fix(automod): flow real LLM analysis + descriptive fallback
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Root cause: ai-analysis-worker read llmResult.explanation and llmResult.toxicityScore — fields the LLM pipeline never produces (canonical AnalysisResult uses analysis/score). Every message fell back to the bare template "Tidak ada indikasi pelanggaran." and the stored score was always 0. - Map analysis/score correctly; fallback now quotes the message content - Prompt: ban generic analysis phrasing, require reply context - LLM context: include replied-to message content (metadata.reference) so the model can explain what the user is replying to - Frontend: show thread/channel names from metadata instead of raw IDs (message card, detail views, search overlay); detail panel now displays the ai_analysis text - Auto-delete log/DM include the descriptive analysis as the reason
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@@ -1,9 +1,10 @@
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"use client";
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import { ArrowLeft, MessageSquare } from "lucide-react";
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import { ArrowLeft, MessageSquare, MessagesSquare } from "lucide-react";
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import { GlassCard } from "@/components/glass/card";
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import { AttachmentsGrid } from "./attachments-grid";
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import { AiAnalysisPanel } from "./ai-analysis-panel";
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import { getMessageChannelLabel } from "@/lib/format";
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import type { AttachmentRecord, MessageRecord } from "@/lib/types";
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interface MessageDetailViewProps {
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@@ -25,7 +26,10 @@ export function MessageDetailView({ message, attachments, onBack }: MessageDetai
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<div className="flex items-center gap-2 mb-3">
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<MessageSquare className="size-4 text-primary" />
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<span className="font-semibold text-sm text-text-primary">{message.username}</span>
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<span className="text-[10px] text-text-secondary/40 font-mono">{message.channel_id?.slice(0, 8)}</span>
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<span className="text-[10px] text-text-secondary/40 font-mono inline-flex items-center gap-1">
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{message.thread_id && <MessagesSquare className="size-3" />}
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{getMessageChannelLabel(message)}
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</span>
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</div>
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{/* Content */}
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@@ -49,6 +53,7 @@ export function MessageDetailView({ message, attachments, onBack }: MessageDetai
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categories={message.ai_categories}
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action={message.ai_recommended_action}
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score={message.ai_moderation_score}
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analysis={message.ai_analysis}
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/>
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</GlassCard>
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);
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