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

docs/CHANGELOG.md

@@ -1,5 +1,28 @@
 # 更新日志
 
+## v1.2.1
+
+> 2026-07-01
+
+### Bug 修复
+
+- **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
+- **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
+- **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
+- **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
+- **修复 `approveOriginalComment` 缺少乐观锁重试** — 同上，添加 `Retry.backoff(3, 100ms)` 重试
+- **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
+- **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
+- **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
+- **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
+- **修复 `performCleanup` 逻辑错误** — 清理逻辑存在判断错误
+
+### 改进
+
+- **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
+
+---
+
 ## v1.2.0
 
 > 2026-06-25

gradle.properties

@@ -1,4 +1,4 @@
-version=1.2.0
+version=1.2.1
 
 # Fix Windows Gradle Worker Daemon exit code 268435659 when running pnpm via Exec tasks
 org.gradle.daemon=false

src/main/java/top/nxxy335/commentaiautopilot/endpoint/CommentAiAutopilotEndpoint.java

@@ -1060,10 +1060,13 @@ public class CommentAiAutopilotEndpoint implements CustomEndpoint {
 
                 return client.fetch(AiCommentReply.class, name)
                     .flatMap(record -> {
-                        if (!"FILTERED".equals(record.getSpec().getStatus())
+                        String currentStatus = record.getSpec().getStatus();
-                            && !"FALSE_POSITIVE".equals(record.getSpec().getStatus())) {
+                        // 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）
+                        if (!"FILTERED".equals(currentStatus)
+                            && !"FALSE_POSITIVE".equals(currentStatus)
+                            && !"FAIL".equals(currentStatus)) {
                             return ServerResponse.badRequest()
-                                .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"));
+                                .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"));
                         }
 
                         String commentName = record.getSpec().getCommentId();
@@ -1092,11 +1095,15 @@ public class CommentAiAutopilotEndpoint implements CustomEndpoint {
                                 .filter(e -> e instanceof OptimisticLockingFailureException))
                             .then());
 
-                        // 3. 异步触发 AI 回复（不阻塞 HTTP 响应）
+                        // 3. 异步触发 AI 回复（在记录更新完成后，不阻塞 HTTP 响应）
                         // 使用 processFalsePositive 跳过前置过滤和去重检查
+                        final boolean isConversation = Boolean.TRUE.equals(record.getSpec().getIsAiConversation());
+                        final String recordName = record.getMetadata().getName();
+
+                        return approveMono
+                            .then(updateRecordMono)
+                            .doOnSuccess(v -> {
                                 if ("aiReply".equals(action)) {
-                            boolean isConversation = Boolean.TRUE.equals(record.getSpec().getIsAiConversation());
-                            String recordName = record.getMetadata().getName();
                                     personaResolver.getPersonaNameFromComment(commentName)
                                         .flatMap(personaName ->
                                             orchestrator.processFalsePositive(commentName, replyName, isConversation, personaName, recordName)
@@ -1107,9 +1114,7 @@ public class CommentAiAutopilotEndpoint implements CustomEndpoint {
                                             () -> log.info("[FalsePositive] AI reply trigger completed for {}", commentName)
                                         );
                                 }
-
+                            })
-                        return approveMono
-                            .then(updateRecordMono)
                             .then(ServerResponse.ok().bodyValue(Map.of(
                                 "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"
                             )));

src/main/java/top/nxxy335/commentaiautopilot/service/AiFoundationDelegate.java

@@ -127,6 +127,8 @@ class AiFoundationDelegate {
     /**
      * 从 chat 响应文本中提取匹配的分类值。
      * 优先精确匹配，其次包含匹配。
+     * 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"，
+     * 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"。
      * 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。
      */
     static String extractChoice(String text, List<String> choices) {
@@ -136,10 +138,16 @@ class AiFoundationDelegate {
         for (String choice : choices) {
             if (trimmed.equals(choice)) return choice;
         }
-        // 包含匹配（响应可能包含额外文字，如"该评论属于：广告"）
+        // 包含匹配：先匹配违规类别，最后匹配"正常"
+        // 避免"该评论属于广告，不是正常评论"被误匹配为"正常"
         for (String choice : choices) {
+            if ("正常".equals(choice)) continue;
             if (trimmed.contains(choice)) return choice;
         }
+        // 最后检查"正常"
+        for (String choice : choices) {
+            if ("正常".equals(choice) && trimmed.contains(choice)) return choice;
+        }
         // 无匹配，返回空字符串触发安全拦截
         log.warn("[Delegate] No matching choice found in response: '{}', returning empty for safety", trimmed);
         return "";

src/main/java/top/nxxy335/commentaiautopilot/service/AiReplyOrchestrator.java

@@ -341,7 +341,7 @@ public class AiReplyOrchestrator {
                 // Update retryCount and reset status to PENDING
                 return updateRecordForRetry(replyRecord, newRetryCount)
                     .delayElement(Duration.ofSeconds(delaySeconds))
-                    .then(retryGenerate(context, replyRecord, modelName, personaName));
+                    .flatMap(updated -> retryGenerate(context, updated, modelName, personaName));
             } else {
                 log.warn("[Orchestrator] Max retry count ({}) exceeded for: {}, marking as FAIL. Reason: {}",
                     maxRetry, context.commentId(), reason);

src/main/java/top/nxxy335/commentaiautopilot/service/CommentPreFilterService.java

@@ -5,13 +5,16 @@ import com.fasterxml.jackson.databind.ObjectMapper;
 import lombok.extern.slf4j.Slf4j;
 import org.jsoup.Jsoup;
 import org.jsoup.safety.Safelist;
+import org.springframework.dao.OptimisticLockingFailureException;
 import org.springframework.stereotype.Component;
 import reactor.core.publisher.Mono;
+import reactor.util.retry.Retry;
 import run.halo.app.core.extension.content.Comment;
 import run.halo.app.core.extension.content.Reply;
 import run.halo.app.extension.ConfigMap;
 import run.halo.app.extension.ReactiveExtensionClient;
 
+import java.time.Duration;
 import java.time.Instant;
 import java.util.List;
 import java.util.Map;
@@ -178,15 +181,18 @@ public class CommentPreFilterService {
                     spec.setApproved(false);
                     spec.setApprovedTime(null);
                     return client.update(comment)
-                        .doOnSuccess(c -> log.info("[PreFilter] Comment {} set to pending for violation", commentName))
+                        .doOnSuccess(c -> log.info("[PreFilter] Comment {} set to pending for violation", commentName));
-                        .onErrorResume(e -> {
-                            log.warn("[PreFilter] Failed to penalize comment {}: {}", commentName, e.getMessage());
-                            return Mono.empty();
-                        });
                 }
                 log.debug("[PreFilter] Comment {} already unapproved, skip penalize", commentName);
                 return Mono.<Comment>empty();
             })
+            .retryWhen(Retry.backoff(3, Duration.ofMillis(100))
+                .filter(OptimisticLockingFailureException.class::isInstance)
+                .doBeforeRetry(sig -> log.debug("[PreFilter] Retrying penalizeComment {} (attempt {})", commentName, sig.totalRetries() + 1)))
+            .onErrorResume(e -> {
+                log.warn("[PreFilter] Failed to penalize comment {} after retries: {}", commentName, e.getMessage());
+                return Mono.empty();
+            })
             .then();
     }
 
@@ -201,15 +207,18 @@ public class CommentPreFilterService {
                     spec.setApproved(false);
                     spec.setApprovedTime(null);
                     return client.update(reply)
-                        .doOnSuccess(r -> log.info("[PreFilter] Reply {} set to pending for violation", replyName))
+                        .doOnSuccess(r -> log.info("[PreFilter] Reply {} set to pending for violation", replyName));
-                        .onErrorResume(e -> {
-                            log.warn("[PreFilter] Failed to penalize reply {}: {}", replyName, e.getMessage());
-                            return Mono.empty();
-                        });
                 }
                 log.debug("[PreFilter] Reply {} already unapproved, skip penalize", replyName);
                 return Mono.<Reply>empty();
             })
+            .retryWhen(Retry.backoff(3, Duration.ofMillis(100))
+                .filter(OptimisticLockingFailureException.class::isInstance)
+                .doBeforeRetry(sig -> log.debug("[PreFilter] Retrying penalizeReply {} (attempt {})", replyName, sig.totalRetries() + 1)))
+            .onErrorResume(e -> {
+                log.warn("[PreFilter] Failed to penalize reply {} after retries: {}", replyName, e.getMessage());
+                return Mono.empty();
+            })
             .then();
     }
 

src/main/java/top/nxxy335/commentaiautopilot/service/PersonaResolver.java

@@ -9,8 +9,11 @@ import run.halo.app.core.extension.content.Post;
 import run.halo.app.core.extension.content.Tag;
 import run.halo.app.extension.ExtensionClient;
 import run.halo.app.extension.ReactiveExtensionClient;
+import reactor.core.publisher.Flux;
 import reactor.core.publisher.Mono;
 
+import java.util.List;
+
 /**
  * Shared service for resolving AI persona name from a comment's associated
  * post/category/tag annotations.
@@ -57,30 +60,47 @@ public class PersonaResolver {
                         return Mono.just(persona);
                     }
                 }
-                // 2. Category annotations
+                // 2. Category annotations (check sequentially, return first match)
                 var spec = post.getSpec();
-                if (spec != null && spec.getCategories() != null) {
+                List<String> categories = (spec != null && spec.getCategories() != null)
-                    for (String categoryName : spec.getCategories()) {
+                    ? spec.getCategories() : List.of();
-                        var persona = resolveFromCategory(categoryName);
+                // 3. Tag annotations (fallback if no category match)
-                        if (persona != null) return Mono.just(persona);
+                List<String> tags = (spec != null && spec.getTags() != null)
-                    }
+                    ? spec.getTags() : List.of();
-                }
+
-                // 3. Tag annotations
+                return resolveFromCategories(categories)
-                if (spec != null && spec.getTags() != null) {
+                    .switchIfEmpty(resolveFromTags(tags));
-                    for (String tagName : spec.getTags()) {
-                        var persona = resolveFromTag(tagName);
-                        if (persona != null) return Mono.just(persona);
-                    }
-                }
-                return Mono.just("");
             })
             .defaultIfEmpty("");
     }
 
-    private String resolveFromCategory(String categoryName) {
+    /**
-        // Use block() here because this is called from a Reconciler (sync context)
+     * Sequentially check category annotations, returning the first non-empty persona.
-        // For reactive context, the caller should use the reactive version
+     * Uses concatMap to preserve order and short-circuit on first match.
-        try {
+     */
+    private Mono<String> resolveFromCategories(List<String> categoryNames) {
+        if (categoryNames == null || categoryNames.isEmpty()) {
+            return Mono.empty();
+        }
+        return Flux.fromIterable(categoryNames)
+            .concatMap(this::resolveFromCategory)
+            .next();
+    }
+
+    /**
+     * Sequentially check tag annotations, returning the first non-empty persona.
+     * Uses concatMap to preserve order and short-circuit on first match.
+     */
+    private Mono<String> resolveFromTags(List<String> tagNames) {
+        if (tagNames == null || tagNames.isEmpty()) {
+            return Mono.empty();
+        }
+        return Flux.fromIterable(tagNames)
+            .concatMap(this::resolveFromTag)
+            .next();
+    }
+
+    private Mono<String> resolveFromCategory(String categoryName) {
         return reactiveClient.fetch(Category.class, categoryName)
             .mapNotNull(cat -> {
                 var catAnnotations = cat.getMetadata().getAnnotations();
@@ -92,14 +112,13 @@ public class PersonaResolver {
                 }
                 return null;
             })
-                .block();
+            .onErrorResume(e -> {
-        } catch (Exception e) {
+                log.warn("Failed to resolve persona from category {}: {}", categoryName, e.getMessage());
-            return null;
+                return Mono.empty();
-        }
+            });
     }
 
-    private String resolveFromTag(String tagName) {
+    private Mono<String> resolveFromTag(String tagName) {
-        try {
         return reactiveClient.fetch(Tag.class, tagName)
             .mapNotNull(tag -> {
                 var tagAnnotations = tag.getMetadata().getAnnotations();
@@ -111,10 +130,10 @@ public class PersonaResolver {
                 }
                 return null;
             })
-                .block();
+            .onErrorResume(e -> {
-        } catch (Exception e) {
+                log.warn("Failed to resolve persona from tag {}: {}", tagName, e.getMessage());
-            return null;
+                return Mono.empty();
-        }
+            });
     }
 
     /**

src/main/resources/plugin.yaml

@@ -30,4 +30,4 @@ spec:
       url: "https://github.com/sunny-335/plugin-comment-ai-autopilot/blob/main/LICENSE"
   settingName: "comment-ai-autopilot-settings"
   configMapName: "comment-ai-autopilot-configmap"
-  version: "1.2.0"
+  version: "1.2.1"

ui/src/views/LogsView.vue

@@ -76,7 +76,10 @@
                 <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>
                 <span class="filter-category">误报</span>
                 <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>
+                  触发AI回复
+                </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 }
 }
-}
+// 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, filterKeyword], () => { page.value = 1; fetchReplies() })
+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 { 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 { background: #2563eb; color: #fff; }
+.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; }

ui/src/views/SettingsView.vue

@@ -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`