feat: 多AI角色支持、Bug修复、文档更新

src/main/java/top/nxxy335/commentaiautopilot/CommentAiAutopilotPlugin.java

@@ -1,12 +1,17 @@
 package top.nxxy335.commentaiautopilot;
 
 import org.springframework.stereotype.Component;
+import run.halo.app.extension.ReactiveExtensionClient;
 import run.halo.app.extension.index.IndexSpecs;
 import run.halo.app.extension.Scheme;
 import run.halo.app.extension.SchemeManager;
+import run.halo.app.extension.Metadata;
 import run.halo.app.plugin.BasePlugin;
 import run.halo.app.plugin.PluginContext;
 import top.nxxy335.commentaiautopilot.extension.AiCommentReply;
+import top.nxxy335.commentaiautopilot.extension.AiPersona;
+import lombok.extern.slf4j.Slf4j;
+import reactor.core.publisher.Mono;
 
 /**
  * <p>Plugin main class to manage the lifecycle of the plugin.</p>
@@ -16,14 +21,17 @@ import top.nxxy335.commentaiautopilot.extension.AiCommentReply;
  * @author 暖心向阳335
  * @since 1.0.0
  */
+@Slf4j
 @Component
 public class CommentAiAutopilotPlugin extends BasePlugin {
 
     private final SchemeManager schemeManager;
+    private final ReactiveExtensionClient client;
 
-    public CommentAiAutopilotPlugin(PluginContext pluginContext, SchemeManager schemeManager) {
+    public CommentAiAutopilotPlugin(PluginContext pluginContext, SchemeManager schemeManager, ReactiveExtensionClient client) {
         super(pluginContext);
         this.schemeManager = schemeManager;
+        this.client = client;
     }
 
     @Override
@@ -36,10 +44,36 @@ public class CommentAiAutopilotPlugin extends BasePlugin {
             indexSpecs.add(IndexSpecs.<AiCommentReply, String>single("spec.status", String.class)
                 .indexFunc(ext -> ext.getSpec().getStatus()));
         });
+        schemeManager.register(AiPersona.class);
+
+        // 初始化默认AI角色"小回"
+        initDefaultPersona();
+    }
+
+    private void initDefaultPersona() {
+        client.fetch(AiPersona.class, "default-ai-persona")
+            .switchIfEmpty(Mono.defer(() -> {
+                log.info("初始化默认AI角色：小回");
+                AiPersona persona = new AiPersona();
+                persona.setMetadata(new Metadata());
+                persona.getMetadata().setName("default-ai-persona");
+                AiPersona.AiPersonaSpec spec = new AiPersona.AiPersonaSpec();
+                spec.setDisplayName("小回");
+                spec.setPrompt("你是一个友善的评论者，回复简洁自然，像朋友聊天一样。");
+                spec.setEmail("");
+                spec.setIsDefault(true);
+                persona.setSpec(spec);
+                return client.create(persona);
+            }))
+            .subscribe(
+                created -> log.info("默认AI角色已就绪"),
+                err -> log.warn("初始化默认AI角色失败: {}", err.getMessage())
+            );
     }
 
     @Override
     public void stop() {
         schemeManager.unregister(Scheme.buildFromType(AiCommentReply.class));
+        schemeManager.unregister(Scheme.buildFromType(AiPersona.class));
     }
 }

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

@@ -1,6 +1,7 @@
 package top.nxxy335.commentaiautopilot.endpoint;
 
 import lombok.extern.slf4j.Slf4j;
+import org.springframework.beans.factory.ObjectProvider;
 import org.springframework.stereotype.Component;
 import org.springframework.web.reactive.function.server.RouterFunction;
 import org.springframework.web.reactive.function.server.ServerRequest;
@@ -8,6 +9,7 @@ import org.springframework.web.reactive.function.server.ServerResponse;
 import reactor.core.publisher.Flux;
 import reactor.core.publisher.Mono;
 import run.halo.app.core.extension.content.Comment;
+import run.halo.app.core.extension.content.Post;
 import run.halo.app.core.extension.content.Reply;
 import run.halo.app.core.extension.endpoint.CustomEndpoint;
 import run.halo.app.extension.ConfigMap;
@@ -16,6 +18,8 @@ import run.halo.app.extension.ListOptions;
 import run.halo.app.extension.ReactiveExtensionClient;
 import run.halo.app.extension.PageRequestImpl;
 import top.nxxy335.commentaiautopilot.extension.AiCommentReply;
+import top.nxxy335.commentaiautopilot.extension.AiPersona;
+import top.nxxy335.commentaiautopilot.service.AiFoundationClient;
 import top.nxxy335.commentaiautopilot.service.AiReplyCleanupService;
 import top.nxxy335.commentaiautopilot.service.AiReplyOrchestrator;
 
@@ -44,14 +48,16 @@ public class CommentAiAutopilotEndpoint implements CustomEndpoint {
     private final ReactiveExtensionClient client;
     private final AiReplyOrchestrator orchestrator;
     private final AiReplyCleanupService cleanupService;
+    private final ObjectProvider<AiFoundationClient> aiFoundationClientProvider;
     private final ObjectMapper objectMapper;
 
     private static final String CONFIG_MAP_NAME = "comment-ai-autopilot-configmap";
 
-    public CommentAiAutopilotEndpoint(ReactiveExtensionClient client, AiReplyOrchestrator orchestrator, AiReplyCleanupService cleanupService) {
+    public CommentAiAutopilotEndpoint(ReactiveExtensionClient client, AiReplyOrchestrator orchestrator, AiReplyCleanupService cleanupService, ObjectProvider<AiFoundationClient> aiFoundationClientProvider) {
         this.client = client;
         this.orchestrator = orchestrator;
         this.cleanupService = cleanupService;
+        this.aiFoundationClientProvider = aiFoundationClientProvider;
         this.objectMapper = new ObjectMapper();
     }
 
@@ -72,6 +78,12 @@ public class CommentAiAutopilotEndpoint implements CustomEndpoint {
             .POST("/replies/{replyName}/trigger-conversation", this::triggerConversationReply)
             .GET("/commenters", this::listCommenters)
             .POST("/cleanup", this::triggerCleanup)
+            .GET("/health", this::health)
+            .GET("/personas", this::listPersonas)
+            .GET("/personas/{name}", this::getPersonaByName)
+            .POST("/personas", this::createPersona)
+            .PUT("/personas/{name}", this::updatePersona)
+            .DELETE("/personas/{name}", this::deletePersona)
             .build();
     }
 
@@ -142,9 +154,39 @@ public class CommentAiAutopilotEndpoint implements CustomEndpoint {
     }
 
     private Mono<ServerResponse> getStats(ServerRequest request) {
+        String range = request.queryParam("range").orElse("7");
+
         return client.listAll(AiCommentReply.class, ListOptions.builder().build(), Sort.unsorted())
             .collectList()
-            .map(replies -> {
+            .map(allReplies -> {
+                // 根据 range 计算截止时间
+                ZoneId zoneId = ZoneId.systemDefault();
+                LocalDate today = LocalDate.now(zoneId);
+                Instant cutoffInstant;
+                int trendDays;
+
+                if ("all".equals(range)) {
+                    cutoffInstant = null; // 不做时间过滤
+                    trendDays = 30; // "all" 时趋势也展示最近30天
+                } else {
+                    int days = Integer.parseInt(range);
+                    cutoffInstant = today.minusDays(days).atStartOfDay(zoneId).toInstant();
+                    trendDays = days;
+                }
+
+                // 根据 range 过滤记录
+                List<AiCommentReply> replies;
+                if (cutoffInstant != null) {
+                    replies = allReplies.stream()
+                        .filter(r -> {
+                            Instant ts = r.getMetadata().getCreationTimestamp();
+                            return ts != null && !ts.isBefore(cutoffInstant);
+                        })
+                        .toList();
+                } else {
+                    replies = allReplies;
+                }
+
                 long total = replies.size();
                 long passCount = replies.stream()
                     .filter(r -> "PASS".equals(r.getSpec().getStatus())).count();
@@ -174,11 +216,10 @@ public class CommentAiAutopilotEndpoint implements CustomEndpoint {
                     }
                 }
 
-                ZoneId zoneId = ZoneId.systemDefault();
+                // 计算 dailyTrend
                 DateTimeFormatter formatter = DateTimeFormatter.ofPattern("yyyy-MM-dd");
-                LocalDate today = LocalDate.now(zoneId);
                 Map<LocalDate, Long> dailyMap = new HashMap<>();
-                for (int i = 0; i < 7; i++) {
+                for (int i = 0; i < trendDays; i++) {
                     dailyMap.put(today.minusDays(i), 0L);
                 }
                 for (var r : replies) {
@@ -194,7 +235,7 @@ public class CommentAiAutopilotEndpoint implements CustomEndpoint {
                     }
                 }
                 List<DailyCount> dailyTrend = new ArrayList<>();
-                for (int i = 0; i < 7; i++) {
+                for (int i = 0; i < trendDays; i++) {
                     LocalDate date = today.minusDays(i);
                     dailyTrend.add(new DailyCount(date.format(formatter), dailyMap.get(date)));
                 }
@@ -212,29 +253,35 @@ public class CommentAiAutopilotEndpoint implements CustomEndpoint {
     }
 
     private Mono<ServerResponse> getPersona(ServerRequest request) {
-        return client.fetch(ConfigMap.class, CONFIG_MAP_NAME)
-            .mapNotNull(cm -> {
-                var data = cm.getData();
-                if (data == null) return new PersonaResponse("小回", "", "");
-                String personaJson = data.get("persona");
-                if (personaJson == null || personaJson.isBlank()) return new PersonaResponse("小回", "", "");
-                try {
-                    JsonNode node = objectMapper.readTree(personaJson);
-                    String name = node.has("personaName") ? node.get("personaName").asText("小回") : "小回";
-                    String prompt = node.has("personaPrompt") ? node.get("personaPrompt").asText("") : "";
-                    String email = node.has("personaEmail") ? node.get("personaEmail").asText("") : "";
-                    return new PersonaResponse(name, prompt, email);
-                } catch (Exception e) {
-                    log.warn("Failed to parse persona config: {}", e.getMessage());
-                    return new PersonaResponse("小回", "", "");
+        return client.list(AiPersona.class,
+                persona -> persona.getSpec() != null && Boolean.TRUE.equals(persona.getSpec().getIsDefault()),
+                null)
+            .next()
+            .flatMap(persona -> {
+                String email = persona.getSpec().getEmail();
+                String avatarUrl = "";
+                if (email != null && !email.isBlank()) {
+                    try {
+                        var digest = java.security.MessageDigest.getInstance("SHA-256");
+                        var hashBytes = digest.digest(email.trim().toLowerCase().getBytes(java.nio.charset.StandardCharsets.UTF_8));
+                        var hexString = new StringBuilder();
+                        for (byte b : hashBytes) {
+                            hexString.append(String.format("%02x", b));
+                        }
+                        avatarUrl = "https://cn.cravatar.com/avatar/" + hexString;
+                    } catch (Exception ignored) {}
                 }
+                return ServerResponse.ok().bodyValue(Map.of(
+                    "name", persona.getSpec().getDisplayName(),
+                    "prompt", persona.getSpec().getPrompt() != null ? persona.getSpec().getPrompt() : "",
+                    "avatar", avatarUrl
+                ));
             })
-            .defaultIfEmpty(new PersonaResponse("小回", "", ""))
-            .onErrorResume(e -> {
-                log.warn("Failed to fetch persona settings: {}", e.getMessage());
-                return Mono.just(new PersonaResponse("小回", "", ""));
-            })
-            .flatMap(persona -> ServerResponse.ok().bodyValue(persona));
+            .switchIfEmpty(ServerResponse.ok().bodyValue(Map.of(
+                "name", "小回",
+                "prompt", "",
+                "avatar", ""
+            )));
     }
 
     public record DailyCount(String date, long count) {}
@@ -489,9 +536,12 @@ public class CommentAiAutopilotEndpoint implements CustomEndpoint {
                     return ServerResponse.badRequest()
                         .bodyValue(Map.of("message", "该评论已有AI回复记录"));
                 }
-                // Trigger the orchestrator
-                return orchestrator.processComment(commentName, null, false)
-                    .then(ServerResponse.ok().bodyValue(Map.of("message", "已触发AI回复")));
+                // Read persona name from post annotations
+                return getPersonaNameFromComment(commentName)
+                    .flatMap(personaName ->
+                        orchestrator.processComment(commentName, null, false, personaName)
+                            .then(ServerResponse.ok().bodyValue(Map.of("message", "已触发AI回复")))
+                    );
             });
     }
 
@@ -514,15 +564,44 @@ public class CommentAiAutopilotEndpoint implements CustomEndpoint {
                             return ServerResponse.badRequest()
                                 .bodyValue(Map.of("message", "该回复已有AI对话记录"));
                         }
-                        return orchestrator.processComment(commentName, replyName, true)
-                            .then(ServerResponse.ok().bodyValue(Map.of("message", "已触发AI对话回复")));
+                        return getPersonaNameFromComment(commentName)
+                            .flatMap(personaName ->
+                                orchestrator.processComment(commentName, replyName, true, personaName)
+                                    .then(ServerResponse.ok().bodyValue(Map.of("message", "已触发AI对话回复")))
+                            );
                     });
             })
             .switchIfEmpty(ServerResponse.notFound().build());
     }
 
+    private static final String AI_PERSONA_ANNOTATION = "comment-ai-autopilot.nxxy335.top/ai-persona";
+
+    private Mono<String> getPersonaNameFromComment(String commentName) {
+        return client.fetch(Comment.class, commentName)
+            .flatMap(comment -> {
+                var subjectRef = comment.getSpec().getSubjectRef();
+                if (subjectRef == null || !"Post".equals(subjectRef.getKind())) {
+                    return Mono.justOrEmpty(null);
+                }
+                String postName = subjectRef.getName();
+                return client.fetch(Post.class, postName)
+                    .mapNotNull(post -> {
+                        var annotations = post.getMetadata().getAnnotations();
+                        if (annotations != null) {
+                            String persona = annotations.get(AI_PERSONA_ANNOTATION);
+                            if (persona != null && !persona.isBlank()) {
+                                return persona;
+                            }
+                        }
+                        return null;
+                    });
+            })
+            .defaultIfEmpty("");
+    }
+
     private Mono<Reply> findReplyForRecord(AiCommentReply record) {
         // Find the Reply that belongs to the same comment and was created by AI
+        // If the record has a quoteReply, match by that too for precision
         return client.list(Reply.class,
                 reply -> {
                     if (!record.getSpec().getCommentId().equals(reply.getSpec().getCommentName())) {
@@ -531,7 +610,14 @@ public class CommentAiAutopilotEndpoint implements CustomEndpoint {
                     var owner = reply.getSpec().getOwner();
                     if (owner == null) return false;
                     var annotations = owner.getAnnotations();
-                    return annotations != null && "true".equals(annotations.get("comment-ai-autopilot.nxxy335.top/is-ai"));
+                    if (annotations == null || !"true".equals(annotations.get("comment-ai-autopilot.nxxy335.top/is-ai"))) {
+                        return false;
+                    }
+                    // If record has a quoteReply, also match by quoteReply for precision
+                    if (record.getSpec().getReplyTo() != null && !record.getSpec().getReplyTo().isBlank()) {
+                        return record.getSpec().getReplyTo().equals(reply.getSpec().getQuoteReply());
+                    }
+                    return true;
                 },
                 null)
             .next()
@@ -586,4 +672,97 @@ public class CommentAiAutopilotEndpoint implements CustomEndpoint {
                     .bodyValue(Map.of("message", "清理失败: " + e.getMessage()));
             });
     }
+
+    private Mono<ServerResponse> health(ServerRequest request) {
+        AiFoundationClient aiClient = aiFoundationClientProvider.getIfAvailable();
+        boolean aiFoundationInstalled = aiClient != null;
+
+        if (!aiFoundationInstalled) {
+            return ServerResponse.ok().bodyValue(
+                new HealthResponse(false, false, false, "", "unhealthy"));
+        }
+
+        // AI Foundation is installed, check if it's enabled and model is available
+        return aiClient.chat("ping", null)
+            .map(response -> (HealthResponse) new HealthResponse(true, true, true, "default", "healthy"))
+            .onErrorResume(e -> {
+                log.debug("Health check: AI Foundation call failed: {}", e.getMessage());
+                return Mono.just(new HealthResponse(true, true, false, "", "degraded"));
+            })
+            .flatMap(health -> ServerResponse.ok().bodyValue(health));
+    }
+
+    public record HealthResponse(
+        boolean aiFoundationInstalled,
+        boolean aiFoundationEnabled,
+        boolean modelAvailable,
+        String modelName,
+        String status
+    ) {}
+
+    private Mono<ServerResponse> listPersonas(ServerRequest request) {
+        return client.listAll(AiPersona.class, ListOptions.builder().build(), Sort.unsorted())
+            .collectList()
+            .flatMap(personas -> ServerResponse.ok().bodyValue(personas));
+    }
+
+    private Mono<ServerResponse> getPersonaByName(ServerRequest request) {
+        var name = request.pathVariable("name");
+        return client.fetch(AiPersona.class, name)
+            .flatMap(persona -> ServerResponse.ok().bodyValue(persona))
+            .switchIfEmpty(ServerResponse.notFound().build());
+    }
+
+    private Mono<ServerResponse> createPersona(ServerRequest request) {
+        return request.bodyToMono(AiPersona.class)
+            .flatMap(persona -> {
+                if (persona.getMetadata() == null) {
+                    persona.setMetadata(new run.halo.app.extension.Metadata());
+                }
+                if (persona.getMetadata().getName() == null || persona.getMetadata().getName().isBlank()) {
+                    persona.getMetadata().setName("ai-persona-" + java.util.UUID.randomUUID().toString().substring(0, 8));
+                }
+                return client.create(persona)
+                    .flatMap(created -> ServerResponse.ok().bodyValue(created))
+                    .onErrorResume(e -> {
+                        log.warn("Failed to create persona: {}", e.getMessage());
+                        return ServerResponse.badRequest()
+                            .bodyValue(Map.of("message", "创建角色失败: " + e.getMessage()));
+                    });
+            })
+            .switchIfEmpty(ServerResponse.badRequest()
+                .bodyValue(Map.of("message", "请求体不能为空")));
+    }
+
+    private Mono<ServerResponse> updatePersona(ServerRequest request) {
+        var name = request.pathVariable("name");
+        return request.bodyToMono(AiPersona.class)
+            .flatMap(updatedPersona -> client.fetch(AiPersona.class, name)
+                .flatMap(existing -> {
+                    existing.setSpec(updatedPersona.getSpec());
+                    return client.update(existing);
+                })
+                .flatMap(saved -> ServerResponse.ok().bodyValue(saved))
+                .onErrorResume(e -> {
+                    log.warn("Failed to update persona {}: {}", name, e.getMessage());
+                    return ServerResponse.badRequest()
+                        .bodyValue(Map.of("message", "更新角色失败: " + e.getMessage()));
+                })
+            )
+            .switchIfEmpty(ServerResponse.notFound().build());
+    }
+
+    private Mono<ServerResponse> deletePersona(ServerRequest request) {
+        var name = request.pathVariable("name");
+        return client.fetch(AiPersona.class, name)
+            .flatMap(persona -> {
+                if (persona.getSpec() != null && Boolean.TRUE.equals(persona.getSpec().getIsDefault())) {
+                    return ServerResponse.badRequest()
+                        .bodyValue(Map.of("message", "默认角色不可删除，请先将其他角色设为默认"));
+                }
+                return client.delete(persona)
+                    .then(ServerResponse.ok().bodyValue(Map.of("message", "deleted")));
+            })
+            .switchIfEmpty(ServerResponse.notFound().build());
+    }
 }

src/main/java/top/nxxy335/commentaiautopilot/extension/AiCommentReply.java

@@ -56,5 +56,8 @@ public class AiCommentReply extends AbstractExtension {
 
         @Schema(description = "评论情感倾向: POSITIVE/NEUTRAL/NEGATIVE")
         private String sentiment;
+
+        @Schema(description = "使用的AI角色名称")
+        private String personaName;
     }
 }

src/main/java/top/nxxy335/commentaiautopilot/extension/AiPersona.java

@@ -0,0 +1,41 @@
+package top.nxxy335.commentaiautopilot.extension;
+
+import com.fasterxml.jackson.annotation.JsonProperty;
+import io.swagger.v3.oas.annotations.media.Schema;
+import lombok.Data;
+import lombok.EqualsAndHashCode;
+import run.halo.app.extension.AbstractExtension;
+import run.halo.app.extension.GVK;
+
+@Data
+@EqualsAndHashCode(callSuper = true)
+@GVK(
+    group = "comment-ai-autopilot.nxxy335.top",
+    version = "v1alpha1",
+    kind = "AiPersona",
+    plural = "aipersonas",
+    singular = "aipersona"
+)
+public class AiPersona extends AbstractExtension {
+
+    @Schema(requiredMode = Schema.RequiredMode.REQUIRED)
+    private AiPersonaSpec spec;
+
+    @Data
+    @Schema(name = "AiPersonaSpec")
+    public static class AiPersonaSpec {
+
+        @Schema(description = "角色昵称")
+        private String displayName;
+
+        @Schema(description = "人格提示词")
+        private String prompt;
+
+        @Schema(description = "邮箱（用于Gravatar头像）")
+        private String email;
+
+        @Schema(description = "是否为默认角色")
+        @JsonProperty("isDefault")
+        private Boolean isDefault;
+    }
+}

src/main/java/top/nxxy335/commentaiautopilot/listener/AiPersonaReconciler.java

@@ -0,0 +1,31 @@
+package top.nxxy335.commentaiautopilot.listener;
+
+import lombok.RequiredArgsConstructor;
+import lombok.extern.slf4j.Slf4j;
+import org.springframework.stereotype.Component;
+import run.halo.app.extension.ReactiveExtensionClient;
+import run.halo.app.extension.controller.Controller;
+import run.halo.app.extension.controller.ControllerBuilder;
+import run.halo.app.extension.controller.Reconciler;
+import top.nxxy335.commentaiautopilot.extension.AiPersona;
+
+@Component
+@Slf4j
+@RequiredArgsConstructor
+public class AiPersonaReconciler implements Reconciler<Reconciler.Request> {
+
+    private final ReactiveExtensionClient client;
+
+    @Override
+    public Result reconcile(Request request) {
+        return new Result(false, null);
+    }
+
+    @Override
+    public Controller setupWith(ControllerBuilder builder) {
+        return builder
+            .extension(new AiPersona())
+            .syncAllOnStart(false)
+            .build();
+    }
+}

src/main/java/top/nxxy335/commentaiautopilot/listener/CommentReconciler.java

@@ -5,6 +5,7 @@ import lombok.extern.slf4j.Slf4j;
 import org.springframework.stereotype.Component;
 import reactor.core.scheduler.Schedulers;
 import run.halo.app.core.extension.content.Comment;
+import run.halo.app.core.extension.content.Post;
 import run.halo.app.extension.ExtensionClient;
 import run.halo.app.extension.controller.Controller;
 import run.halo.app.extension.controller.ControllerBuilder;
@@ -29,6 +30,7 @@ public class CommentReconciler implements Reconciler<Reconciler.Request> {
     private static final String PROCESSED_ANNOTATION = "comment-ai-autopilot.nxxy335.top/processed";
     private static final String AI_MARKER_ANNOTATION = "comment-ai-autopilot.nxxy335.top/is-ai";
     private static final String AI_PERSONA_OWNER_PREFIX = "ai-persona-";
+    private static final String AI_PERSONA_ANNOTATION = "comment-ai-autopilot.nxxy335.top/ai-persona";
 
     // Record the time when this bean was created (plugin startup time)
     private final Instant pluginStartTime = Instant.now();
@@ -88,10 +90,13 @@ public class CommentReconciler implements Reconciler<Reconciler.Request> {
                 markProcessed(comment);
                 client.update(comment);
 
+                // Read persona name from the post's annotations
+                String personaName = getPersonaNameFromComment(comment);
+
                 // Top-level comment → always trigger AI reply
-                log.info("[CommentReconciler] New top-level comment detected: {}", name);
+                log.info("[CommentReconciler] New top-level comment detected: {}, personaName: {}", name, personaName);
                 asyncStarted.set(true);
-                orchestrator.processComment(name, null, false)
+                orchestrator.processComment(name, null, false, personaName)
                     .subscribeOn(Schedulers.boundedElastic())
                     .doFinally(signal -> {
                         processingLocks.remove(name);
@@ -132,6 +137,29 @@ public class CommentReconciler implements Reconciler<Reconciler.Request> {
         return false;
     }
 
+    /**
+     * Read persona name from the post's annotations associated with this comment.
+     */
+    private String getPersonaNameFromComment(Comment comment) {
+        var subjectRef = comment.getSpec().getSubjectRef();
+        if (subjectRef == null || !"Post".equals(subjectRef.getKind())) {
+            return null;
+        }
+        String postName = subjectRef.getName();
+        return client.fetch(Post.class, postName)
+            .map(post -> {
+                var annotations = post.getMetadata().getAnnotations();
+                if (annotations != null) {
+                    String persona = annotations.get(AI_PERSONA_ANNOTATION);
+                    if (persona != null && !persona.isBlank()) {
+                        return persona;
+                    }
+                }
+                return null;
+            })
+            .orElse(null);
+    }
+
     private boolean isProcessed(Map<String, String> annotations) {
         return annotations != null && "true".equals(annotations.get(PROCESSED_ANNOTATION));
     }

src/main/java/top/nxxy335/commentaiautopilot/listener/ReplyReconciler.java

@@ -4,6 +4,8 @@ import lombok.RequiredArgsConstructor;
 import lombok.extern.slf4j.Slf4j;
 import org.springframework.stereotype.Component;
 import reactor.core.scheduler.Schedulers;
+import run.halo.app.core.extension.content.Comment;
+import run.halo.app.core.extension.content.Post;
 import run.halo.app.core.extension.content.Reply;
 import run.halo.app.extension.ExtensionClient;
 import run.halo.app.extension.controller.Controller;
@@ -27,6 +29,7 @@ public class ReplyReconciler implements Reconciler<Reconciler.Request> {
     private static final String PROCESSED_ANNOTATION = "comment-ai-autopilot.nxxy335.top/processed";
     private static final String AI_PERSONA_OWNER_PREFIX = "ai-persona-";
     private static final String AI_MARKER_ANNOTATION = "comment-ai-autopilot.nxxy335.top/is-ai";
+    private static final String AI_PERSONA_ANNOTATION = "comment-ai-autopilot.nxxy335.top/ai-persona";
 
     // Record the time when this bean was created (plugin startup time)
     private final Instant pluginStartTime = Instant.now();
@@ -109,8 +112,9 @@ public class ReplyReconciler implements Reconciler<Reconciler.Request> {
             client.update(reply);
 
             // Reply to AI → trigger AI reply (conversation continuation)
-            log.info("[ReplyReconciler] Reply to AI detected: {}, triggering conversation", name);
-            orchestrator.processComment(parentCommentName, name, true)
+            String personaName = getPersonaNameFromComment(parentCommentName);
+            log.info("[ReplyReconciler] Reply to AI detected: {}, triggering conversation, personaName: {}", name, personaName);
+            orchestrator.processComment(parentCommentName, name, true, personaName)
                 .subscribeOn(Schedulers.boundedElastic())
                 .subscribe(
                     null,
@@ -142,6 +146,33 @@ public class ReplyReconciler implements Reconciler<Reconciler.Request> {
             .orElse(false);
     }
 
+    /**
+     * Read persona name from the post's annotations associated with the parent comment.
+     */
+    private String getPersonaNameFromComment(String commentName) {
+        return client.fetch(Comment.class, commentName)
+            .map(comment -> {
+                var subjectRef = comment.getSpec().getSubjectRef();
+                if (subjectRef == null || !"Post".equals(subjectRef.getKind())) {
+                    return null;
+                }
+                String postName = subjectRef.getName();
+                return client.fetch(Post.class, postName)
+                    .map(post -> {
+                        var annotations = post.getMetadata().getAnnotations();
+                        if (annotations != null) {
+                            String persona = annotations.get(AI_PERSONA_ANNOTATION);
+                            if (persona != null && !persona.isBlank()) {
+                                return persona;
+                            }
+                        }
+                        return null;
+                    })
+                    .orElse(null);
+            })
+            .orElse(null);
+    }
+
     private boolean isProcessed(Map<String, String> annotations) {
         return annotations != null && "true".equals(annotations.get(PROCESSED_ANNOTATION));
     }

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

@@ -49,7 +49,7 @@ public class AiReplyCleanupService implements DisposableBean {
                     if (cleanupJson == null || cleanupJson.isBlank()) return true;
                     try {
                         JsonNode node = objectMapper.readTree(cleanupJson);
-                        return node.has("cleanupEnabled") && node.get("cleanupEnabled").asBoolean(true);
+                        return !node.has("cleanupEnabled") || node.get("cleanupEnabled").asBoolean(true);
                     } catch (Exception e) {
                         log.warn("[Cleanup] Failed to parse cleanup config: {}", e.getMessage());
                         return true;

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

@@ -7,6 +7,7 @@ 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.Reply;
 import run.halo.app.extension.ConfigMap;
 import run.halo.app.extension.Metadata;
 import run.halo.app.extension.ReactiveExtensionClient;
@@ -29,6 +30,7 @@ public class AiReplyOrchestrator {
     private final ReviewService reviewService;
     private final CommentReplyPublisher commentReplyPublisher;
     private final FilterService filterService;
+    private final RateLimitService rateLimitService;
     private final ReactiveExtensionClient client;
     private final ObjectMapper objectMapper;
 
@@ -43,6 +45,7 @@ public class AiReplyOrchestrator {
                                ReviewService reviewService,
                                CommentReplyPublisher commentReplyPublisher,
                                FilterService filterService,
+                               RateLimitService rateLimitService,
                                ReactiveExtensionClient client) {
         this.contextExtractor = contextExtractor;
         this.promptBuilder = promptBuilder;
@@ -51,6 +54,7 @@ public class AiReplyOrchestrator {
         this.reviewService = reviewService;
         this.commentReplyPublisher = commentReplyPublisher;
         this.filterService = filterService;
+        this.rateLimitService = rateLimitService;
         this.client = client;
         this.objectMapper = new ObjectMapper();
     }
@@ -61,8 +65,10 @@ public class AiReplyOrchestrator {
      * @param commentName     the parent Comment name
      * @param replyName       the Reply name that triggered this (null for top-level comments)
      * @param isAiConversation true when someone replied to AI's reply (conversation continuation)
+     * @param personaName     the persona name to use (null for default persona)
      */
-    public Mono<Void> processComment(String commentName, String replyName, boolean isAiConversation) {
+    public Mono<Void> processComment(String commentName, String replyName, boolean isAiConversation,
+                                      String personaName) {
         String lockKey = isAiConversation ? commentName + ":conv:" + replyName : commentName + ":top";
 
         // In-memory dedup: if already processing, skip immediately
@@ -71,8 +77,8 @@ public class AiReplyOrchestrator {
             return Mono.empty();
         }
 
-        log.info("[Orchestrator] Start processing: comment={}, replyName={}, isAiConversation={}",
-            commentName, replyName, isAiConversation);
+        log.info("[Orchestrator] Start processing: comment={}, replyName={}, isAiConversation={}, personaName={}",
+            commentName, replyName, isAiConversation, personaName);
 
         return isAutoReplyEnabled()
             .flatMap(enabled -> {
@@ -80,12 +86,18 @@ public class AiReplyOrchestrator {
                     log.info("[Orchestrator] Auto reply disabled, skipping: {}", commentName);
                     return Mono.empty();
                 }
-                return filterService.shouldProcess(commentName)
-                    .flatMap(shouldProcess -> {
-                        if (!shouldProcess) {
-                            log.info("[Orchestrator] Filtered out by rules: {}", commentName);
+                return getRateLimit()
+                    .flatMap(rateLimit -> {
+                        if (!rateLimitService.tryAcquire(rateLimit)) {
+                            log.info("[Orchestrator] 速率限制，跳过: {}", commentName);
                             return Mono.empty();
                         }
+                        return filterService.shouldProcess(commentName)
+                            .flatMap(shouldProcess -> {
+                                if (!shouldProcess) {
+                                    log.info("[Orchestrator] Filtered out by rules: {}", commentName);
+                                    return Mono.empty();
+                                }
                         // For top-level comments: skip if we already have ANY reply record
                         // For AI conversation: skip if we already replied to THIS specific reply
                         if (!isAiConversation) {
@@ -95,16 +107,27 @@ public class AiReplyOrchestrator {
                                         log.info("[Orchestrator] Already have reply record for: {}, skipping", commentName);
                                         return Mono.empty();
                                     }
-                                    return doProcess(commentName, replyName, isAiConversation);
+                                    return doProcess(commentName, replyName, isAiConversation, personaName);
                                 });
                         }
-                        return hasExistingConversationReply(replyName)
-                            .flatMap(hasReply -> {
-                                if (hasReply) {
-                                    log.info("[Orchestrator] Already replied to reply: {}, skipping", replyName);
-                                    return Mono.empty();
-                                }
-                                return doProcess(commentName, replyName, isAiConversation);
+                        // Check conversation rounds limit
+                        return getMaxConversationRounds()
+                            .flatMap(maxRounds -> getConversationRounds(commentName)
+                                .flatMap(rounds -> {
+                                    if (rounds >= maxRounds) {
+                                        log.info("[Orchestrator] 对话轮次已达上限({}/{}), 跳过: {}", rounds, maxRounds, commentName);
+                                        return Mono.empty();
+                                    }
+                                    return hasExistingConversationReply(replyName)
+                                        .flatMap(hasReply -> {
+                                            if (hasReply) {
+                                                log.info("[Orchestrator] Already replied to reply: {}, skipping", replyName);
+                                                return Mono.empty();
+                                            }
+                                            return doProcess(commentName, replyName, isAiConversation, personaName);
+                                        });
+                                })
+                            );
                             });
                     });
             })
@@ -117,16 +140,17 @@ public class AiReplyOrchestrator {
             .then();
     }
 
-    private Mono<Void> doProcess(String commentName, String replyName, boolean isAiConversation) {
+    private Mono<Void> doProcess(String commentName, String replyName, boolean isAiConversation,
+                                  String personaName) {
         return getModelName().flatMap(modelName ->
             contextExtractor.extract(commentName, replyName, isAiConversation)
                 .flatMap(context -> sentimentService.analyzeSentiment(context.commentContent(), modelName)
                     .flatMap(sentimentResult -> {
                         log.info("[Orchestrator] Sentiment for {}: {} (confidence: {})",
                             commentName, sentimentResult.sentiment(), sentimentResult.confidence());
-                        return promptBuilder.buildPrompt(context, sentimentResult.sentiment())
-                            .flatMap(prompt -> createAiCommentReply(context, sentimentResult.sentiment())
-                                .flatMap(replyRecord -> generateAndPublish(prompt, context, replyRecord, modelName))
+                        return promptBuilder.buildPrompt(context, sentimentResult.sentiment(), personaName)
+                            .flatMap(prompt -> createAiCommentReply(context, sentimentResult.sentiment(), personaName)
+                                .flatMap(replyRecord -> generateAndPublish(prompt, context, replyRecord, modelName, personaName))
                             );
                     })
                 )
@@ -175,13 +199,14 @@ public class AiReplyOrchestrator {
      * Includes retry logic for empty AI replies and review failures.
      */
     private Mono<Void> generateAndPublish(String prompt, ContextExtractor.CommentContext context,
-                                           AiCommentReply replyRecord, String modelName) {
+                                           AiCommentReply replyRecord, String modelName,
+                                           String personaName) {
         return aiReplyService.generateReply(prompt, modelName)
             .defaultIfEmpty("")
             .flatMap(aiReply -> {
                 if (aiReply.isBlank()) {
                     log.warn("[Orchestrator] AI generated empty reply for: {}", context.commentId());
-                    return retryOrFail(replyRecord, context, modelName, "AI generated empty reply");
+                    return retryOrFail(replyRecord, context, modelName, personaName, "AI generated empty reply");
                 }
 
                 log.info("[Orchestrator] AI generated reply for {}: {} chars",
@@ -196,16 +221,16 @@ public class AiReplyOrchestrator {
                                 context.commentId());
                             // Save the failed reply content, then retry
                             return updateRecord(replyRecord, aiReply, 0, "FAIL", false)
-                                .then(retryOrFail(replyRecord, context, modelName, "Content safety review failed"));
+                                .then(retryOrFail(replyRecord, context, modelName, personaName, "Content safety review failed"));
                         }
-                        return publishReply(context, aiReply, replyRecord, reviewResult.score());
+                        return publishReply(context, aiReply, replyRecord, reviewResult.score(), personaName);
                     })
                     .switchIfEmpty(
-                        publishReply(context, aiReply, replyRecord, 100)
+                        publishReply(context, aiReply, replyRecord, 100, personaName)
                     )
                     .onErrorResume(e -> {
                         log.warn("[Orchestrator] Review error, auto-passing: {}", e.getMessage());
-                        return publishReply(context, aiReply, replyRecord, 100);
+                        return publishReply(context, aiReply, replyRecord, 100, personaName);
                     });
             });
     }
@@ -219,6 +244,7 @@ public class AiReplyOrchestrator {
     private Mono<Void> retryOrFail(AiCommentReply replyRecord,
                                     ContextExtractor.CommentContext context,
                                     String modelName,
+                                    String personaName,
                                     String reason) {
         return getMaxRetryCount().flatMap(maxRetry -> {
             int currentRetryCount = replyRecord.getSpec().getRetryCount() != null
@@ -233,7 +259,7 @@ public class AiReplyOrchestrator {
                 // Update retryCount and reset status to PENDING
                 return updateRecordForRetry(replyRecord, newRetryCount)
                     .delayElement(Duration.ofSeconds(delaySeconds))
-                    .then(retryGenerate(context, replyRecord, modelName));
+                    .then(retryGenerate(context, replyRecord, modelName, personaName));
             } else {
                 log.warn("[Orchestrator] Max retry count ({}) exceeded for: {}, marking as FAIL. Reason: {}",
                     maxRetry, context.commentId(), reason);
@@ -248,10 +274,11 @@ public class AiReplyOrchestrator {
      */
     private Mono<Void> retryGenerate(ContextExtractor.CommentContext context,
                                       AiCommentReply replyRecord,
-                                      String modelName) {
+                                      String modelName,
+                                      String personaName) {
         return sentimentService.analyzeSentiment(context.commentContent(), modelName)
-            .flatMap(sentimentResult -> promptBuilder.buildPrompt(context, sentimentResult.sentiment())
-                .flatMap(prompt -> generateAndPublish(prompt, context, replyRecord, modelName))
+            .flatMap(sentimentResult -> promptBuilder.buildPrompt(context, sentimentResult.sentiment(), personaName)
+                .flatMap(prompt -> generateAndPublish(prompt, context, replyRecord, modelName, personaName))
             );
     }
 
@@ -281,11 +308,11 @@ public class AiReplyOrchestrator {
      * Publish the reply and update the record to PASS + published=true.
      */
     private Mono<Void> publishReply(ContextExtractor.CommentContext context, String aiReply,
-                                     AiCommentReply replyRecord, int score) {
+                                     AiCommentReply replyRecord, int score, String personaName) {
         return isAutoPublishEnabled()
             .flatMap(autoPublish -> {
                 return commentReplyPublisher.publishReply(
-                        context.commentId(), aiReply, context.postId(), context.replyTo(), autoPublish)
+                        context.commentId(), aiReply, context.postId(), context.replyTo(), autoPublish, personaName)
                     .flatMap(publishedReply -> {
                         log.info("[Orchestrator] Reply {} for: {}", autoPublish ? "published" : "saved as draft", context.commentId());
                         return updateRecord(replyRecord, aiReply, score, "PASS", autoPublish);
@@ -394,7 +421,78 @@ public class AiReplyOrchestrator {
             .defaultIfEmpty(3);
     }
 
-    private Mono<AiCommentReply> createAiCommentReply(ContextExtractor.CommentContext context, String sentiment) {
+    private Mono<Integer> getMaxConversationRounds() {
+        return client.fetch(ConfigMap.class, CONFIG_MAP_NAME)
+            .mapNotNull(cm -> {
+                var data = cm.getData();
+                if (data == null) return null;
+                String basicJson = data.get("basic");
+                if (basicJson == null || basicJson.isBlank()) return null;
+                try {
+                    JsonNode node = objectMapper.readTree(basicJson);
+                    if (node.has("maxConversationRounds")) {
+                        return node.get("maxConversationRounds").asInt(8);
+                    }
+                } catch (Exception e) {
+                    log.warn("[Orchestrator] Failed to parse maxConversationRounds from ConfigMap: {}", e.getMessage());
+                }
+                return null;
+            })
+            .onErrorResume(e -> {
+                log.debug("[Orchestrator] Failed to fetch maxConversationRounds setting from ConfigMap: {}", e.getMessage());
+                return Mono.empty();
+            })
+            .defaultIfEmpty(8);
+    }
+
+    private Mono<Integer> getConversationRounds(String commentName) {
+        return client.list(Reply.class,
+                reply -> {
+                    if (!commentName.equals(reply.getSpec().getCommentName())) {
+                        return false;
+                    }
+                    var owner = reply.getSpec().getOwner();
+                    if (owner == null) return false;
+                    // Check AI annotation marker (CommentReplyPublisher sets this on all AI replies)
+                    var annotations = owner.getAnnotations();
+                    return annotations != null
+                        && "true".equals(annotations.get("comment-ai-autopilot.nxxy335.top/is-ai"));
+                },
+                null)
+            .collectList()
+            .map(replies -> replies.size())
+            .onErrorResume(e -> {
+                log.warn("[Orchestrator] Failed to count conversation rounds: {}", e.getMessage());
+                return Mono.just(0);
+            });
+    }
+
+    private Mono<Integer> getRateLimit() {
+        return client.fetch(ConfigMap.class, CONFIG_MAP_NAME)
+            .mapNotNull(cm -> {
+                var data = cm.getData();
+                if (data == null) return null;
+                String basicJson = data.get("basic");
+                if (basicJson == null || basicJson.isBlank()) return null;
+                try {
+                    JsonNode node = objectMapper.readTree(basicJson);
+                    if (node.has("rateLimitPerMinute")) {
+                        return node.get("rateLimitPerMinute").asInt(10);
+                    }
+                } catch (Exception e) {
+                    log.warn("[Orchestrator] Failed to parse rateLimitPerMinute from ConfigMap: {}", e.getMessage());
+                }
+                return null;
+            })
+            .onErrorResume(e -> {
+                log.debug("[Orchestrator] Failed to fetch rateLimitPerMinute setting from ConfigMap: {}", e.getMessage());
+                return Mono.empty();
+            })
+            .defaultIfEmpty(10);
+    }
+
+    private Mono<AiCommentReply> createAiCommentReply(ContextExtractor.CommentContext context, String sentiment,
+                                                        String personaName) {
         AiCommentReply record = new AiCommentReply();
         record.setMetadata(new Metadata());
         record.getMetadata().setName("ai-reply-" + UUID.randomUUID().toString().substring(0, 8));
@@ -410,6 +508,7 @@ public class AiReplyOrchestrator {
         record.getSpec().setIsAiConversation(context.isAiConversation());
         record.getSpec().setPublished(false);
         record.getSpec().setSentiment(sentiment);
+        record.getSpec().setPersonaName(personaName);
         return client.create(record)
             .doOnSuccess(created -> log.info("[Orchestrator] Created AiCommentReply record: {}",
                 created.getMetadata().getName()));

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

@@ -1,15 +1,13 @@
 package top.nxxy335.commentaiautopilot.service;
 
-import com.fasterxml.jackson.databind.JsonNode;
-import com.fasterxml.jackson.databind.ObjectMapper;
 import lombok.extern.slf4j.Slf4j;
 import org.springframework.stereotype.Component;
 import reactor.core.publisher.Mono;
 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.Metadata;
 import run.halo.app.extension.ReactiveExtensionClient;
+import top.nxxy335.commentaiautopilot.extension.AiPersona;
 
 import java.nio.charset.StandardCharsets;
 import java.security.MessageDigest;
@@ -23,24 +21,23 @@ import java.util.UUID;
 public class CommentReplyPublisher {
 
     private final ReactiveExtensionClient client;
-    private final ObjectMapper objectMapper;
 
     public CommentReplyPublisher(ReactiveExtensionClient client) {
         this.client = client;
-        this.objectMapper = new ObjectMapper();
     }
 
-    private static final String DEFAULT_PERSONA_NAME = "小回";
     private static final String AI_PERSONA_OWNER_PREFIX = "ai-persona-";
-    private static final String CONFIG_MAP_NAME = "comment-ai-autopilot-configmap";
 
     /**
      * Publish a reply to a comment automatically using AI Persona identity.
      * Includes a final dedup check: if an AI reply already exists for this comment,
      * skip publishing to prevent duplicate replies.
+     *
+     * @param personaName the persona name to use (null for default persona)
      */
     public Mono<Reply> publishReply(String parentCommentName, String replyContent,
-                                     String postName, String quoteReplyName, boolean autoPublish) {
+                                     String postName, String quoteReplyName, boolean autoPublish,
+                                     String personaName) {
         return checkExistingAiReply(parentCommentName, quoteReplyName)
             .flatMap(exists -> {
                 if (exists) {
@@ -48,7 +45,7 @@ public class CommentReplyPublisher {
                         parentCommentName);
                     return Mono.empty();
                 }
-                return doPublish(parentCommentName, replyContent, postName, quoteReplyName, autoPublish);
+                return doPublish(parentCommentName, replyContent, postName, quoteReplyName, autoPublish, personaName);
             });
     }
 
@@ -82,109 +79,88 @@ public class CommentReplyPublisher {
     }
 
     private Mono<Reply> doPublish(String parentCommentName, String replyContent,
-                                   String postName, String quoteReplyName, boolean autoPublish) {
-        return getPersonaName().flatMap(personaName ->
-            getPersonaEmail().flatMap(email -> {
-                Reply reply = new Reply();
-                reply.setMetadata(new Metadata());
-                reply.getMetadata().setName(generateReplyName());
-                reply.setSpec(new Reply.ReplySpec());
+                                   String postName, String quoteReplyName, boolean autoPublish,
+                                   String personaName) {
+        return resolvePersona(personaName).flatMap(persona -> {
+            String displayName = persona.displayName();
+            String email = persona.email();
 
-                var spec = reply.getSpec();
-                spec.setCommentName(parentCommentName);
-                spec.setRaw(replyContent);
-                spec.setContent(replyContent);
-                spec.setApproved(autoPublish);
-                if (autoPublish) {
-                    spec.setApprovedTime(Instant.now());
-                }
-                spec.setPriority(0);
-                spec.setTop(false);
-                spec.setAllowNotification(false);
-                spec.setHidden(false);
+            Reply reply = new Reply();
+            reply.setMetadata(new Metadata());
+            reply.getMetadata().setName(generateReplyName());
+            reply.setSpec(new Reply.ReplySpec());
 
-                if (quoteReplyName != null && !quoteReplyName.isBlank()) {
-                    spec.setQuoteReply(quoteReplyName);
-                }
+            var spec = reply.getSpec();
+            spec.setCommentName(parentCommentName);
+            spec.setRaw(replyContent);
+            spec.setContent(replyContent);
+            spec.setApproved(autoPublish);
+            if (autoPublish) {
+                spec.setApprovedTime(Instant.now());
+            }
+            spec.setPriority(0);
+            spec.setTop(false);
+            spec.setAllowNotification(false);
+            spec.setHidden(false);
 
-                var owner = new Comment.CommentOwner();
-                owner.setKind(Comment.CommentOwner.KIND_EMAIL);
-                if (email != null && !email.isBlank()) {
-                    owner.setName(email);
-                } else {
-                    owner.setName(AI_PERSONA_OWNER_PREFIX + personaName);
-                }
-                owner.setDisplayName(personaName + " AI");
+            if (quoteReplyName != null && !quoteReplyName.isBlank()) {
+                spec.setQuoteReply(quoteReplyName);
+            }
 
-                Map<String, String> ownerAnnotations = new HashMap<>();
-                ownerAnnotations.put("comment-ai-autopilot.nxxy335.top/is-ai", "true");
-                if (email != null && !email.isBlank()) {
-                    String gravatarUrl = generateGravatarUrl(email);
-                    ownerAnnotations.put(Comment.CommentOwner.AVATAR_ANNO, gravatarUrl);
-                }
-                owner.setAnnotations(ownerAnnotations);
-                spec.setOwner(owner);
+            var owner = new Comment.CommentOwner();
+            owner.setKind(Comment.CommentOwner.KIND_EMAIL);
+            if (email != null && !email.isBlank()) {
+                owner.setName(email);
+            } else {
+                owner.setName(AI_PERSONA_OWNER_PREFIX + displayName);
+            }
+            owner.setDisplayName(displayName + " AI");
 
-                return client.create(reply)
-                    .doOnSuccess(created -> log.info("[Publisher] AI Persona '{}' reply published for comment: {}, quoteReply: {}",
-                        personaName, parentCommentName, quoteReplyName))
-                    .doOnError(e -> log.error("[Publisher] Failed to publish AI reply: {}", e.getMessage()));
-            })
-        );
+            Map<String, String> ownerAnnotations = new HashMap<>();
+            ownerAnnotations.put("comment-ai-autopilot.nxxy335.top/is-ai", "true");
+            if (email != null && !email.isBlank()) {
+                String gravatarUrl = generateGravatarUrl(email);
+                ownerAnnotations.put(Comment.CommentOwner.AVATAR_ANNO, gravatarUrl);
+            }
+            owner.setAnnotations(ownerAnnotations);
+            spec.setOwner(owner);
+
+            return client.create(reply)
+                .doOnSuccess(created -> log.info("[Publisher] AI Persona '{}' reply published for comment: {}, quoteReply: {}",
+                    displayName, parentCommentName, quoteReplyName))
+                .doOnError(e -> log.error("[Publisher] Failed to publish AI reply: {}", e.getMessage()));
+        });
     }
 
     /**
-     * Read persona setting directly from ConfigMap to avoid ClassLoader conflict.
-     * Halo's ReactiveSettingFetcher returns JsonNode loaded by the main app ClassLoader,
-     * which is incompatible with the plugin's PluginClassLoader, causing ClassCastException.
+     * Resolve persona info from AiPersona extension.
+     * Priority:
+     * 1. If personaName is provided, fetch from AiPersona extension
+     * 2. If personaName is empty, find the default AiPersona (isDefault=true)
+     * 3. If no AiPersona found, return default "小回" with empty email
      */
-    private Mono<String> getPersonaName() {
-        return client.fetch(ConfigMap.class, CONFIG_MAP_NAME)
-            .mapNotNull(cm -> {
-                var data = cm.getData();
-                if (data == null) return null;
-                String personaJson = data.get("persona");
-                if (personaJson == null || personaJson.isBlank()) return null;
-                try {
-                    JsonNode node = objectMapper.readTree(personaJson);
-                    JsonNode nameNode = node.get("personaName");
-                    if (nameNode != null && !nameNode.asText().isBlank()) {
-                        return nameNode.asText();
-                    }
-                } catch (Exception e) {
-                    log.warn("[Publisher] Failed to parse personaName from ConfigMap: {}", e.getMessage());
-                }
-                return null;
-            })
-            .defaultIfEmpty(DEFAULT_PERSONA_NAME);
+    private Mono<ResolvedPersona> resolvePersona(String personaName) {
+        if (personaName != null && !personaName.isBlank()) {
+            return client.fetch(AiPersona.class, personaName)
+                .map(p -> new ResolvedPersona(
+                    p.getSpec().getDisplayName(),
+                    p.getSpec().getEmail()
+                ))
+                .defaultIfEmpty(new ResolvedPersona("小回", ""));
+        }
+        // Find default persona
+        return client.list(AiPersona.class,
+                persona -> persona.getSpec() != null && Boolean.TRUE.equals(persona.getSpec().getIsDefault()),
+                null)
+            .next()
+            .map(p -> new ResolvedPersona(
+                p.getSpec().getDisplayName(),
+                p.getSpec().getEmail()
+            ))
+            .defaultIfEmpty(new ResolvedPersona("小回", ""));
     }
 
-    /**
-     * Read persona email directly from ConfigMap to avoid ClassLoader conflict.
-     */
-    private Mono<String> getPersonaEmail() {
-        return client.fetch(ConfigMap.class, CONFIG_MAP_NAME)
-            .mapNotNull(cm -> {
-                var data = cm.getData();
-                if (data == null) return null;
-                String personaJson = data.get("persona");
-                if (personaJson == null || personaJson.isBlank()) return null;
-                try {
-                    JsonNode node = objectMapper.readTree(personaJson);
-                    JsonNode emailNode = node.get("personaEmail");
-                    if (emailNode != null && !emailNode.asText().isBlank()) {
-                        String email = emailNode.asText().trim().toLowerCase();
-                        log.info("[Publisher] personaEmail resolved from ConfigMap: {}", email);
-                        return email;
-                    }
-                    log.info("[Publisher] personaEmail is blank in ConfigMap");
-                } catch (Exception e) {
-                    log.warn("[Publisher] Failed to parse personaEmail from ConfigMap: {}", e.getMessage());
-                }
-                return null;
-            })
-            .defaultIfEmpty("");
-    }
+    private record ResolvedPersona(String displayName, String email) {}
 
     private String generateReplyName() {
         return "ai-comment-reply-" + UUID.randomUUID().toString().substring(0, 8);

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

@@ -51,17 +51,21 @@ public class ContextExtractor {
             String postName = subjectRef.getName();
             return client.fetch(Post.class, postName)
                 .flatMap(post -> getPostContent(postName)
-                    .map(content -> new CommentContext(
-                        comment.getMetadata().getName(),
-                        postName,
-                        post.getSpec().getSlug(),
-                        commentContent,
-                        commentOwner,
-                        post.getSpec().getTitle(),
-                        content,
-                        null,
-                        isAiConversation
-                    ))
+                    .flatMap(content -> getCommentCount(comment.getMetadata().getName())
+                        .map(commentCount -> new CommentContext(
+                            comment.getMetadata().getName(),
+                            postName,
+                            post.getSpec().getSlug(),
+                            commentContent,
+                            commentOwner,
+                            post.getSpec().getTitle(),
+                            content,
+                            null,
+                            isAiConversation,
+                            formatPostDate(post),
+                            commentCount
+                        ))
+                    )
                 )
                 .defaultIfEmpty(new CommentContext(
                     comment.getMetadata().getName(),
@@ -72,7 +76,9 @@ public class ContextExtractor {
                     "",
                     "",
                     null,
-                    isAiConversation
+                    isAiConversation,
+                    "",
+                    0
                 ));
         }
 
@@ -85,7 +91,9 @@ public class ContextExtractor {
             "",
             "",
             null,
-            isAiConversation
+            isAiConversation,
+            "",
+            0
         ));
     }
 
@@ -98,17 +106,21 @@ public class ContextExtractor {
             String postName = subjectRef.getName();
             return client.fetch(Post.class, postName)
                 .flatMap(post -> getPostContent(postName)
-                    .map(content -> new CommentContext(
-                        comment.getMetadata().getName(),
-                        postName,
-                        post.getSpec().getSlug(),
-                        replyContent,
-                        replyOwner,
-                        post.getSpec().getTitle(),
-                        content,
-                        reply.getMetadata().getName(),
-                        isAiConversation
-                    ))
+                    .flatMap(content -> getCommentCount(comment.getMetadata().getName())
+                        .map(commentCount -> new CommentContext(
+                            comment.getMetadata().getName(),
+                            postName,
+                            post.getSpec().getSlug(),
+                            replyContent,
+                            replyOwner,
+                            post.getSpec().getTitle(),
+                            content,
+                            reply.getMetadata().getName(),
+                            isAiConversation,
+                            formatPostDate(post),
+                            commentCount
+                        ))
+                    )
                 )
                 .defaultIfEmpty(new CommentContext(
                     comment.getMetadata().getName(),
@@ -119,7 +131,9 @@ public class ContextExtractor {
                     "",
                     "",
                     reply.getMetadata().getName(),
-                    isAiConversation
+                    isAiConversation,
+                    "",
+                    0
                 ));
         }
 
@@ -132,7 +146,9 @@ public class ContextExtractor {
             "",
             "",
             reply.getMetadata().getName(),
-            isAiConversation
+            isAiConversation,
+            "",
+            0
         ));
     }
 
@@ -197,6 +213,27 @@ public class ContextExtractor {
             .defaultIfEmpty("");
     }
 
+    private String formatPostDate(Post post) {
+        var publishTime = post.getSpec().getPublishTime();
+        if (publishTime != null) {
+            return publishTime.toString().substring(0, 10);
+        }
+        var creationTimestamp = post.getMetadata().getCreationTimestamp();
+        if (creationTimestamp != null) {
+            return creationTimestamp.toString().substring(0, 10);
+        }
+        return "";
+    }
+
+    private Mono<Integer> getCommentCount(String commentName) {
+        return client.list(Reply.class,
+                reply -> commentName.equals(reply.getSpec().getCommentName()),
+                null)
+            .collectList()
+            .map(replies -> replies.size())
+            .defaultIfEmpty(0);
+    }
+
     public record CommentContext(
         String commentId,
         String postId,
@@ -206,6 +243,8 @@ public class ContextExtractor {
         String postTitle,
         String postContent,
         String replyTo,
-        boolean isAiConversation
+        boolean isAiConversation,
+        String postDate,
+        int commentCount
     ) {}
 }

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

@@ -14,6 +14,7 @@ import run.halo.app.extension.ReactiveExtensionClient;
 import java.util.Arrays;
 import java.util.Collections;
 import java.util.List;
+import java.util.regex.Pattern;
 import java.util.stream.Collectors;
 
 @Component
@@ -151,6 +152,18 @@ public class FilterService {
 
     private boolean isInList(String value, List<String> list) {
         if (value == null || value.isEmpty() || list.isEmpty()) return false;
-        return list.stream().anyMatch(item -> item.equalsIgnoreCase(value));
+        return list.stream().anyMatch(item -> {
+            if (item.startsWith("regex:")) {
+                try {
+                    String regex = item.substring(6);
+                    Pattern pattern = Pattern.compile(regex, Pattern.CASE_INSENSITIVE);
+                    return pattern.matcher(value).matches();
+                } catch (Exception e) {
+                    log.warn("[Filter] Invalid regex pattern '{}': {}", item, e.getMessage());
+                    return false;
+                }
+            }
+            return item.equalsIgnoreCase(value);
+        });
     }
 }

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

@@ -7,6 +7,10 @@ import org.springframework.stereotype.Component;
 import reactor.core.publisher.Mono;
 import run.halo.app.extension.ConfigMap;
 import run.halo.app.extension.ReactiveExtensionClient;
+import top.nxxy335.commentaiautopilot.extension.AiPersona;
+
+import java.util.LinkedHashMap;
+import java.util.Map;
 
 @Component
 @Slf4j
@@ -21,6 +25,30 @@ public class PromptBuilder {
         this.objectMapper = new ObjectMapper();
     }
 
+    private static final String PRESET_FRIENDLY = """
+【友好型预设】你的回复应该热情友好，多用感叹号和表情符号，让评论者感到受欢迎。像朋友一样聊天，适当使用口语化表达。
+""";
+
+    private static final String PRESET_PROFESSIONAL = """
+【专业型预设】你的回复应该专业严谨，使用正式的语言风格，避免口语化表达。回复要有逻辑性，必要时引用文章中的具体内容。
+""";
+
+    private static final String PRESET_HUMOROUS = """
+【幽默型预设】你的回复可以适当加入幽默元素，使用轻松诙谐的语言，但不要过度搞笑。保持友善的同时让对话更有趣。
+""";
+
+    private static final String PRESET_CONCISE = """
+【简洁型预设】你的回复应该非常简洁，一两句话即可。不要展开讨论，直接回应评论的核心内容。
+""";
+
+    private static final Map<String, String> PRESET_MAP = new LinkedHashMap<>();
+    static {
+        PRESET_MAP.put("friendly", PRESET_FRIENDLY);
+        PRESET_MAP.put("professional", PRESET_PROFESSIONAL);
+        PRESET_MAP.put("humorous", PRESET_HUMOROUS);
+        PRESET_MAP.put("concise", PRESET_CONCISE);
+    }
+
     private static final String SAFETY_PROMPT = """
             【安全规范】
             - 内容红线：坚决不生成任何涉及暴力、歧视、辱骂、人身攻击或违反法律法规的内容。
@@ -41,6 +69,9 @@ public class PromptBuilder {
             - 自然对话，不要写小作文
             - 只有评论涉及具体内容时才针对性回应
 
+            文章标题：{{post_title}}
+            发布日期：{{post_date}}
+            评论数：{{comment_count}}
             文章（仅供理解上下文，不要复述）：
             {{article}}
 
@@ -53,14 +84,24 @@ public class PromptBuilder {
             """;
 
     public Mono<String> buildPrompt(ContextExtractor.CommentContext context) {
-        return Mono.zip(getPromptTemplate(), getPersonaPrompt())
+        return Mono.zip(getPromptTemplate(), getPersonaPrompt(null), getEnabledPresetsPrompt())
             .map(tuple -> {
                 String template = tuple.getT1();
                 String personaPrompt = tuple.getT2();
+                String presetPrompt = tuple.getT3();
+
+                // 将预设提示词合并到 persona_prompt 之后
+                String combinedPersona = personaPrompt;
+                if (presetPrompt != null && !presetPrompt.isBlank()) {
+                    combinedPersona = personaPrompt + "\n" + presetPrompt;
+                }
 
                 String prompt = template
-                    .replace("{{persona_prompt}}", personaPrompt)
+                    .replace("{{persona_prompt}}", combinedPersona)
                     .replace("{{safety_prompt}}", SAFETY_PROMPT)
+                    .replace("{{post_title}}", context.postTitle() != null ? context.postTitle() : "")
+                    .replace("{{post_date}}", context.postDate() != null ? context.postDate() : "")
+                    .replace("{{comment_count}}", String.valueOf(context.commentCount()))
                     .replace("{{article}}", context.postTitle() + "\n" + context.postContent())
                     .replace("{{comment}}", context.commentOwner() + ": " + context.commentContent());
 
@@ -69,8 +110,31 @@ public class PromptBuilder {
     }
 
     public Mono<String> buildPrompt(ContextExtractor.CommentContext context, String sentiment) {
-        return buildPrompt(context)
-            .map(prompt -> {
+        return buildPrompt(context, sentiment, null);
+    }
+
+    public Mono<String> buildPrompt(ContextExtractor.CommentContext context, String sentiment, String personaName) {
+        return Mono.zip(getPromptTemplate(), getPersonaPrompt(personaName), getEnabledPresetsPrompt())
+            .map(tuple -> {
+                String template = tuple.getT1();
+                String personaPrompt = tuple.getT2();
+                String presetPrompt = tuple.getT3();
+
+                // 将预设提示词合并到 persona_prompt 之后
+                String combinedPersona = personaPrompt;
+                if (presetPrompt != null && !presetPrompt.isBlank()) {
+                    combinedPersona = personaPrompt + "\n" + presetPrompt;
+                }
+
+                String prompt = template
+                    .replace("{{persona_prompt}}", combinedPersona)
+                    .replace("{{safety_prompt}}", SAFETY_PROMPT)
+                    .replace("{{post_title}}", context.postTitle() != null ? context.postTitle() : "")
+                    .replace("{{post_date}}", context.postDate() != null ? context.postDate() : "")
+                    .replace("{{comment_count}}", String.valueOf(context.commentCount()))
+                    .replace("{{article}}", context.postTitle() + "\n" + context.postContent())
+                    .replace("{{comment}}", context.commentOwner() + ": " + context.commentContent());
+
                 if (sentiment == null || "NEUTRAL".equals(sentiment)) {
                     return prompt;
                 }
@@ -108,28 +172,65 @@ public class PromptBuilder {
             .defaultIfEmpty(DEFAULT_PROMPT_TEMPLATE);
     }
 
-    private Mono<String> getPersonaPrompt() {
-        return client.fetch(ConfigMap.class, CONFIG_MAP_NAME)
-            .mapNotNull(cm -> {
-                var data = cm.getData();
-                if (data == null) return null;
-                String personaJson = data.get("persona");
-                if (personaJson == null || personaJson.isBlank()) return null;
-                try {
-                    JsonNode node = objectMapper.readTree(personaJson);
-                    JsonNode promptNode = node.get("personaPrompt");
-                    if (promptNode != null && !promptNode.asText().isBlank()) {
-                        return promptNode.asText();
-                    }
-                } catch (Exception e) {
-                    log.warn("Failed to parse personaPrompt from ConfigMap: {}", e.getMessage());
-                }
-                return null;
-            })
-            .onErrorResume(e -> {
-                log.debug("Failed to fetch persona prompt setting: {}", e.getMessage());
-                return Mono.just(DEFAULT_PERSONA_PROMPT);
+    private Mono<String> getPersonaPrompt(String personaName) {
+        if (personaName != null && !personaName.isBlank()) {
+            return client.fetch(AiPersona.class, personaName)
+                .mapNotNull(persona -> {
+                    String prompt = persona.getSpec().getPrompt();
+                    return (prompt != null && !prompt.isBlank()) ? prompt : null;
+                })
+                .defaultIfEmpty(DEFAULT_PERSONA_PROMPT);
+        }
+        // Find default persona
+        return client.list(AiPersona.class,
+                persona -> persona.getSpec() != null && Boolean.TRUE.equals(persona.getSpec().getIsDefault()),
+                null)
+            .next()
+            .mapNotNull(persona -> {
+                String prompt = persona.getSpec().getPrompt();
+                return (prompt != null && !prompt.isBlank()) ? prompt : null;
             })
             .defaultIfEmpty(DEFAULT_PERSONA_PROMPT);
     }
+
+    private Mono<String> getEnabledPresetsPrompt() {
+        return client.fetch(ConfigMap.class, CONFIG_MAP_NAME)
+            .mapNotNull(cm -> {
+                var data = cm.getData();
+                if (data == null) return "";
+                String promptJson = data.get("prompt");
+                if (promptJson == null || promptJson.isBlank()) return "";
+                try {
+                    JsonNode node = objectMapper.readTree(promptJson);
+                    JsonNode presetsNode = node.get("enabledPresets");
+                    if (presetsNode == null) return "";
+                    StringBuilder sb = new StringBuilder();
+                    if (presetsNode.isArray()) {
+                        for (JsonNode item : presetsNode) {
+                            String key = item.asText().trim().toLowerCase();
+                            if (PRESET_MAP.containsKey(key)) {
+                                sb.append(PRESET_MAP.get(key));
+                            }
+                        }
+                    } else if (presetsNode.isTextual() && !presetsNode.asText().isBlank()) {
+                        String[] presetNames = presetsNode.asText().split(",");
+                        for (String presetName : presetNames) {
+                            String key = presetName.trim().toLowerCase();
+                            if (PRESET_MAP.containsKey(key)) {
+                                sb.append(PRESET_MAP.get(key));
+                            }
+                        }
+                    }
+                    return sb.toString();
+                } catch (Exception e) {
+                    log.warn("Failed to parse enabledPresets from ConfigMap: {}", e.getMessage());
+                }
+                return "";
+            })
+            .onErrorResume(e -> {
+                log.debug("Failed to fetch enabledPresets setting: {}", e.getMessage());
+                return Mono.just("");
+            })
+            .defaultIfEmpty("");
+    }
 }

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

@@ -0,0 +1,58 @@
+package top.nxxy335.commentaiautopilot.service;
+
+import lombok.extern.slf4j.Slf4j;
+import org.springframework.stereotype.Component;
+
+import java.util.concurrent.ConcurrentHashMap;
+import java.util.concurrent.atomic.AtomicInteger;
+
+@Slf4j
+@Component
+public class RateLimitService {
+    private final ConcurrentHashMap<Long, AtomicInteger> windowMap = new ConcurrentHashMap<>();
+
+    public RateLimitService() {
+        // 每5分钟清理过期窗口，防止内存泄漏
+        Thread cleanupThread = new Thread(() -> {
+            while (!Thread.currentThread().isInterrupted()) {
+                try {
+                    Thread.sleep(5 * 60 * 1000);
+                    cleanup();
+                } catch (InterruptedException e) {
+                    Thread.currentThread().interrupt();
+                    break;
+                }
+            }
+        }, "rate-limit-cleanup");
+        cleanupThread.setDaemon(true);
+        cleanupThread.start();
+    }
+
+    public boolean tryAcquire(int limit) {
+        long currentWindow = System.currentTimeMillis() / 60000; // 每分钟一个窗口
+        AtomicInteger counter = windowMap.computeIfAbsent(currentWindow, k -> new AtomicInteger(0));
+        return counter.incrementAndGet() <= limit;
+    }
+
+    public int getCurrentCount() {
+        long currentWindow = System.currentTimeMillis() / 60000;
+        AtomicInteger counter = windowMap.get(currentWindow);
+        return counter != null ? counter.get() : 0;
+    }
+
+    // 清理过期窗口
+    public void cleanup() {
+        long currentWindow = System.currentTimeMillis() / 60000;
+        int removed = 0;
+        var iter = windowMap.keySet().iterator();
+        while (iter.hasNext()) {
+            if (iter.next() < currentWindow - 5) {
+                iter.remove();
+                removed++;
+            }
+        }
+        if (removed > 0) {
+            log.debug("[RateLimit] Cleaned up {} expired windows", removed);
+        }
+    }
+}

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

@@ -4,19 +4,15 @@ import lombok.extern.slf4j.Slf4j;
 import org.springframework.beans.factory.ObjectProvider;
 import org.springframework.stereotype.Component;
 import reactor.core.publisher.Mono;
-import run.halo.app.plugin.ReactiveSettingFetcher;
 
 @Component
 @Slf4j
 public class ReviewService {
 
     private final ObjectProvider<AiFoundationClient> aiFoundationClientProvider;
-    private final ReactiveSettingFetcher settingFetcher;
 
-    public ReviewService(ObjectProvider<AiFoundationClient> aiFoundationClientProvider,
-                         ReactiveSettingFetcher settingFetcher) {
+    public ReviewService(ObjectProvider<AiFoundationClient> aiFoundationClientProvider) {
         this.aiFoundationClientProvider = aiFoundationClientProvider;
-        this.settingFetcher = settingFetcher;
     }
 
     private static final String REVIEW_PROMPT_TEMPLATE = """

src/main/resources/extensions/annotation-setting.yaml

@@ -12,6 +12,11 @@ spec:
       label: 启用AI回评
       value: true
       help: 开启后，该文章收到评论时将自动触发AI回复
+    - $formkit: text
+      name: comment-ai-autopilot.nxxy335.top/ai-persona
+      label: AI角色
+      help: 选择该文章使用的AI回复角色名称，留空使用默认角色
+      value: ""
 ---
 apiVersion: v1alpha1
 kind: AnnotationSetting
@@ -27,3 +32,8 @@ spec:
       label: 启用AI回评
       value: false
       help: 开启后，该页面收到评论时将自动触发AI回复
+    - $formkit: text
+      name: comment-ai-autopilot.nxxy335.top/ai-persona
+      label: AI角色
+      help: 选择该页面使用的AI回复角色名称，留空使用默认角色
+      value: ""

src/main/resources/extensions/roleTemplate.yaml

@@ -13,6 +13,9 @@ rules:
   - apiGroups: ["comment-ai-autopilot.nxxy335.top"]
     resources: ["comment-ai-autopilot/aicommentreplies"]
     verbs: ["*"]
+  - apiGroups: ["comment-ai-autopilot.nxxy335.top"]
+    resources: ["comment-ai-autopilot/aipersonas"]
+    verbs: ["*"]
   - apiGroups: ["console.api.comment-ai-autopilot.nxxy335.top"]
     resources: ["*"]
     verbs: ["*"]

src/main/resources/extensions/settings.yaml

@@ -21,26 +21,24 @@ spec:
           value: 3
           min: 1
           max: 10
+        - $formkit: number
+          name: maxConversationRounds
+          label: 最大对话轮次
+          help: 同一评论线程中AI最多自动回复的轮次，超过后不再回复
+          value: 8
+          min: 1
+          max: 100
+        - $formkit: number
+          name: rateLimitPerMinute
+          label: 速率限制
+          help: 每分钟最大AI回复数量，防止批量评论消耗过多额度
+          value: 10
+          min: 1
+          max: 100
         - $formkit: textarea
           name: blockedCommenters
           label: 评论者黑名单
-          help: 输入评论者显示名称或邮箱，多个用逗号分隔。这些评论者的评论不会触发AI回复
-          value: ""
-    - group: persona
-      label: AI角色设置
-      formSchema:
-        - $formkit: text
-          name: personaName
-          label: AI角色昵称
-          value: "小回"
-        - $formkit: textarea
-          name: personaPrompt
-          label: AI角色人格提示词
-          value: "你是「小回」，一个友善的评论者。你的回复简洁自然，像朋友聊天一样。简短的评论就简短回复，有深度的讨论才展开回应。不要长篇大论，不要复述文章内容。"
-        - $formkit: email
-          name: personaEmail
-          label: AI角色邮箱
-          help: 用于Gravatar头像服务展示头像
+          help: "输入评论者显示名称或邮箱，多个用逗号分隔。支持正则表达式，以 regex: 开头，如 regex:^spam.*"
           value: ""
     - group: model
       label: 模型设置
@@ -57,6 +55,21 @@ spec:
           name: customPromptTemplate
           label: 自定义Prompt模板
           value: "{{persona_prompt}}\n\n{{safety_prompt}}\n\n【语言要求】请用评论所使用的语言回复。如果评论是英文，请用英文回复；如果是中文，请用中文回复；如果是日文，请用日文回复；以此类推。\n\n请回复以下评论。注意：\n- 回复长度应与评论长度匹配，简短问候简短回复\n- 不要复述或总结文章内容\n- 自然对话，不要写小作文\n- 只有评论涉及具体内容时才针对性回应\n\n文章（仅供理解上下文，不要复述）：\n{{article}}\n\n评论：\n{{comment}}"
+        - $formkit: select
+          name: enabledPresets
+          label: 启用预设
+          help: 选择要启用的Prompt预设风格
+          value: []
+          multiple: true
+          options:
+            - label: 友好型
+              value: friendly
+            - label: 专业型
+              value: professional
+            - label: 幽默型
+              value: humorous
+            - label: 简洁型
+              value: concise
     - group: cleanup
       label: 数据清理
       formSchema:

src/main/resources/plugin.yaml

@@ -10,18 +10,18 @@ spec:
   requires: ">=2.23.0"
   author:
     name: 暖心向阳335
-    website: https://github.com/暖心向阳335
+    website: https://nxxy335.top
   logo: logo.png
-  homepage: https://github.com/暖心向阳335/comment-ai-autopilot#readme
-  repo: https://github.com/暖心向阳335/comment-ai-autopilot
-  issues: https://github.com/暖心向阳335/comment-ai-autopilot/issues
+  homepage: https://nxxy335.top/comment-ai-autopilot
+  repo: https://github.com/sunny-335/plugin-comment-ai-autopilot.git
+  issues: https://github.com/sunny-335/plugin-comment-ai-autopilot/issues
   displayName: "AI回评"
   description: "基于 AI 的 Halo 博客评论自动回复插件，支持 AI 虚拟角色回复、自审核、自动发布和对话式连续回复"
   license:
     - name: "GPL-3.0"
-      url: "https://github.com/暖心向阳335/comment-ai-autopilot/blob/main/LICENSE"
+      url: "https://github.com/sunny-335/plugin-comment-ai-autopilot/blob/main/LICENSE"
   settingName: "comment-ai-autopilot-settings"
   configMapName: "comment-ai-autopilot-configmap"
-  version: "0.0.1-w5s2t7"
+  version: "0.0.1-t5w8r3"
   pluginDependencies:
     ai-foundation: "*"