first commit

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

@@ -0,0 +1,45 @@
+package top.nxxy335.commentaiautopilot;
+
+import org.springframework.stereotype.Component;
+import run.halo.app.extension.index.IndexSpecs;
+import run.halo.app.extension.Scheme;
+import run.halo.app.extension.SchemeManager;
+import run.halo.app.plugin.BasePlugin;
+import run.halo.app.plugin.PluginContext;
+import top.nxxy335.commentaiautopilot.extension.AiCommentReply;
+
+/**
+ * <p>Plugin main class to manage the lifecycle of the plugin.</p>
+ * <p>This class must be public and have a public constructor.</p>
+ * <p>Only one main class extending {@link BasePlugin} is allowed per plugin.</p>
+ *
+ * @author 暖心向阳335
+ * @since 1.0.0
+ */
+@Component
+public class CommentAiAutopilotPlugin extends BasePlugin {
+
+    private final SchemeManager schemeManager;
+
+    public CommentAiAutopilotPlugin(PluginContext pluginContext, SchemeManager schemeManager) {
+        super(pluginContext);
+        this.schemeManager = schemeManager;
+    }
+
+    @Override
+    public void start() {
+        schemeManager.register(AiCommentReply.class, indexSpecs -> {
+            indexSpecs.add(IndexSpecs.<AiCommentReply, String>single("spec.commentId", String.class)
+                .indexFunc(ext -> ext.getSpec().getCommentId()));
+            indexSpecs.add(IndexSpecs.<AiCommentReply, String>single("spec.postId", String.class)
+                .indexFunc(ext -> ext.getSpec().getPostId()));
+            indexSpecs.add(IndexSpecs.<AiCommentReply, String>single("spec.status", String.class)
+                .indexFunc(ext -> ext.getSpec().getStatus()));
+        });
+    }
+
+    @Override
+    public void stop() {
+        schemeManager.unregister(Scheme.buildFromType(AiCommentReply.class));
+    }
+}

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

@@ -0,0 +1,498 @@
+package top.nxxy335.commentaiautopilot.endpoint;
+
+import lombok.extern.slf4j.Slf4j;
+import org.springframework.stereotype.Component;
+import org.springframework.web.reactive.function.server.RouterFunction;
+import org.springframework.web.reactive.function.server.ServerRequest;
+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.Reply;
+import run.halo.app.core.extension.endpoint.CustomEndpoint;
+import run.halo.app.extension.ConfigMap;
+import run.halo.app.extension.GroupVersion;
+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.service.AiReplyOrchestrator;
+
+import com.fasterxml.jackson.databind.JsonNode;
+import com.fasterxml.jackson.databind.ObjectMapper;
+import org.springframework.data.domain.Sort;
+
+import java.time.Instant;
+import java.time.LocalDate;
+import java.time.ZoneId;
+import java.time.format.DateTimeFormatter;
+import java.util.ArrayList;
+import java.util.Comparator;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+
+import static org.springframework.web.reactive.function.server.RouterFunctions.route;
+
+@Component
+@Slf4j
+public class CommentAiAutopilotEndpoint implements CustomEndpoint {
+
+    private final ReactiveExtensionClient client;
+    private final AiReplyOrchestrator orchestrator;
+    private final ObjectMapper objectMapper;
+
+    private static final String CONFIG_MAP_NAME = "comment-ai-autopilot-configmap";
+
+    public CommentAiAutopilotEndpoint(ReactiveExtensionClient client, AiReplyOrchestrator orchestrator) {
+        this.client = client;
+        this.orchestrator = orchestrator;
+        this.objectMapper = new ObjectMapper();
+    }
+
+    @Override
+    public RouterFunction<ServerResponse> endpoint() {
+        return route()
+            .GET("/replies", this::listReplies)
+            .POST("/replies/batch-approve", this::batchApproveReplies)
+            .POST("/replies/batch-reject", this::batchRejectReplies)
+            .POST("/replies/batch-delete", this::batchDeleteReplies)
+            .DELETE("/replies/{name}", this::deleteReply)
+            .GET("/stats", this::getStats)
+            .GET("/persona", this::getPersona)
+            .GET("/conversation/{commentName}", this::getConversation)
+            .POST("/replies/{name}/approve", this::approveReply)
+            .POST("/replies/{name}/reject", this::rejectReply)
+            .POST("/comments/{commentName}/trigger", this::triggerReply)
+            .POST("/replies/{replyName}/trigger-conversation", this::triggerConversationReply)
+            .build();
+    }
+
+    @Override
+    public GroupVersion groupVersion() {
+        return new GroupVersion("console.api.comment-ai-autopilot.nxxy335.top", "v1alpha1");
+    }
+
+    private Mono<ServerResponse> listReplies(ServerRequest request) {
+        var page = Integer.parseInt(request.queryParam("page").orElse("1"));
+        var size = Integer.parseInt(request.queryParam("size").orElse("20"));
+        var sort = Sort.by(Sort.Order.desc("metadata.creationTimestamp"));
+        var pageable = PageRequestImpl.of(page, size, sort);
+
+        return client.listBy(AiCommentReply.class, ListOptions.builder().build(), pageable)
+            .flatMap(result -> ServerResponse.ok().bodyValue(result));
+    }
+
+    private Mono<ServerResponse> deleteReply(ServerRequest request) {
+        var name = request.pathVariable("name");
+        return client.fetch(AiCommentReply.class, name)
+            .flatMap(record -> client.delete(record))
+            .then(ServerResponse.ok().bodyValue("{\"message\":\"deleted\"}"))
+            .switchIfEmpty(ServerResponse.notFound().build());
+    }
+
+    private Mono<ServerResponse> getStats(ServerRequest request) {
+        return client.listAll(AiCommentReply.class, ListOptions.builder().build(), Sort.unsorted())
+            .collectList()
+            .map(replies -> {
+                long total = replies.size();
+                long passCount = replies.stream()
+                    .filter(r -> "PASS".equals(r.getSpec().getStatus())).count();
+                long failCount = replies.stream()
+                    .filter(r -> "FAIL".equals(r.getSpec().getStatus())).count();
+                double avgScore = replies.stream()
+                    .filter(r -> r.getSpec().getScore() != null && r.getSpec().getScore() > 0)
+                    .mapToInt(r -> r.getSpec().getScore())
+                    .average().orElse(0.0);
+
+                long reviewingCount = replies.stream()
+                    .filter(r -> "PASS".equals(r.getSpec().getStatus())
+                        && !Boolean.TRUE.equals(r.getSpec().getPublished()))
+                    .count();
+
+                Map<String, Long> sentimentDistribution = new HashMap<>();
+                sentimentDistribution.put("POSITIVE", 0L);
+                sentimentDistribution.put("NEUTRAL", 0L);
+                sentimentDistribution.put("NEGATIVE", 0L);
+                sentimentDistribution.put("UNKNOWN", 0L);
+                for (var r : replies) {
+                    String sentiment = r.getSpec().getSentiment();
+                    if (sentiment == null || sentiment.isBlank()) {
+                        sentimentDistribution.merge("UNKNOWN", 1L, Long::sum);
+                    } else {
+                        sentimentDistribution.merge(sentiment, 1L, Long::sum);
+                    }
+                }
+
+                ZoneId zoneId = ZoneId.systemDefault();
+                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++) {
+                    dailyMap.put(today.minusDays(i), 0L);
+                }
+                for (var r : replies) {
+                    Instant timestamp = r.getMetadata().getCreationTimestamp();
+                    if (timestamp != null) {
+                        try {
+                            LocalDate date = timestamp.atZone(zoneId).toLocalDate();
+                            if (dailyMap.containsKey(date)) {
+                                dailyMap.merge(date, 1L, Long::sum);
+                            }
+                        } catch (Exception ignored) {
+                        }
+                    }
+                }
+                List<DailyCount> dailyTrend = new ArrayList<>();
+                for (int i = 0; i < 7; i++) {
+                    LocalDate date = today.minusDays(i);
+                    dailyTrend.add(new DailyCount(date.format(formatter), dailyMap.get(date)));
+                }
+
+                return new StatsResponse(total, passCount, failCount, avgScore,
+                    reviewingCount, sentimentDistribution, dailyTrend);
+            })
+            .onErrorResume(e -> {
+                log.warn("Failed to fetch stats: {}", e.getMessage());
+                return Mono.just(new StatsResponse(0, 0, 0, 0.0, 0L,
+                    Map.of("POSITIVE", 0L, "NEUTRAL", 0L, "NEGATIVE", 0L, "UNKNOWN", 0L),
+                    List.of()));
+            })
+            .flatMap(stats -> ServerResponse.ok().bodyValue(stats));
+    }
+
+    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", "", "");
+                }
+            })
+            .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));
+    }
+
+    public record DailyCount(String date, long count) {}
+
+    public record StatsResponse(
+        long total,
+        long passCount,
+        long failCount,
+        double avgScore,
+        long reviewingCount,
+        Map<String, Long> sentimentDistribution,
+        List<DailyCount> dailyTrend
+    ) {}
+
+    public record PersonaResponse(
+        String name,
+        String prompt,
+        String avatar
+    ) {}
+
+    private Mono<ServerResponse> getConversation(ServerRequest request) {
+        var commentName = request.pathVariable("commentName");
+        return client.fetch(Comment.class, commentName)
+            .flatMap(comment -> {
+                var commentOwner = extractOwnerName(comment.getSpec().getOwner());
+                var commentContent = extractContent(comment.getSpec().getRaw(), comment.getSpec().getContent());
+                var commentTime = String.valueOf(comment.getMetadata().getCreationTimestamp());
+                var isCommentAi = isAiOwner(comment.getSpec().getOwner());
+
+                var commentMsg = new ConversationMessage(
+                    "comment", commentOwner, commentContent, commentTime, isCommentAi
+                );
+
+                return client.listAll(Reply.class, ListOptions.builder().build(), Sort.unsorted())
+                    .filter(reply -> commentName.equals(reply.getSpec().getCommentName()))
+                    .sort(Comparator.comparing(r -> r.getMetadata().getCreationTimestamp()))
+                    .map(reply -> {
+                        var replyOwner = extractOwnerName(reply.getSpec().getOwner());
+                        var replyContent = extractContent(reply.getSpec().getRaw(), reply.getSpec().getContent());
+                        var replyTime = String.valueOf(reply.getMetadata().getCreationTimestamp());
+                        var isAi = isAiOwner(reply.getSpec().getOwner());
+                        return new ConversationMessage("reply", replyOwner, replyContent, replyTime, isAi);
+                    })
+                    .collectList()
+                    .map(replyList -> {
+                        List<ConversationMessage> messages = new ArrayList<>();
+                        messages.add(commentMsg);
+                        messages.addAll(replyList);
+                        return messages;
+                    });
+            })
+            .flatMap(messages -> ServerResponse.ok().bodyValue(Map.of("messages", messages)))
+            .switchIfEmpty(ServerResponse.ok().bodyValue(Map.of("messages", List.of())));
+    }
+
+    private String extractOwnerName(Comment.CommentOwner owner) {
+        if (owner == null) return "匿名用户";
+        var displayName = owner.getDisplayName();
+        return (displayName != null && !displayName.isBlank()) ? displayName : "匿名用户";
+    }
+
+    private String extractContent(String raw, String content) {
+        if (raw != null && !raw.isBlank()) return raw;
+        if (content != null && !content.isBlank()) return content;
+        return "";
+    }
+
+    private boolean isAiOwner(Comment.CommentOwner owner) {
+        if (owner == null) return false;
+        var annotations = owner.getAnnotations();
+        if (annotations != null) {
+            return "true".equals(annotations.get("comment-ai-autopilot.nxxy335.top/is-ai"));
+        }
+        return false;
+    }
+
+    private Mono<ServerResponse> approveReply(ServerRequest request) {
+        var name = request.pathVariable("name");
+        return client.fetch(AiCommentReply.class, name)
+            .flatMap(record -> {
+                // Find the corresponding Reply and set approved=true
+                return findReplyForRecord(record)
+                    .flatMap(reply -> {
+                        reply.getSpec().setApproved(true);
+                        reply.getSpec().setApprovedTime(Instant.now());
+                        return client.update(reply);
+                    })
+                    .then(Mono.defer(() -> {
+                        // Update AiCommentReply record
+                        return client.fetch(AiCommentReply.class, name)
+                            .flatMap(latest -> {
+                                latest.getSpec().setPublished(true);
+                                return client.update(latest);
+                            });
+                    }))
+                    .then(ServerResponse.ok().bodyValue(Map.of("message", "approved")));
+            })
+            .switchIfEmpty(ServerResponse.notFound().build());
+    }
+
+    private Mono<ServerResponse> rejectReply(ServerRequest request) {
+        var name = request.pathVariable("name");
+        return client.fetch(AiCommentReply.class, name)
+            .flatMap(record -> {
+                // Delete the draft Reply if it exists
+                return findReplyForRecord(record)
+                    .flatMap(reply -> client.delete(reply))
+                    .then(Mono.defer(() -> {
+                        // Update AiCommentReply record status to REJECTED
+                        return client.fetch(AiCommentReply.class, name)
+                            .flatMap(latest -> {
+                                latest.getSpec().setStatus("REJECTED");
+                                latest.getSpec().setPublished(false);
+                                return client.update(latest);
+                            });
+                    }))
+                    .then(ServerResponse.ok().bodyValue(Map.of("message", "rejected")));
+            })
+            .switchIfEmpty(ServerResponse.notFound().build());
+    }
+
+    private Mono<ServerResponse> batchApproveReplies(ServerRequest request) {
+        return request.bodyToMono(String.class)
+            .flatMap(body -> {
+                List<String> names;
+                try {
+                    JsonNode node = objectMapper.readTree(body);
+                    names = new ArrayList<>();
+                    node.get("names").forEach(n -> names.add(n.asText()));
+                } catch (Exception e) {
+                    return ServerResponse.badRequest()
+                        .bodyValue(Map.of("successCount", 0, "failCount", 0));
+                }
+                return Flux.fromIterable(names)
+                    .flatMap(name ->
+                        client.fetch(AiCommentReply.class, name)
+                            .flatMap(record -> findReplyForRecord(record)
+                                .flatMap(reply -> {
+                                    reply.getSpec().setApproved(true);
+                                    reply.getSpec().setApprovedTime(Instant.now());
+                                    return client.update(reply);
+                                })
+                                .then(Mono.defer(() -> client.fetch(AiCommentReply.class, name)
+                                    .flatMap(latest -> {
+                                        latest.getSpec().setPublished(true);
+                                        return client.update(latest);
+                                    })))
+                                .thenReturn(true)
+                            )
+                            .onErrorResume(e -> {
+                                log.warn("Batch approve failed for {}: {}", name, e.getMessage());
+                                return Mono.just(false);
+                            })
+                            .defaultIfEmpty(false)
+                    )
+                    .collectList()
+                    .flatMap(results -> {
+                        long successCount = results.stream().filter(b -> b).count();
+                        long failCount = results.size() - successCount;
+                        return ServerResponse.ok()
+                            .bodyValue(Map.of("successCount", successCount, "failCount", failCount));
+                    });
+            });
+    }
+
+    private Mono<ServerResponse> batchRejectReplies(ServerRequest request) {
+        return request.bodyToMono(String.class)
+            .flatMap(body -> {
+                List<String> names;
+                try {
+                    JsonNode node = objectMapper.readTree(body);
+                    names = new ArrayList<>();
+                    node.get("names").forEach(n -> names.add(n.asText()));
+                } catch (Exception e) {
+                    return ServerResponse.badRequest()
+                        .bodyValue(Map.of("successCount", 0, "failCount", 0));
+                }
+                return Flux.fromIterable(names)
+                    .flatMap(name ->
+                        client.fetch(AiCommentReply.class, name)
+                            .flatMap(record -> findReplyForRecord(record)
+                                .flatMap(reply -> client.delete(reply))
+                                .then(Mono.defer(() -> client.fetch(AiCommentReply.class, name)
+                                    .flatMap(latest -> {
+                                        latest.getSpec().setStatus("REJECTED");
+                                        latest.getSpec().setPublished(false);
+                                        return client.update(latest);
+                                    })))
+                                .thenReturn(true)
+                            )
+                            .onErrorResume(e -> {
+                                log.warn("Batch reject failed for {}: {}", name, e.getMessage());
+                                return Mono.just(false);
+                            })
+                            .defaultIfEmpty(false)
+                    )
+                    .collectList()
+                    .flatMap(results -> {
+                        long successCount = results.stream().filter(b -> b).count();
+                        long failCount = results.size() - successCount;
+                        return ServerResponse.ok()
+                            .bodyValue(Map.of("successCount", successCount, "failCount", failCount));
+                    });
+            });
+    }
+
+    private Mono<ServerResponse> batchDeleteReplies(ServerRequest request) {
+        return request.bodyToMono(String.class)
+            .flatMap(body -> {
+                List<String> names;
+                try {
+                    JsonNode node = objectMapper.readTree(body);
+                    names = new ArrayList<>();
+                    node.get("names").forEach(n -> names.add(n.asText()));
+                } catch (Exception e) {
+                    return ServerResponse.badRequest()
+                        .bodyValue(Map.of("successCount", 0, "failCount", 0));
+                }
+                return Flux.fromIterable(names)
+                    .flatMap(name ->
+                        client.fetch(AiCommentReply.class, name)
+                            .flatMap(record -> client.delete(record)
+                                .thenReturn(true)
+                            )
+                            .onErrorResume(e -> {
+                                log.warn("Batch delete failed for {}: {}", name, e.getMessage());
+                                return Mono.just(false);
+                            })
+                            .defaultIfEmpty(false)
+                    )
+                    .collectList()
+                    .flatMap(results -> {
+                        long successCount = results.stream().filter(b -> b).count();
+                        long failCount = results.size() - successCount;
+                        return ServerResponse.ok()
+                            .bodyValue(Map.of("successCount", successCount, "failCount", failCount));
+                    });
+            });
+    }
+
+    private Mono<ServerResponse> triggerReply(ServerRequest request) {
+        var commentName = request.pathVariable("commentName");
+
+        // Check if there's already an AiCommentReply record for this comment
+        return client.list(AiCommentReply.class,
+                record -> commentName.equals(record.getSpec().getCommentId())
+                    && !Boolean.TRUE.equals(record.getSpec().getIsAiConversation()),
+                null)
+            .hasElements()
+            .flatMap(hasExisting -> {
+                if (hasExisting) {
+                    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")));
+            });
+    }
+
+    private Mono<ServerResponse> triggerConversationReply(ServerRequest request) {
+        var replyName = request.pathVariable("replyName");
+
+        // First fetch the reply to get its parent comment name
+        return client.fetch(Reply.class, replyName)
+            .flatMap(reply -> {
+                var commentName = reply.getSpec().getCommentName();
+
+                // Check if there's already an AiCommentReply record for this conversation
+                return client.list(AiCommentReply.class,
+                        record -> replyName.equals(record.getSpec().getReplyTo())
+                            && Boolean.TRUE.equals(record.getSpec().getIsAiConversation()),
+                        null)
+                    .hasElements()
+                    .flatMap(hasExisting -> {
+                        if (hasExisting) {
+                            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")));
+                    });
+            })
+            .switchIfEmpty(ServerResponse.notFound().build());
+    }
+
+    private Mono<Reply> findReplyForRecord(AiCommentReply record) {
+        // Find the Reply that belongs to the same comment and was created by AI
+        return client.list(Reply.class,
+                reply -> {
+                    if (!record.getSpec().getCommentId().equals(reply.getSpec().getCommentName())) {
+                        return false;
+                    }
+                    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"));
+                },
+                null)
+            .next()
+            .switchIfEmpty(Mono.empty());
+    }
+
+    public record ConversationMessage(
+        String type,
+        String owner,
+        String content,
+        String time,
+        boolean isAi
+    ) {}
+}

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

@@ -0,0 +1,60 @@
+package top.nxxy335.commentaiautopilot.extension;
+
+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 = "AiCommentReply",
+    plural = "aicommentreplies",
+    singular = "aicommentreply"
+)
+public class AiCommentReply extends AbstractExtension {
+
+    @Schema(requiredMode = Schema.RequiredMode.REQUIRED)
+    private Spec spec;
+
+    @Data
+    @Schema(name = "AiCommentReplySpec")
+    public static class Spec {
+
+        @Schema(description = "关联评论ID")
+        private String commentId;
+
+        @Schema(description = "关联文章ID")
+        private String postId;
+
+        @Schema(description = "关联文章Slug，用于生成文章链接")
+        private String postSlug;
+
+        @Schema(description = "AI回复内容")
+        private String reply;
+
+        @Schema(description = "审核评分")
+        private Integer score;
+
+        @Schema(description = "状态: PENDING/REVIEWING/PASS/FAIL")
+        private String status;
+
+        @Schema(description = "重试次数")
+        private Integer retryCount;
+
+        @Schema(description = "回复目标的评论ID")
+        private String replyTo;
+
+        @Schema(description = "是否为AI对话中的回复")
+        private Boolean isAiConversation;
+
+        @Schema(description = "是否已发布回复")
+        private Boolean published;
+
+        @Schema(description = "评论情感倾向: POSITIVE/NEUTRAL/NEGATIVE")
+        private String sentiment;
+    }
+}

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

@@ -0,0 +1,155 @@
+package top.nxxy335.commentaiautopilot.listener;
+
+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.extension.ExtensionClient;
+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.AiCommentReply;
+import top.nxxy335.commentaiautopilot.service.AiReplyOrchestrator;
+
+import java.time.Instant;
+import java.util.HashMap;
+import java.util.Map;
+import java.util.concurrent.ConcurrentHashMap;
+import java.util.concurrent.atomic.AtomicBoolean;
+
+@Component
+@Slf4j
+@RequiredArgsConstructor
+public class CommentReconciler implements Reconciler<Reconciler.Request> {
+
+    private final ExtensionClient client;
+    private final AiReplyOrchestrator orchestrator;
+
+    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-";
+
+    // Record the time when this bean was created (plugin startup time)
+    private final Instant pluginStartTime = Instant.now();
+
+    // In-memory dedup lock: prevents the same comment from being processed multiple times
+    // even if reconcile is triggered concurrently
+    private final ConcurrentHashMap<String, Boolean> processingLocks = new ConcurrentHashMap<>();
+
+    @Override
+    public Result reconcile(Request request) {
+        var name = request.name();
+
+        // Acquire lock at the very beginning to prevent any concurrent processing
+        if (processingLocks.putIfAbsent(name, Boolean.TRUE) != null) {
+            log.debug("[CommentReconciler] Already processing comment: {}, skipping", name);
+            return Result.doNotRetry();
+        }
+
+        AtomicBoolean asyncStarted = new AtomicBoolean(false);
+        try {
+            client.fetch(Comment.class, name).ifPresent(comment -> {
+                if (isProcessed(comment.getMetadata().getAnnotations())) {
+                    return;
+                }
+
+                // Skip comments created before plugin startup (historical comments)
+                var creationTime = comment.getMetadata().getCreationTimestamp();
+                if (creationTime != null && creationTime.isBefore(pluginStartTime)) {
+                    log.debug("[CommentReconciler] Skipping historical comment: {} (created before plugin startup)", name);
+                    markProcessed(comment);
+                    client.update(comment);
+                    return;
+                }
+
+                // Skip comments from AI persona itself
+                if (isAiComment(comment)) {
+                    markProcessed(comment);
+                    client.update(comment);
+                    return;
+                }
+
+                // Dedup: check if we already have an AiCommentReply record for this comment
+                boolean alreadyHasRecord = !client.list(AiCommentReply.class,
+                        record -> name.equals(record.getSpec().getCommentId())
+                            && !Boolean.TRUE.equals(record.getSpec().getIsAiConversation()),
+                        null)
+                    .isEmpty();
+
+                if (alreadyHasRecord) {
+                    log.debug("[CommentReconciler] Already have AiCommentReply record for: {}, skipping", name);
+                    markProcessed(comment);
+                    client.update(comment);
+                    return;
+                }
+
+                // Mark as processed first to avoid re-processing
+                markProcessed(comment);
+                client.update(comment);
+
+                // Top-level comment → always trigger AI reply
+                log.info("[CommentReconciler] New top-level comment detected: {}", name);
+                asyncStarted.set(true);
+                orchestrator.processComment(name, null, false)
+                    .subscribeOn(Schedulers.boundedElastic())
+                    .doFinally(signal -> {
+                        processingLocks.remove(name);
+                        log.debug("[CommentReconciler] Released processing lock for: {}", name);
+                    })
+                    .subscribe(
+                        null,
+                        e -> log.error("[CommentReconciler] Error processing comment {}: {}", name, e.getMessage(), e),
+                        () -> log.info("[CommentReconciler] Processing completed for comment: {}", name)
+                    );
+            });
+        } catch (Exception e) {
+            log.error("[CommentReconciler] Error in reconcile for {}: {}", name, e.getMessage(), e);
+        } finally {
+            // Only release lock here if async processing was NOT started
+            // (async path releases lock in doFinally)
+            if (!asyncStarted.get()) {
+                processingLocks.remove(name);
+            }
+        }
+
+        return Result.doNotRetry();
+    }
+
+    /**
+     * Check if a comment is from AI persona.
+     */
+    private boolean isAiComment(Comment comment) {
+        var owner = comment.getSpec().getOwner();
+        if (owner != null && owner.getName() != null
+            && owner.getName().startsWith(AI_PERSONA_OWNER_PREFIX)) {
+            return true;
+        }
+        if (owner != null && owner.getAnnotations() != null
+            && "true".equals(owner.getAnnotations().get(AI_MARKER_ANNOTATION))) {
+            return true;
+        }
+        return false;
+    }
+
+    private boolean isProcessed(Map<String, String> annotations) {
+        return annotations != null && "true".equals(annotations.get(PROCESSED_ANNOTATION));
+    }
+
+    private void markProcessed(Comment comment) {
+        var annotations = comment.getMetadata().getAnnotations();
+        if (annotations == null) {
+            annotations = new HashMap<>();
+            comment.getMetadata().setAnnotations(annotations);
+        }
+        annotations.put(PROCESSED_ANNOTATION, "true");
+    }
+
+    @Override
+    public Controller setupWith(ControllerBuilder builder) {
+        return builder
+            .extension(new Comment())
+            .syncAllOnStart(false)
+            .build();
+    }
+}

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

@@ -0,0 +1,165 @@
+package top.nxxy335.commentaiautopilot.listener;
+
+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.Reply;
+import run.halo.app.extension.ExtensionClient;
+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.AiCommentReply;
+import top.nxxy335.commentaiautopilot.service.AiReplyOrchestrator;
+
+import java.time.Instant;
+import java.util.HashMap;
+import java.util.Map;
+
+@Component
+@Slf4j
+@RequiredArgsConstructor
+public class ReplyReconciler implements Reconciler<Reconciler.Request> {
+
+    private final ExtensionClient client;
+    private final AiReplyOrchestrator orchestrator;
+
+    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";
+
+    // Record the time when this bean was created (plugin startup time)
+    private final Instant pluginStartTime = Instant.now();
+
+    @Override
+    public Result reconcile(Request request) {
+        var name = request.name();
+
+        client.fetch(Reply.class, name).ifPresent(reply -> {
+            if (isProcessed(reply.getMetadata().getAnnotations())) {
+                return;
+            }
+
+            // Skip replies created before plugin startup (historical replies)
+            var creationTime = reply.getMetadata().getCreationTimestamp();
+            if (creationTime != null && creationTime.isBefore(pluginStartTime)) {
+                log.debug("[ReplyReconciler] Skipping historical reply: {} (created before plugin startup)", name);
+                markProcessed(reply);
+                client.update(reply);
+                return;
+            }
+
+            // Skip replies from AI persona itself
+            var owner = reply.getSpec().getOwner();
+            if (owner != null && owner.getName() != null
+                && owner.getName().startsWith(AI_PERSONA_OWNER_PREFIX)) {
+                markProcessed(reply);
+                client.update(reply);
+                return;
+            }
+            // Also skip if owner has AI marker annotation
+            if (owner != null && owner.getAnnotations() != null
+                && "true".equals(owner.getAnnotations().get(AI_MARKER_ANNOTATION))) {
+                markProcessed(reply);
+                client.update(reply);
+                return;
+            }
+
+            String parentCommentName = reply.getSpec().getCommentName();
+            if (parentCommentName == null || parentCommentName.isBlank()) {
+                return;
+            }
+
+            // Check if this reply is specifically replying to an AI reply
+            // by checking the quoteReply field
+            String quoteReply = reply.getSpec().getQuoteReply();
+
+            if (quoteReply == null || quoteReply.isBlank()) {
+                // No quoteReply - this is a direct reply to the top-level comment,
+                // NOT a reply to AI. Skip it (CommentReconciler handles top-level comments).
+                log.debug("[ReplyReconciler] Reply {} has no quoteReply, skipping (not a reply to AI)", name);
+                return;
+            }
+
+            // This reply quotes another reply - check if the quoted reply is from AI
+            boolean isReplyToAi = isAiReply(quoteReply);
+            log.debug("[ReplyReconciler] Reply {} quotes {}, isAiReply={}", name, quoteReply, isReplyToAi);
+
+            if (!isReplyToAi) {
+                log.debug("[ReplyReconciler] Not a reply to AI, skipping: {}", name);
+                return;
+            }
+
+            // Dedup: check if we already have an AiCommentReply record for this reply
+            boolean alreadyHasRecord = !client.list(AiCommentReply.class,
+                    record -> name.equals(record.getSpec().getReplyTo())
+                        && Boolean.TRUE.equals(record.getSpec().getIsAiConversation()),
+                    null)
+                .isEmpty();
+
+            if (alreadyHasRecord) {
+                log.debug("[ReplyReconciler] Already have AiCommentReply record for reply: {}, skipping", name);
+                markProcessed(reply);
+                client.update(reply);
+                return;
+            }
+
+            // Mark as processed
+            markProcessed(reply);
+            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)
+                .subscribeOn(Schedulers.boundedElastic())
+                .subscribe(
+                    null,
+                    e -> log.error("[ReplyReconciler] Error processing reply {}: {}", name, e.getMessage(), e),
+                    () -> log.info("[ReplyReconciler] Processing completed for reply: {}", name)
+                );
+        });
+
+        return Result.doNotRetry();
+    }
+
+    /**
+     * Check if a specific Reply is from AI persona.
+     */
+    private boolean isAiReply(String replyName) {
+        return client.fetch(Reply.class, replyName)
+            .map(reply -> {
+                var owner = reply.getSpec().getOwner();
+                if (owner != null && owner.getName() != null
+                    && owner.getName().startsWith(AI_PERSONA_OWNER_PREFIX)) {
+                    return true;
+                }
+                if (owner != null && owner.getAnnotations() != null
+                    && "true".equals(owner.getAnnotations().get(AI_MARKER_ANNOTATION))) {
+                    return true;
+                }
+                return false;
+            })
+            .orElse(false);
+    }
+
+    private boolean isProcessed(Map<String, String> annotations) {
+        return annotations != null && "true".equals(annotations.get(PROCESSED_ANNOTATION));
+    }
+
+    private void markProcessed(Reply reply) {
+        var annotations = reply.getMetadata().getAnnotations();
+        if (annotations == null) {
+            annotations = new HashMap<>();
+            reply.getMetadata().setAnnotations(annotations);
+        }
+        annotations.put(PROCESSED_ANNOTATION, "true");
+    }
+
+    @Override
+    public Controller setupWith(ControllerBuilder builder) {
+        return builder
+            .extension(new Reply())
+            .syncAllOnStart(false)
+            .build();
+    }
+}

src/main/java/top/nxxy335/commentaiautopilot/processor/AiBadgeHeadProcessor.java

@@ -0,0 +1,28 @@
+package top.nxxy335.commentaiautopilot.processor;
+
+import lombok.RequiredArgsConstructor;
+import lombok.extern.slf4j.Slf4j;
+import org.springframework.stereotype.Component;
+import org.thymeleaf.context.ITemplateContext;
+import org.thymeleaf.model.IModel;
+import org.thymeleaf.processor.element.IElementModelStructureHandler;
+import reactor.core.publisher.Mono;
+import run.halo.app.theme.dialect.TemplateHeadProcessor;
+
+/**
+ * Template head processor for comment-ai-autopilot.
+ * Previously used to inject avatar replacement scripts, but now
+ * avatar is handled natively via Gravatar (email-based).
+ * Kept as a no-op to avoid breaking the Spring component scan.
+ */
+@Component
+@Slf4j
+@RequiredArgsConstructor
+public class AiBadgeHeadProcessor implements TemplateHeadProcessor {
+
+    @Override
+    public Mono<Void> process(ITemplateContext context, IModel model,
+                               IElementModelStructureHandler structureHandler) {
+        return Mono.empty();
+    }
+}

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

@@ -0,0 +1,80 @@
+package top.nxxy335.commentaiautopilot.service;
+
+import lombok.RequiredArgsConstructor;
+import lombok.extern.slf4j.Slf4j;
+import reactor.core.publisher.Mono;
+import run.halo.app.core.extension.Plugin;
+import run.halo.app.extension.ReactiveExtensionClient;
+import run.halo.app.plugin.extensionpoint.ExtensionGetter;
+import run.halo.aifoundation.AiModelService;
+import run.halo.aifoundation.chat.LanguageModel;
+import run.halo.aifoundation.chat.GenerateTextResult;
+
+/**
+ * AI Foundation client that calls the AI Foundation plugin's AiModelService.
+ * Only instantiated when AI Foundation classes are available (via @ConditionalOnClass).
+ */
+@Slf4j
+@RequiredArgsConstructor
+public class AiFoundationClient {
+
+    private static final String AI_FOUNDATION_PLUGIN_NAME = "ai-foundation";
+
+    private final ExtensionGetter extensionGetter;
+    private final ReactiveExtensionClient client;
+
+    /**
+     * Call AI Foundation to generate a chat response using the specified model.
+     * Checks at runtime whether the ai-foundation plugin is installed and enabled
+     * before attempting to use it.
+     *
+     * @param prompt    the prompt text
+     * @param modelName the AiModel metadata.name, null or blank to use default model
+     * @return the generated text, or empty if AI Foundation is unavailable
+     */
+    public Mono<String> chat(String prompt, String modelName) {
+        return isAiFoundationEnabled()
+            .flatMap(enabled -> {
+                if (!enabled) {
+                    log.warn("AI Foundation plugin is not installed or not enabled, skipping AI reply");
+                    return Mono.empty();
+                }
+                return doChat(prompt, modelName);
+            });
+    }
+
+    /**
+     * Check if the ai-foundation plugin is installed and enabled at runtime.
+     */
+    private Mono<Boolean> isAiFoundationEnabled() {
+        return client.fetch(Plugin.class, AI_FOUNDATION_PLUGIN_NAME)
+            .map(plugin -> plugin.getSpec().getEnabled())
+            .defaultIfEmpty(false)
+            .onErrorResume(e -> {
+                log.debug("Failed to check AI Foundation plugin status: {}", e.getMessage());
+                return Mono.just(false);
+            });
+    }
+
+    private Mono<String> doChat(String prompt, String modelName) {
+        return extensionGetter.getEnabledExtension(AiModelService.class)
+            .flatMap(service -> {
+                Mono<LanguageModel> modelMono;
+                if (modelName != null && !modelName.isBlank()) {
+                    modelMono = service.languageModel(modelName);
+                } else {
+                    modelMono = service.languageModel();
+                }
+                return modelMono.flatMap(model -> model.generateText(prompt)
+                    .map(GenerateTextResult::getText)
+                    .doOnNext(text -> log.debug("AI generated reply ({} chars) using model '{}'",
+                        text.length(), modelName != null ? modelName : "default"))
+                );
+            })
+            .doOnError(e -> log.error("AI Foundation call failed: {}", e.getMessage()))
+            .onErrorResume(e -> {
+                log.warn("AI Foundation not available: {}", e.getMessage());
+                return Mono.empty();
+            });
+    }
+}

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

@@ -0,0 +1,23 @@
+package top.nxxy335.commentaiautopilot.service;
+
+import org.springframework.boot.autoconfigure.condition.ConditionalOnClass;
+import org.springframework.context.annotation.Bean;
+import org.springframework.context.annotation.Configuration;
+import run.halo.app.extension.ReactiveExtensionClient;
+import run.halo.app.plugin.extensionpoint.ExtensionGetter;
+
+/**
+ * Configuration that registers AiFoundationClient only when
+ * AI Foundation plugin classes are available in the classloader.
+ * When AI Foundation is not installed, this entire configuration is skipped.
+ */
+@Configuration
+@ConditionalOnClass(name = "run.halo.aifoundation.AiModelService")
+public class AiFoundationConfiguration {
+
+    @Bean
+    public AiFoundationClient aiFoundationClient(ExtensionGetter extensionGetter,
+                                                  ReactiveExtensionClient client) {
+        return new AiFoundationClient(extensionGetter, client);
+    }
+}

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

@@ -0,0 +1,284 @@
+package top.nxxy335.commentaiautopilot.service;
+
+import lombok.RequiredArgsConstructor;
+import lombok.extern.slf4j.Slf4j;
+import org.springframework.dao.OptimisticLockingFailureException;
+import org.springframework.stereotype.Component;
+import reactor.core.publisher.Mono;
+import reactor.util.retry.Retry;
+import run.halo.app.extension.Metadata;
+import run.halo.app.extension.ReactiveExtensionClient;
+import run.halo.app.plugin.ReactiveSettingFetcher;
+import top.nxxy335.commentaiautopilot.extension.AiCommentReply;
+
+import java.time.Duration;
+import java.util.UUID;
+import java.util.concurrent.ConcurrentHashMap;
+
+@Component
+@Slf4j
+@RequiredArgsConstructor
+public class AiReplyOrchestrator {
+
+    private final ContextExtractor contextExtractor;
+    private final PromptBuilder promptBuilder;
+    private final AiReplyService aiReplyService;
+    private final SentimentService sentimentService;
+    private final ReviewService reviewService;
+    private final CommentReplyPublisher commentReplyPublisher;
+    private final FilterService filterService;
+    private final ReactiveExtensionClient client;
+    private final ReactiveSettingFetcher settingFetcher;
+
+    // In-memory dedup: tracks which comment/reply is currently being processed
+    // Prevents duplicate replies when Reconciler fires multiple times
+    private final ConcurrentHashMap<String, Boolean> processingLocks = new ConcurrentHashMap<>();
+
+    /**
+     * Process a new comment or reply.
+     *
+     * @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)
+     */
+    public Mono<Void> processComment(String commentName, String replyName, boolean isAiConversation) {
+        String lockKey = isAiConversation ? commentName + ":conv:" + replyName : commentName + ":top";
+
+        // In-memory dedup: if already processing, skip immediately
+        if (processingLocks.putIfAbsent(lockKey, Boolean.TRUE) != null) {
+            log.info("[Orchestrator] Already processing: {}, skipping duplicate", lockKey);
+            return Mono.empty();
+        }
+
+        log.info("[Orchestrator] Start processing: comment={}, replyName={}, isAiConversation={}",
+            commentName, replyName, isAiConversation);
+
+        return isAutoReplyEnabled()
+            .flatMap(enabled -> {
+                if (!enabled) {
+                    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 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) {
+                            return hasExistingReply(commentName)
+                                .flatMap(hasReply -> {
+                                    if (hasReply) {
+                                        log.info("[Orchestrator] Already have reply record for: {}, skipping", commentName);
+                                        return Mono.empty();
+                                    }
+                                    return doProcess(commentName, replyName, isAiConversation);
+                                });
+                        }
+                        return hasExistingConversationReply(replyName)
+                            .flatMap(hasReply -> {
+                                if (hasReply) {
+                                    log.info("[Orchestrator] Already replied to reply: {}, skipping", replyName);
+                                    return Mono.empty();
+                                }
+                                return doProcess(commentName, replyName, isAiConversation);
+                            });
+                    });
+            })
+            .doOnError(e -> log.error("[Orchestrator] Error processing comment {}: {}", commentName, e.getMessage(), e))
+            .doFinally(signal -> {
+                // Always release the lock when processing completes
+                processingLocks.remove(lockKey);
+                log.debug("[Orchestrator] Released processing lock for: {}", lockKey);
+            })
+            .then();
+    }
+
+    private Mono<Void> doProcess(String commentName, String replyName, boolean isAiConversation) {
+        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))
+                            );
+                    })
+                )
+        );
+    }
+
+    /**
+     * Check if there's already ANY AiCommentReply record for this top-level comment.
+     * Checks for ANY record (not just published) to prevent race conditions.
+     */
+    private Mono<Boolean> hasExistingReply(String commentName) {
+        return client.list(AiCommentReply.class,
+                record -> commentName.equals(record.getSpec().getCommentId())
+                    && !Boolean.TRUE.equals(record.getSpec().getIsAiConversation()),
+                null)
+            .hasElements()
+            .defaultIfEmpty(false)
+            .onErrorResume(e -> {
+                log.debug("[Orchestrator] Failed to check existing replies: {}", e.getMessage());
+                return Mono.just(false);
+            });
+    }
+
+    /**
+     * Check if we already have ANY AiCommentReply record for this specific reply (conversation).
+     * Checks for ANY record (not just published) to prevent race conditions.
+     */
+    private Mono<Boolean> hasExistingConversationReply(String replyName) {
+        if (replyName == null || replyName.isBlank()) {
+            return Mono.just(false);
+        }
+        return client.list(AiCommentReply.class,
+                record -> replyName.equals(record.getSpec().getReplyTo())
+                    && Boolean.TRUE.equals(record.getSpec().getIsAiConversation()),
+                null)
+            .hasElements()
+            .defaultIfEmpty(false)
+            .onErrorResume(e -> {
+                log.debug("[Orchestrator] Failed to check existing conversation replies: {}", e.getMessage());
+                return Mono.just(false);
+            });
+    }
+
+    /**
+     * Generate AI reply, optionally review it, then publish.
+     */
+    private Mono<Void> generateAndPublish(String prompt, ContextExtractor.CommentContext context,
+                                           AiCommentReply replyRecord, String modelName) {
+        return aiReplyService.generateReply(prompt, modelName)
+            .defaultIfEmpty("")
+            .flatMap(aiReply -> {
+                if (aiReply.isBlank()) {
+                    log.warn("[Orchestrator] AI generated empty reply for: {}", context.commentId());
+                    return updateRecord(replyRecord, "", 0, "FAIL", false).then();
+                }
+
+                log.info("[Orchestrator] AI generated reply for {}: {} chars",
+                    context.commentId(), aiReply.length());
+
+                return reviewService.review(context.postContent(), context.commentContent(), aiReply, modelName)
+                    .flatMap(reviewResult -> {
+                        log.info("[Orchestrator] Review for {}: score={}, status={}, reason={}",
+                            context.commentId(), reviewResult.score(), reviewResult.status(), reviewResult.reason());
+                        if ("FAIL".equals(reviewResult.status())) {
+                            log.warn("[Orchestrator] Content safety review FAILED for: {}, not publishing",
+                                context.commentId());
+                            return updateRecord(replyRecord, aiReply, 0, "FAIL", false).then();
+                        }
+                        return publishReply(context, aiReply, replyRecord, reviewResult.score());
+                    })
+                    .switchIfEmpty(
+                        publishReply(context, aiReply, replyRecord, 100)
+                    )
+                    .onErrorResume(e -> {
+                        log.warn("[Orchestrator] Review error, auto-passing: {}", e.getMessage());
+                        return publishReply(context, aiReply, replyRecord, 100);
+                    });
+            });
+    }
+
+    /**
+     * Publish the reply and update the record to PASS + published=true.
+     */
+    private Mono<Void> publishReply(ContextExtractor.CommentContext context, String aiReply,
+                                     AiCommentReply replyRecord, int score) {
+        return isAutoPublishEnabled()
+            .flatMap(autoPublish -> {
+                return commentReplyPublisher.publishReply(
+                        context.commentId(), aiReply, context.postId(), context.replyTo(), autoPublish)
+                    .flatMap(publishedReply -> {
+                        log.info("[Orchestrator] Reply {} for: {}", autoPublish ? "published" : "saved as draft", context.commentId());
+                        return updateRecord(replyRecord, aiReply, score, "PASS", autoPublish);
+                    })
+                    .flatMap(updated -> Mono.empty());
+            })
+            .then();
+    }
+
+    private Mono<String> getModelName() {
+        return settingFetcher.getSettingValue("model")
+            .map(node -> {
+                var nameNode = node.get("modelName");
+                if (nameNode != null && !nameNode.asText().isBlank()) {
+                    return nameNode.asText();
+                }
+                return "";
+            })
+            .onErrorResume(e -> {
+                log.debug("[Orchestrator] Failed to fetch model setting: {}", e.getMessage());
+                return Mono.just("");
+            })
+            .defaultIfEmpty("");
+    }
+
+    private Mono<Boolean> isAutoReplyEnabled() {
+        return settingFetcher.getSettingValue("basic")
+            .map(node -> !node.has("autoReply") || node.get("autoReply").asBoolean(true))
+            .onErrorResume(e -> {
+                log.debug("[Orchestrator] Failed to fetch autoReply setting: {}", e.getMessage());
+                return Mono.just(true);
+            })
+            .defaultIfEmpty(true);
+    }
+
+    private Mono<Boolean> isAutoPublishEnabled() {
+        return settingFetcher.getSettingValue("basic")
+            .map(node -> !node.has("autoPublish") || node.get("autoPublish").asBoolean(true))
+            .onErrorResume(e -> {
+                log.debug("[Orchestrator] Failed to fetch autoPublish setting: {}", e.getMessage());
+                return Mono.just(true);
+            })
+            .defaultIfEmpty(true);
+    }
+
+    private Mono<AiCommentReply> createAiCommentReply(ContextExtractor.CommentContext context, String sentiment) {
+        AiCommentReply record = new AiCommentReply();
+        record.setMetadata(new Metadata());
+        record.getMetadata().setName("ai-reply-" + UUID.randomUUID().toString().substring(0, 8));
+        record.setSpec(new AiCommentReply.Spec());
+        record.getSpec().setCommentId(context.commentId());
+        record.getSpec().setPostId(context.postId());
+        record.getSpec().setPostSlug(context.postSlug());
+        record.getSpec().setReply("");
+        record.getSpec().setScore(0);
+        record.getSpec().setStatus("PENDING");
+        record.getSpec().setRetryCount(0);
+        record.getSpec().setReplyTo(context.replyTo());
+        record.getSpec().setIsAiConversation(context.isAiConversation());
+        record.getSpec().setPublished(false);
+        record.getSpec().setSentiment(sentiment);
+        return client.create(record)
+            .doOnSuccess(created -> log.info("[Orchestrator] Created AiCommentReply record: {}",
+                created.getMetadata().getName()));
+    }
+
+    private Mono<AiCommentReply> updateRecord(AiCommentReply record, String reply,
+                                               int score, String status, boolean published) {
+        log.debug("[Orchestrator] Updating record {}: status={}, score={}, published={}",
+            record.getMetadata().getName(), status, score, published);
+        return client.fetch(AiCommentReply.class, record.getMetadata().getName())
+            .flatMap(latest -> {
+                latest.getSpec().setReply(reply);
+                latest.getSpec().setScore(score);
+                latest.getSpec().setStatus(status);
+                latest.getSpec().setPublished(published);
+                return client.update(latest);
+            })
+            .retryWhen(Retry.backoff(3, Duration.ofMillis(100))
+                .filter(e -> e instanceof OptimisticLockingFailureException)
+                .doBeforeRetry(signal -> log.debug("[Orchestrator] Retrying update for {} due to optimistic lock",
+                    record.getMetadata().getName()))
+            )
+            .doOnSuccess(updated -> log.debug("[Orchestrator] Record {} updated: status={}, score={}, published={}",
+                record.getMetadata().getName(), status, score, published));
+    }
+}

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

@@ -0,0 +1,37 @@
+package top.nxxy335.commentaiautopilot.service;
+
+import lombok.extern.slf4j.Slf4j;
+import org.springframework.beans.factory.ObjectProvider;
+import org.springframework.stereotype.Component;
+import reactor.core.publisher.Mono;
+
+@Component
+@Slf4j
+public class AiReplyService {
+
+    private final ObjectProvider<AiFoundationClient> aiFoundationClientProvider;
+
+    public AiReplyService(ObjectProvider<AiFoundationClient> aiFoundationClientProvider) {
+        this.aiFoundationClientProvider = aiFoundationClientProvider;
+    }
+
+    /**
+     * Generate an AI reply using the AI Foundation plugin.
+     *
+     * @param prompt    the prompt text
+     * @param modelName the model name (null for default)
+     */
+    public Mono<String> generateReply(String prompt, String modelName) {
+        AiFoundationClient client = aiFoundationClientProvider.getIfAvailable();
+        if (client == null) {
+            log.warn("AI Foundation plugin is not installed, cannot generate reply");
+            return Mono.empty();
+        }
+        return client.chat(prompt, modelName)
+            .doOnError(e -> log.error("AI reply generation failed: {}", e.getMessage()))
+            .onErrorResume(e -> {
+                log.warn("AI Foundation not available: {}", e.getMessage());
+                return Mono.empty();
+            });
+    }
+}

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

@@ -0,0 +1,210 @@
+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 java.nio.charset.StandardCharsets;
+import java.security.MessageDigest;
+import java.time.Instant;
+import java.util.HashMap;
+import java.util.Map;
+import java.util.UUID;
+
+@Component
+@Slf4j
+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.
+     */
+    public Mono<Reply> publishReply(String parentCommentName, String replyContent,
+                                     String postName, String quoteReplyName, boolean autoPublish) {
+        return checkExistingAiReply(parentCommentName, quoteReplyName)
+            .flatMap(exists -> {
+                if (exists) {
+                    log.info("[Publisher] AI reply already exists for comment: {}, skipping duplicate publish",
+                        parentCommentName);
+                    return Mono.empty();
+                }
+                return doPublish(parentCommentName, replyContent, postName, quoteReplyName, autoPublish);
+            });
+    }
+
+    private Mono<Boolean> checkExistingAiReply(String parentCommentName, String quoteReplyName) {
+        return client.list(Reply.class,
+                reply -> {
+                    if (!parentCommentName.equals(reply.getSpec().getCommentName())) {
+                        return false;
+                    }
+                    var owner = reply.getSpec().getOwner();
+                    if (owner == null || owner.getName() == null) {
+                        return false;
+                    }
+                    boolean isAiOwner = owner.getName().startsWith(AI_PERSONA_OWNER_PREFIX);
+                    boolean hasAiAnnotation = owner.getAnnotations() != null
+                        && "true".equals(owner.getAnnotations().get("comment-ai-autopilot.nxxy335.top/is-ai"));
+                    boolean isAiReply = isAiOwner || hasAiAnnotation;
+
+                    if (!isAiReply) {
+                        return false;
+                    }
+
+                    if (quoteReplyName != null && !quoteReplyName.isBlank()) {
+                        return quoteReplyName.equals(reply.getSpec().getQuoteReply());
+                    }
+                    return true;
+                },
+                null)
+            .hasElements()
+            .defaultIfEmpty(false);
+    }
+
+    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());
+
+                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);
+
+                if (quoteReplyName != null && !quoteReplyName.isBlank()) {
+                    spec.setQuoteReply(quoteReplyName);
+                }
+
+                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");
+
+                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: {}",
+                        personaName, 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.
+     */
+    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);
+    }
+
+    /**
+     * 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 String generateReplyName() {
+        return "ai-comment-reply-" + UUID.randomUUID().toString().substring(0, 8);
+    }
+
+    /**
+     * Generate Gravatar URL from email address using SHA-256 hash.
+     */
+    private String generateGravatarUrl(String email) {
+        try {
+            var digest = MessageDigest.getInstance("SHA-256");
+            var hashBytes = digest.digest(email.trim().toLowerCase().getBytes(StandardCharsets.UTF_8));
+            var hexString = new StringBuilder();
+            for (byte b : hashBytes) {
+                hexString.append(String.format("%02x", b));
+            }
+            return "https://cn.cravatar.com/avatar/" + hexString;
+        } catch (Exception e) {
+            log.error("[Publisher] Failed to generate Gravatar URL: {}", e.getMessage());
+            return "";
+        }
+    }
+}

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

@@ -0,0 +1,211 @@
+package top.nxxy335.commentaiautopilot.service;
+
+import lombok.RequiredArgsConstructor;
+import lombok.extern.slf4j.Slf4j;
+import org.jsoup.Jsoup;
+import org.jsoup.safety.Safelist;
+import org.springframework.stereotype.Component;
+import reactor.core.publisher.Mono;
+import run.halo.app.content.ContentWrapper;
+import run.halo.app.content.PostContentService;
+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.ReactiveExtensionClient;
+
+@Component
+@Slf4j
+@RequiredArgsConstructor
+public class ContextExtractor {
+
+    private final ReactiveExtensionClient client;
+    private final PostContentService postContentService;
+
+    /**
+     * Extract context from a comment event.
+     * Returns a CommentContext record with all needed info.
+     *
+     * @param commentName     the Comment name (always required)
+     * @param replyName       the Reply name that triggered this (null for top-level comments)
+     * @param isAiConversation whether this is a continuation of AI conversation
+     */
+    public Mono<CommentContext> extract(String commentName, String replyName, boolean isAiConversation) {
+        return client.fetch(Comment.class, commentName)
+            .flatMap(comment -> {
+                if (replyName != null && !replyName.isBlank()) {
+                    // This is a reply to a comment - fetch the Reply for content
+                    return client.fetch(Reply.class, replyName)
+                        .flatMap(reply -> buildContextFromReply(comment, reply, isAiConversation))
+                        .switchIfEmpty(buildContext(comment, isAiConversation));
+                }
+                return buildContext(comment, isAiConversation);
+            });
+    }
+
+    private Mono<CommentContext> buildContext(Comment comment, boolean isAiConversation) {
+        var commentContent = extractCommentContent(comment);
+        var commentOwner = extractCommentOwner(comment);
+        var subjectRef = comment.getSpec().getSubjectRef();
+
+        if (subjectRef != null && "Post".equals(subjectRef.getKind())) {
+            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
+                    ))
+                )
+                .defaultIfEmpty(new CommentContext(
+                    comment.getMetadata().getName(),
+                    postName,
+                    "",
+                    commentContent,
+                    commentOwner,
+                    "",
+                    "",
+                    null,
+                    isAiConversation
+                ));
+        }
+
+        return Mono.just(new CommentContext(
+            comment.getMetadata().getName(),
+            "",
+            "",
+            commentContent,
+            commentOwner,
+            "",
+            "",
+            null,
+            isAiConversation
+        ));
+    }
+
+    private Mono<CommentContext> buildContextFromReply(Comment comment, Reply reply, boolean isAiConversation) {
+        var replyContent = extractReplyContent(reply);
+        var replyOwner = extractReplyOwner(reply);
+        var subjectRef = comment.getSpec().getSubjectRef();
+
+        if (subjectRef != null && "Post".equals(subjectRef.getKind())) {
+            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
+                    ))
+                )
+                .defaultIfEmpty(new CommentContext(
+                    comment.getMetadata().getName(),
+                    postName,
+                    "",
+                    replyContent,
+                    replyOwner,
+                    "",
+                    "",
+                    reply.getMetadata().getName(),
+                    isAiConversation
+                ));
+        }
+
+        return Mono.just(new CommentContext(
+            comment.getMetadata().getName(),
+            "",
+            "",
+            replyContent,
+            replyOwner,
+            "",
+            "",
+            reply.getMetadata().getName(),
+            isAiConversation
+        ));
+    }
+
+    private String extractCommentContent(Comment comment) {
+        var spec = comment.getSpec();
+        // Prefer raw content (plain text / markdown), fall back to rendered HTML
+        String raw = spec.getRaw();
+        if (raw != null && !raw.isBlank()) {
+            return raw;
+        }
+        String content = spec.getContent();
+        if (content != null && !content.isBlank()) {
+            return Jsoup.clean(content, Safelist.none());
+        }
+        return "";
+    }
+
+    private String extractCommentOwner(Comment comment) {
+        var owner = comment.getSpec().getOwner();
+        if (owner != null) {
+            String displayName = owner.getDisplayName();
+            if (displayName != null && !displayName.isBlank()) {
+                return displayName;
+            }
+        }
+        return "匿名用户";
+    }
+
+    private String extractReplyContent(Reply reply) {
+        var spec = reply.getSpec();
+        String raw = spec.getRaw();
+        if (raw != null && !raw.isBlank()) {
+            return raw;
+        }
+        String content = spec.getContent();
+        if (content != null && !content.isBlank()) {
+            return Jsoup.clean(content, Safelist.none());
+        }
+        return "";
+    }
+
+    private String extractReplyOwner(Reply reply) {
+        var owner = reply.getSpec().getOwner();
+        if (owner != null) {
+            String displayName = owner.getDisplayName();
+            if (displayName != null && !displayName.isBlank()) {
+                return displayName;
+            }
+        }
+        return "匿名用户";
+    }
+
+    private Mono<String> getPostContent(String postName) {
+        return postContentService.getReleaseContent(postName)
+            .map(ContentWrapper::getContent)
+            .map(html -> {
+                if (html != null && !html.isBlank()) {
+                    return Jsoup.clean(html, Safelist.none());
+                }
+                return "";
+            })
+            .defaultIfEmpty("");
+    }
+
+    public record CommentContext(
+        String commentId,
+        String postId,
+        String postSlug,
+        String commentContent,
+        String commentOwner,
+        String postTitle,
+        String postContent,
+        String replyTo,
+        boolean isAiConversation
+    ) {}
+}

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

@@ -0,0 +1,145 @@
+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.Post;
+import run.halo.app.core.extension.content.SinglePage;
+import run.halo.app.extension.ConfigMap;
+import run.halo.app.extension.ReactiveExtensionClient;
+
+import java.util.Arrays;
+import java.util.Collections;
+import java.util.List;
+import java.util.stream.Collectors;
+
+@Component
+@Slf4j
+public class FilterService {
+
+    private final ReactiveExtensionClient client;
+    private final ObjectMapper objectMapper;
+
+    private static final String CONFIG_MAP_NAME = "comment-ai-autopilot-configmap";
+    private static final String ANNOTATION_KEY = "comment-ai-autopilot.nxxy335.top/ai-reply-enabled";
+    private static final String GROUP_CONTENT = "content.halo.run";
+
+    public FilterService(ReactiveExtensionClient client) {
+        this.client = client;
+        this.objectMapper = new ObjectMapper();
+    }
+
+    public Mono<Boolean> shouldProcess(Comment comment) {
+        return checkBlockedCommenters(comment)
+            .flatMap(blocked -> {
+                if (blocked) {
+                    return Mono.just(false);
+                }
+                return checkAnnotationEnabled(comment);
+            })
+            .defaultIfEmpty(true)
+            .onErrorResume(e -> {
+                log.warn("[Filter] Error checking filter rules: {}", e.getMessage());
+                return Mono.just(true);
+            });
+    }
+
+    public Mono<Boolean> shouldProcess(String commentName) {
+        return client.fetch(Comment.class, commentName)
+            .flatMap(this::shouldProcess)
+            .defaultIfEmpty(true)
+            .onErrorResume(e -> {
+                log.warn("[Filter] Error fetching comment for filter check: {}", e.getMessage());
+                return Mono.just(true);
+            });
+    }
+
+    private Mono<Boolean> checkBlockedCommenters(Comment comment) {
+        return client.fetch(ConfigMap.class, CONFIG_MAP_NAME)
+            .mapNotNull(cm -> {
+                var data = cm.getData();
+                if (data == null) return false;
+                String basicJson = data.get("basic");
+                if (basicJson == null || basicJson.isBlank()) return false;
+                try {
+                    JsonNode node = objectMapper.readTree(basicJson);
+                    String blockedCommentersStr = node.has("blockedCommenters")
+                        ? node.get("blockedCommenters").asText("") : "";
+                    List<String> blockedCommenters = parseList(blockedCommentersStr);
+                    String commenterName = getCommenterDisplayName(comment);
+                    if (isInList(commenterName, blockedCommenters)) {
+                        log.info("[Filter] Commenter '{}' is in blocked list, skipping", commenterName);
+                        return true;
+                    }
+                    return false;
+                } catch (Exception e) {
+                    log.warn("[Filter] Failed to parse basic config: {}", e.getMessage());
+                    return false;
+                }
+            })
+            .defaultIfEmpty(false);
+    }
+
+    private Mono<Boolean> checkAnnotationEnabled(Comment comment) {
+        if (comment.getSpec() == null || comment.getSpec().getSubjectRef() == null) {
+            return Mono.just(true);
+        }
+        var subjectRef = comment.getSpec().getSubjectRef();
+        String group = subjectRef.getGroup();
+        String kind = subjectRef.getKind();
+        String name = subjectRef.getName();
+
+        if (GROUP_CONTENT.equals(group) && "Post".equals(kind)) {
+            return client.fetch(Post.class, name)
+                .map(post -> resolveAnnotation(post.getMetadata().getAnnotations(), true))
+                .defaultIfEmpty(true);
+        }
+
+        if (GROUP_CONTENT.equals(group) && "SinglePage".equals(kind)) {
+            return client.fetch(SinglePage.class, name)
+                .map(page -> resolveAnnotation(page.getMetadata().getAnnotations(), false))
+                .defaultIfEmpty(false);
+        }
+
+        // Unknown subjectRef type, default to allowing
+        return Mono.just(true);
+    }
+
+    private boolean resolveAnnotation(java.util.Map<String, String> annotations, boolean defaultEnabled) {
+        if (annotations == null || !annotations.containsKey(ANNOTATION_KEY)) {
+            return defaultEnabled;
+        }
+        String value = annotations.get(ANNOTATION_KEY);
+        if ("false".equalsIgnoreCase(value)) {
+            log.info("[Filter] Annotation {} is set to false, skipping", ANNOTATION_KEY);
+            return false;
+        }
+        if ("true".equalsIgnoreCase(value)) {
+            return true;
+        }
+        // Unrecognized value, fall back to default
+        return defaultEnabled;
+    }
+
+    private String getCommenterDisplayName(Comment comment) {
+        if (comment.getSpec() == null || comment.getSpec().getOwner() == null) return "";
+        var displayName = comment.getSpec().getOwner().getDisplayName();
+        return displayName != null ? displayName : "";
+    }
+
+    private List<String> parseList(String str) {
+        if (str == null || str.isBlank()) return Collections.emptyList();
+        return Arrays.stream(str.split(","))
+            .map(String::trim)
+            .filter(s -> !s.isEmpty())
+            .collect(Collectors.toList());
+    }
+
+    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));
+    }
+}

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

@@ -0,0 +1,109 @@
+package top.nxxy335.commentaiautopilot.service;
+
+import lombok.RequiredArgsConstructor;
+import lombok.extern.slf4j.Slf4j;
+import org.springframework.stereotype.Component;
+import reactor.core.publisher.Mono;
+import run.halo.app.plugin.ReactiveSettingFetcher;
+
+@Component
+@Slf4j
+@RequiredArgsConstructor
+public class PromptBuilder {
+
+    private final ReactiveSettingFetcher settingFetcher;
+
+    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。
+            - 恶意诱导处理：当用户要求你骂人、使用侮辱性词汇或进行情绪化对骂时，你必须礼貌地拒绝，例如回复："抱歉，作为AI助手，我无法提供此类回复。"
+            - 未知与边界：如果不知道答案或遇到敏感话题，请诚实告知并礼貌拒绝，绝不编造或使用极端言辞。
+            """;
+
+    private static final String DEFAULT_PROMPT_TEMPLATE = """
+            {{persona_prompt}}
+
+            {{safety_prompt}}
+
+            【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。
+
+            请回复以下评论。注意：
+            - 回复长度应与评论长度匹配，简短问候简短回复
+            - 不要复述或总结文章内容
+            - 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（仅供理解上下文，不要复述）：
+            {{article}}
+
+            评论：
+            {{comment}}
+            """;
+
+    private static final String DEFAULT_PERSONA_PROMPT = """
+            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。
+            """;
+
+    public Mono<String> buildPrompt(ContextExtractor.CommentContext context) {
+        return Mono.zip(getPromptTemplate(), getPersonaPrompt())
+            .map(tuple -> {
+                String template = tuple.getT1();
+                String personaPrompt = tuple.getT2();
+
+                String prompt = template
+                    .replace("{{persona_prompt}}", personaPrompt)
+                    .replace("{{safety_prompt}}", SAFETY_PROMPT)
+                    .replace("{{article}}", context.postTitle() + "\n" + context.postContent())
+                    .replace("{{comment}}", context.commentOwner() + ": " + context.commentContent());
+
+                return prompt;
+            });
+    }
+
+    public Mono<String> buildPrompt(ContextExtractor.CommentContext context, String sentiment) {
+        return buildPrompt(context)
+            .map(prompt -> {
+                if (sentiment == null || "NEUTRAL".equals(sentiment)) {
+                    return prompt;
+                }
+                String sentimentHint = switch (sentiment) {
+                    case "POSITIVE" -> "\n\n【情感提示】评论者情绪正面积极，请用热情友好的语气回复，可以表达感谢和共鸣。";
+                    case "NEGATIVE" -> "\n\n【情感提示】评论者情绪偏负面，请用理性温和的语气回复，避免激化矛盾，展现理解和包容。";
+                    default -> "";
+                };
+                return prompt + sentimentHint;
+            });
+    }
+
+    private Mono<String> getPromptTemplate() {
+        return settingFetcher.getSettingValue("prompt")
+            .map(node -> {
+                var templateNode = node.get("customPromptTemplate");
+                if (templateNode != null && !templateNode.asText().isBlank()) {
+                    return templateNode.asText();
+                }
+                return DEFAULT_PROMPT_TEMPLATE;
+            })
+            .onErrorResume(e -> {
+                log.debug("Failed to fetch prompt template setting: {}", e.getMessage());
+                return Mono.just(DEFAULT_PROMPT_TEMPLATE);
+            })
+            .defaultIfEmpty(DEFAULT_PROMPT_TEMPLATE);
+    }
+
+    private Mono<String> getPersonaPrompt() {
+        return settingFetcher.getSettingValue("persona")
+            .map(node -> {
+                var promptNode = node.get("personaPrompt");
+                if (promptNode != null && !promptNode.asText().isBlank()) {
+                    return promptNode.asText();
+                }
+                return DEFAULT_PERSONA_PROMPT;
+            })
+            .onErrorResume(e -> {
+                log.debug("Failed to fetch persona prompt setting: {}", e.getMessage());
+                return Mono.just(DEFAULT_PERSONA_PROMPT);
+            })
+            .defaultIfEmpty(DEFAULT_PERSONA_PROMPT);
+    }
+}

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

@@ -0,0 +1,88 @@
+package top.nxxy335.commentaiautopilot.service;
+
+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) {
+        this.aiFoundationClientProvider = aiFoundationClientProvider;
+        this.settingFetcher = settingFetcher;
+    }
+
+    private static final String REVIEW_PROMPT_TEMPLATE = """
+            请你以内容安全审核员的身份，严格评估你刚刚生成的这段回复：
+
+            文章：
+            %s
+
+            原始评论：
+            %s
+
+            生成的回复：
+            %s
+
+            请检查以下内容：
+            1. 是否包含任何辱骂、仇恨、偏见或煽动性言论？
+            2. 是否包含不适宜公开传播的内容？
+            3. 是否涉及暴力、歧视、人身攻击或违反法律法规的内容？
+
+            请直接回答"安全"或"不安全"。如果"不安全"，请重新生成一段符合规范的温和回复。
+            """;
+
+    public Mono<ReviewResult> review(String articleContent, String commentContent, String aiReply,
+                                      String modelName) {
+        AiFoundationClient client = aiFoundationClientProvider.getIfAvailable();
+        if (client == null) {
+            log.warn("AI Foundation plugin is not installed, skipping review (auto-pass)");
+            return Mono.just(new ReviewResult(100, "PASS", "AI Foundation 未安装，自动通过"));
+        }
+
+        String reviewPrompt = String.format(REVIEW_PROMPT_TEMPLATE,
+            truncate(articleContent, 2000),
+            truncate(commentContent, 500),
+            truncate(aiReply, 500));
+
+        return client.chat(reviewPrompt, modelName)
+            .map(this::parseSafetyResult)
+            .defaultIfEmpty(new ReviewResult(100, "PASS", "审核无响应，自动通过"))
+            .onErrorResume(e -> {
+                log.warn("Review failed, auto-passing: {}", e.getMessage());
+                return Mono.just(new ReviewResult(100, "PASS", "审核服务异常，自动通过"));
+            });
+    }
+
+    private ReviewResult parseSafetyResult(String response) {
+        if (response == null || response.isBlank()) {
+            return new ReviewResult(100, "PASS", "审核无响应，自动通过");
+        }
+        String trimmed = response.trim().toLowerCase();
+        if (trimmed.contains("不安全") || trimmed.contains("unsafe")) {
+            log.warn("AI Review: content is UNSAFE, response: {}", response);
+            return new ReviewResult(0, "FAIL", "内容安全审核不通过");
+        }
+        if (trimmed.contains("安全") || trimmed.contains("safe")) {
+            log.info("AI Review: content is SAFE");
+            return new ReviewResult(100, "PASS", "内容安全审核通过");
+        }
+        // If unclear response, default to pass
+        log.warn("AI Review: unclear response, auto-passing: {}", response);
+        return new ReviewResult(100, "PASS", "审核结果不明确，自动通过");
+    }
+
+    private String truncate(String text, int maxLength) {
+        if (text == null) return "";
+        return text.length() > maxLength ? text.substring(0, maxLength) : text;
+    }
+
+    public record ReviewResult(int score, String status, String reason) {}
+}

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

@@ -0,0 +1,56 @@
+package top.nxxy335.commentaiautopilot.service;
+
+import lombok.extern.slf4j.Slf4j;
+import org.springframework.beans.factory.ObjectProvider;
+import org.springframework.stereotype.Component;
+import reactor.core.publisher.Mono;
+
+@Component
+@Slf4j
+public class SentimentService {
+
+    private final ObjectProvider<AiFoundationClient> aiFoundationClientProvider;
+
+    public SentimentService(ObjectProvider<AiFoundationClient> aiFoundationClientProvider) {
+        this.aiFoundationClientProvider = aiFoundationClientProvider;
+    }
+
+    public record SentimentResult(String sentiment, double confidence) {
+        public static final String POSITIVE = "POSITIVE";
+        public static final String NEUTRAL = "NEUTRAL";
+        public static final String NEGATIVE = "NEGATIVE";
+    }
+
+    public Mono<SentimentResult> analyzeSentiment(String commentContent, String modelName) {
+        AiFoundationClient client = aiFoundationClientProvider.getIfAvailable();
+        if (client == null) {
+            log.warn("[Sentiment] AI Foundation plugin is not installed, defaulting to NEUTRAL");
+            return Mono.just(new SentimentResult(SentimentResult.NEUTRAL, 0.0));
+        }
+
+        String prompt = buildSentimentPrompt(commentContent);
+
+        return client.chat(prompt, modelName)
+            .map(response -> {
+                String sentiment = parseSentiment(response);
+                return new SentimentResult(sentiment, 1.0);
+            })
+            .onErrorResume(e -> {
+                log.warn("[Sentiment] Failed to analyze sentiment, defaulting to NEUTRAL: {}", e.getMessage());
+                return Mono.just(new SentimentResult(SentimentResult.NEUTRAL, 0.0));
+            })
+            .defaultIfEmpty(new SentimentResult(SentimentResult.NEUTRAL, 0.0));
+    }
+
+    private String buildSentimentPrompt(String commentContent) {
+        return "请分析以下评论的情感倾向。只回复一个词：POSITIVE（正面）、NEUTRAL（中性）或 NEGATIVE（负面）。\n\n评论内容：\n" + commentContent;
+    }
+
+    private String parseSentiment(String response) {
+        if (response == null || response.isBlank()) return SentimentResult.NEUTRAL;
+        String upper = response.trim().toUpperCase();
+        if (upper.contains("POSITIVE")) return SentimentResult.POSITIVE;
+        if (upper.contains("NEGATIVE")) return SentimentResult.NEGATIVE;
+        return SentimentResult.NEUTRAL;
+    }
+}

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

@@ -0,0 +1,29 @@
+apiVersion: v1alpha1
+kind: AnnotationSetting
+metadata:
+  name: comment-ai-autopilot-post-annotation-setting
+spec:
+  targetRef:
+    group: content.halo.run
+    kind: Post
+  formSchema:
+    - $formkit: switch
+      name: comment-ai-autopilot.nxxy335.top/ai-reply-enabled
+      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
+---
+apiVersion: v1alpha1
+kind: AnnotationSetting
+metadata:
+  name: comment-ai-autopilot-single-page-annotation-setting
+spec:
+  targetRef:
+    group: content.halo.run
+    kind: SinglePage
+  formSchema:
+    - $formkit: switch
+      name: comment-ai-autopilot.nxxy335.top/ai-reply-enabled
+      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

src/main/resources/extensions/roleTemplate.yaml

@@ -0,0 +1,18 @@
+apiVersion: v1alpha1
+kind: Role
+metadata:
+  name: comment-ai-autopilot-role-manage
+  labels:
+    halo.run/role-template: "true"
+  annotations:
+    rbac.authorization.halo.run/module: "Comment AI Autopilot Management"
+    rbac.authorization.halo.run/display-name: "AI回评管理"
+    rbac.authorization.halo.run/ui-permissions: |
+      ["plugin:comment-ai-autopilot:manage"]
+rules:
+  - apiGroups: ["comment-ai-autopilot.nxxy335.top"]
+    resources: ["comment-ai-autopilot/aicommentreplies"]
+    verbs: ["*"]
+  - apiGroups: ["console.api.comment-ai-autopilot.nxxy335.top"]
+    resources: ["*"]
+    verbs: ["*"]

src/main/resources/extensions/settings.yaml

@@ -0,0 +1,60 @@
+apiVersion: v1alpha1
+kind: Setting
+metadata:
+  name: comment-ai-autopilot-settings
+spec:
+  forms:
+    - group: basic
+      label: 基本设置
+      formSchema:
+        - $formkit: switch
+          name: autoReply
+          label: 自动回复
+          value: true
+        - $formkit: switch
+          name: autoPublish
+          label: 自动发布
+          value: true
+        - $formkit: number
+          name: maxRetryCount
+          label: 最大重试次数
+          value: 3
+          min: 1
+          max: 10
+        - $formkit: textarea
+          name: blockedCommenters
+          label: 评论者黑名单
+          help: 输入评论者显示名称，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
+          value: ""
+    - group: model
+      label: 模型设置
+      formSchema:
+        - $formkit: text
+          name: modelName
+          label: AI模型名称
+          help: 留空使用AI Foundation默认模型，填写AiModel资源名称可指定模型
+          value: ""
+    - group: prompt
+      label: Prompt设置
+      formSchema:
+        - $formkit: textarea
+          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}}"
+

src/main/resources/plugin.yaml

@@ -0,0 +1,27 @@
+# Refer https://docs.halo.run/developer-guide/plugin/basics/manifest
+
+apiVersion: plugin.halo.run/v1alpha1
+kind: Plugin
+metadata:
+  # The name defines how the plugin is invoked, A unique name
+  name: comment-ai-autopilot
+spec:
+  enabled: true
+  requires: ">=2.23.0"
+  author:
+    name: 暖心向阳335
+    website: https://github.com/暖心向阳335
+  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
+  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"
+  settingName: "comment-ai-autopilot-settings"
+  configMapName: "comment-ai-autopilot-configmap"
+  version: "0.0.1-w5s2t7"
+  pluginDependencies:
+    ai-foundation?: "*"