { background: #f1f5f9; color: #b45309; border: 1px solid #fde68a; } .tag-FALSE_POSITIVE { background: #dbeafe; color: #1d4ed8; border: 1px solid #93c5fd; }
|
||||
.tag-published { background: #dbeafe; color: #1d4ed8; } .tag-draft { background: #f3f4f6; color: #4b5563; }
|
||||
.tag-conv { background: #f3e8ff; color: #7e22ce; }
|
||||
.tag-VERY_POSITIVE { background: #dcfce7; color: #14532d; } .tag-POSITIVE { background: #ecfdf5; color: #15803d; } .tag-NEGATIVE { background: #ffe4e6; color: #e11d48; } .tag-VERY_NEGATIVE { background: #fee2e2; color: #991b1b; }
|
||||
.tag-VERY_POSITIVE { background: #dcfce7; color: #14532d; } .tag-POSITIVE { background: #ecfdf5; color: #15803d; } .tag-NEUTRAL { background: #f3f4f6; color: #4b5563; } .tag-NEGATIVE { background: #ffe4e6; color: #e11d48; } .tag-VERY_NEGATIVE { background: #fee2e2; color: #991b1b; }
|
||||
|
||||
/* 对话弹窗与响应式气泡 */
|
||||
.dialog-overlay { position: fixed; inset: 0; background: rgba(0,0,0,0.5); display: flex; align-items: center; justify-content: center; z-index: 9999; backdrop-filter: blur(2px); padding: 16px; box-sizing: border-box; }
|
||||
|
||||
@@ -309,7 +309,7 @@ const filteredCommenters = computed(() => { const kw = commenterSearch.value.tri
|
||||
const openCommenterDialog = async () => { showCommenterDialog.value = true; commenterLoading.value = true; try { const { data } = await axiosInstance.get(`${apiBase}/commenters`); commenterList.value = data.items || data } catch(e) { commenterList.value = [] } finally { commenterLoading.value = false } }
|
||||
const addCommenter = (c: any) => { const v = c.email || c.displayName; const cur = settings.basic.blockedCommenters.split(",").map(s=>s.trim()).filter(Boolean); if(cur.includes(v)) return; cur.push(v); settings.basic.blockedCommenters = cur.join(","); Toast.success("已添加"); showCommenterDialog.value = false }
|
||||
const cleanupLoading = ref(false); const cleanupResult = ref<number | null>(null)
|
||||
const performCleanup = async () => { cleanupLoading.value=true; try { const { data } = await axiosInstance.post(`${apiBase}/cleanup`); cleanupResult.value = data.deletedCount ?? data ?? 0; Toast.success("清理完成") } catch(e){ Toast.error("清理失败") } finally { cleanupLoading.value=false } }
|
||||
const performCleanup = async () => { cleanupLoading.value=true; try { const { data } = await axiosInstance.post(`${apiBase}/cleanup`); cleanupResult.value = typeof data === 'number' ? data : (data?.deletedCount ?? 0); Toast.success("清理完成") } catch(e){ Toast.error("清理失败") } finally { cleanupLoading.value=false } }
|
||||
|
||||
// Persona
|
||||
const personasApiBase = `${apiBase}/personas`
|
||||
|
||||
Reference in New Issue
Block a user