web/src/jmap/types.ts

@@ -268,6 +268,8 @@ export interface Email {
   "header:Received:asText:all"?: string[] | null;
   "header:X-Spam-Status:asText"?: string | null;
   "header:X-Spam-Result:asText"?: string | null;
+  /** inbuxa: the language model's opinion, when AI spam classification is on (lib/llmOpinion). */
+  "header:X-Spam-LLM:asText"?: string | null;
 }
 
 export interface Thread {

web/src/lib/__tests__/llmOpinion.test.ts

@@ -0,0 +1,52 @@
+import { describe, expect, it } from "vitest";
+import { LLM_HEADER_PROP, llmOpinion, parseLlmOpinion } from "@/lib/llmOpinion";
+
+/*
+ * The header as inbuxa-server writes it (crates/features/src/ai/answer.rs):
+ * `X-Spam-LLM: <TAG>`, optionally followed by the explanation in one pair of
+ * parentheses, folded at 78 columns.
+ */
+describe("parseLlmOpinion", () => {
+  it("reads category, confidence and explanation", () => {
+    expect(parseLlmOpinion("LLM_UNSOLICITED_HIGH (Promotes a product the reader never asked about)")).toEqual({
+      tag: "LLM_UNSOLICITED_HIGH",
+      category: "Unsolicited",
+      confidence: "High",
+      explanation: "Promotes a product the reader never asked about",
+    });
+  });
+
+  it("reads a tag with no confidence and no explanation", () => {
+    expect(parseLlmOpinion("LLM_LEGITIMATE")).toEqual({
+      tag: "LLM_LEGITIMATE",
+      category: "Legitimate",
+      confidence: null,
+      explanation: null,
+    });
+  });
+
+  it("keeps an operator's multi-word category whole", () => {
+    const o = parseLlmOpinion("LLM_COLD_OUTREACH_MEDIUM");
+    expect(o?.category).toBe("Cold outreach");
+    expect(o?.confidence).toBe("Medium");
+    // An unknown last word is part of the category, not a confidence.
+    expect(parseLlmOpinion("LLM_COLD_OUTREACH")?.category).toBe("Cold outreach");
+    expect(parseLlmOpinion("LLM_COLD_OUTREACH")?.confidence).toBeNull();
+  });
+
+  it("unfolds a folded header and keeps inner parentheses", () => {
+    const o = parseLlmOpinion("LLM_HARMFUL_LOW (Asks for a password\r\n  (urgently) via a link)");
+    expect(o?.explanation).toBe("Asks for a password (urgently) via a link");
+  });
+
+  it("returns null for anything that isn't the server's tag", () => {
+    for (const raw of [null, undefined, "", "   ", "Yes, score=6.7", "LLM_", "llm_unsolicited_high", "X LLM_SPAM"]) {
+      expect(parseLlmOpinion(raw), String(raw)).toBeNull();
+    }
+  });
+
+  it("reads the JMAP property a full message carries", () => {
+    expect(llmOpinion({ [LLM_HEADER_PROP]: "LLM_LEGITIMATE_HIGH" })?.category).toBe("Legitimate");
+    expect(llmOpinion({})).toBeNull();
+  });
+});

web/src/lib/llmOpinion.ts

@@ -0,0 +1,80 @@
+/**
+ * inbuxa: the language model's opinion, read back off the message.
+ *
+ * When the server's AI spam classification is on (inbuxa-server,
+ * docs/spec/features/ai-spam-classification.md), it writes the model's answer
+ * into an `X-Spam-LLM` header at delivery:
+ *
+ *     X-Spam-LLM: LLM_UNSOLICITED_HIGH (Promotes a product the reader never asked about)
+ *
+ * a tag, then optionally the model's explanation in parentheses. The tag is
+ * `LLM_` + category, or `LLM_` + category + `_` + confidence, uppercased with
+ * anything outside A-Z and 0-9 turned into `_`. The explanation is already
+ * sanitized by the server and may arrive as encoded words, which the JMAP
+ * `asText` form decodes.
+ *
+ * Like `spamScore`, nothing here judges anything: it only reads what the
+ * server wrote. It is one signal the spam filter weighed among many, and the
+ * UI says so.
+ */
+
+/** The JMAP property that carries the header, decoded and unfolded. */
+export const LLM_HEADER_PROP = "header:X-Spam-LLM:asText" as const;
+
+/**
+ * Confidence words the fork's default prompt uses. A tag ending in one of
+ * these is read as category + confidence; anything else is all category,
+ * since an operator's own categories may contain underscores.
+ */
+const CONFIDENCES = new Set(["LOW", "MEDIUM", "HIGH"]);
+
+export interface LlmOpinion {
+  /** The tag as the server wrote it, e.g. `LLM_UNSOLICITED_HIGH`. */
+  tag: string;
+  /** Readable category, e.g. `Unsolicited`. */
+  category: string;
+  /** Readable confidence, e.g. `High`, where the tag carried one. */
+  confidence: string | null;
+  /** The model's own explanation, as plain text, where there is one. */
+  explanation: string | null;
+}
+
+/** `UNSOLICITED_BULK` -> `Unsolicited bulk`. */
+function readable(words: string[]): string {
+  const s = words.join(" ").toLowerCase();
+  return s.charAt(0).toUpperCase() + s.slice(1);
+}
+
+/** Headers arrive folded, so tabs and newlines are whitespace like any other. */
+function flatten(v: string | null | undefined): string {
+  return (v ?? "").replace(/\s+/g, " ").trim();
+}
+
+export function parseLlmOpinion(raw: string | null | undefined): LlmOpinion | null {
+  const s = flatten(raw);
+  const m = /^(LLM_[A-Z0-9_]+)(?:\s+(.*))?$/.exec(s);
+  if (!m) return null;
+  const tag = m[1]!;
+  const parts = tag.slice("LLM_".length).split("_").filter(Boolean);
+  if (parts.length === 0) return null;
+
+  let confidence: string | null = null;
+  if (parts.length > 1 && CONFIDENCES.has(parts[parts.length - 1]!)) {
+    confidence = readable([parts.pop()!]);
+  }
+
+  let explanation: string | null = null;
+  const rest = (m[2] ?? "").trim();
+  if (rest) {
+    // The server wraps the explanation in one pair of parentheses.
+    const inner = rest.startsWith("(") && rest.endsWith(")") ? rest.slice(1, -1).trim() : rest;
+    explanation = inner || null;
+  }
+
+  return { tag, category: readable(parts), confidence, explanation };
+}
+
+/** The opinion on a message, if the server recorded one. */
+export function llmOpinion(email: { [LLM_HEADER_PROP]?: string | null }): LlmOpinion | null {
+  return parseLlmOpinion(email[LLM_HEADER_PROP]);
+}

web/src/locales/de.ts

@@ -1740,6 +1740,9 @@ export const catalog: Catalog = {
     "To confirm, type {phrase}": "Zur Bestätigung {phrase} eingeben",
     "Turn off legacy protocols": "Ältere Mailprotokolle ausschalten",
     "Legacy mail protocols are off for your organization. Only {app} and JMAP apps can sign in.": "Ältere Mailprotokolle sind für Ihre Organisation ausgeschaltet. Nur {app} und JMAP-Apps können sich anmelden.",
+    // ── Spam filter: the language model's opinion (inbuxa) ──────────
+    "Language model's opinion": "Einschätzung des Sprachmodells",
+    "One of several signals the spam filter weighed": "Eines von mehreren Signalen, die der Spamfilter berücksichtigt hat",
   },
   plurals: {
     // ── Administration: legacy mail protocols (INBUXA) ──────────────

web/src/locales/es.ts

@@ -1713,6 +1713,9 @@ export const catalog: Catalog = {
     "To confirm, type {phrase}": "Para confirmar, escriba {phrase}",
     "Turn off legacy protocols": "Desactivar los protocolos de correo heredados",
     "Legacy mail protocols are off for your organization. Only {app} and JMAP apps can sign in.": "Los protocolos de correo heredados están desactivados para su organización. Solo {app} y las aplicaciones JMAP pueden iniciar sesión.",
+    // ── Spam filter: the language model's opinion (inbuxa) ──────────
+    "Language model's opinion": "Opinión del modelo de lenguaje",
+    "One of several signals the spam filter weighed": "Una de varias señales que el filtro de spam ha tenido en cuenta",
   },
   plurals: {
     // ── Administration: legacy mail protocols (INBUXA) ──────────────

web/src/locales/fr.ts

@@ -1718,6 +1718,9 @@ export const catalog: Catalog = {
     "To confirm, type {phrase}": "Pour confirmer, saisissez {phrase}",
     "Turn off legacy protocols": "Désactiver les protocoles de messagerie historiques",
     "Legacy mail protocols are off for your organization. Only {app} and JMAP apps can sign in.": "Les protocoles de messagerie historiques sont désactivés pour votre organisation. Seuls {app} et les applications JMAP peuvent se connecter.",
+    // ── Spam filter: the language model's opinion (inbuxa) ──────────
+    "Language model's opinion": "Avis du modèle de langage",
+    "One of several signals the spam filter weighed": "Un signal parmi d'autres pris en compte par le filtre antispam",
   },
   plurals: {
     // ── Administration: legacy mail protocols (INBUXA) ──────────────

web/src/locales/ja.ts

@@ -1721,6 +1721,9 @@ export const catalog: Catalog = {
     "To confirm, type {phrase}": "確認のため {phrase} と入力してください",
     "Turn off legacy protocols": "従来のメールプロトコルをオフにする",
     "Legacy mail protocols are off for your organization. Only {app} and JMAP apps can sign in.": "組織では従来のメールプロトコルがオフになっています。サインインできるのは {app} と JMAP アプリのみです。",
+    // ── Spam filter: the language model's opinion (inbuxa) ──────────
+    "Language model's opinion": "言語モデルの見解",
+    "One of several signals the spam filter weighed": "迷惑メールフィルターが考慮した複数の判断材料のひとつ",
   },
   plurals: {
     // ── Administration: legacy mail protocols (INBUXA) ──────────────

web/src/locales/nl.ts

@@ -1710,6 +1710,9 @@ export const catalog: Catalog = {
     "To confirm, type {phrase}": "Typ ter bevestiging {phrase}",
     "Turn off legacy protocols": "Verouderde mailprotocollen uitschakelen",
     "Legacy mail protocols are off for your organization. Only {app} and JMAP apps can sign in.": "Verouderde mailprotocollen zijn uitgeschakeld voor uw organisatie. Alleen {app} en JMAP-apps kunnen inloggen.",
+    // ── Spam filter: the language model's opinion (inbuxa) ──────────
+    "Language model's opinion": "Oordeel van het taalmodel",
+    "One of several signals the spam filter weighed": "Een van meerdere signalen die het spamfilter heeft meegewogen",
   },
   plurals: {
     // ── Administration: legacy mail protocols (INBUXA) ──────────────

web/src/locales/pt-BR.ts

@@ -1716,6 +1716,9 @@ export const catalog: Catalog = {
     "To confirm, type {phrase}": "Para confirmar, digite {phrase}",
     "Turn off legacy protocols": "Desativar os protocolos de e-mail legados",
     "Legacy mail protocols are off for your organization. Only {app} and JMAP apps can sign in.": "Os protocolos de e-mail legados estão desativados para sua organização. Só {app} e aplicativos JMAP podem entrar.",
+    // ── Spam filter: the language model's opinion (inbuxa) ──────────
+    "Language model's opinion": "Opinião do modelo de linguagem",
+    "One of several signals the spam filter weighed": "Um dos vários sinais considerados pelo filtro de spam",
   },
   plurals: {
     // ── Administration: legacy mail protocols (INBUXA) ──────────────

web/src/locales/ru.ts

@@ -1715,6 +1715,9 @@ export const catalog: Catalog = {
     "To confirm, type {phrase}": "Для подтверждения введите {phrase}",
     "Turn off legacy protocols": "Отключить устаревшие почтовые протоколы",
     "Legacy mail protocols are off for your organization. Only {app} and JMAP apps can sign in.": "Устаревшие почтовые протоколы отключены для вашей организации. Входить могут только {app} и приложения JMAP.",
+    // ── Spam filter: the language model's opinion (inbuxa) ──────────
+    "Language model's opinion": "Мнение языковой модели",
+    "One of several signals the spam filter weighed": "Один из нескольких признаков, которые учёл спам-фильтр",
   },
   plurals: {
     // ── Administration: legacy mail protocols (INBUXA) ──────────────

web/src/locales/uk.ts

@@ -1709,6 +1709,9 @@ export const catalog: Catalog = {
     "To confirm, type {phrase}": "Для підтвердження введіть {phrase}",
     "Turn off legacy protocols": "Вимкнути застарілі поштові протоколи",
     "Legacy mail protocols are off for your organization. Only {app} and JMAP apps can sign in.": "Застарілі поштові протоколи вимкнено для вашої організації. Входити можуть лише {app} і програми JMAP.",
+    // ── Spam filter: the language model's opinion (inbuxa) ──────────
+    "Language model's opinion": "Думка мовної моделі",
+    "One of several signals the spam filter weighed": "Одна з кількох ознак, які врахував спам-фільтр",
   },
   plurals: {
     // ── Administration: legacy mail protocols (INBUXA) ──────────────

web/src/locales/zh-Hans.ts

@@ -1720,6 +1720,9 @@ export const catalog: Catalog = {
     "To confirm, type {phrase}": "请输入 {phrase} 以确认",
     "Turn off legacy protocols": "关闭传统邮件协议",
     "Legacy mail protocols are off for your organization. Only {app} and JMAP apps can sign in.": "您的组织已关闭传统邮件协议。只有 {app} 和 JMAP 应用可以登录。",
+    // ── Spam filter: the language model's opinion (inbuxa) ──────────
+    "Language model's opinion": "语言模型的判断",
+    "One of several signals the spam filter weighed": "垃圾邮件过滤考虑的多个信号之一",
   },
   plurals: {
     // ── Administration: legacy mail protocols (INBUXA) ──────────────

web/src/store/mail/props.ts

@@ -1,4 +1,5 @@
 import { SPAM_HEADER_PROPS } from "@/lib/spamScore";
+import { LLM_HEADER_PROP } from "@/lib/llmOpinion";
 
 
 /*
@@ -67,6 +68,8 @@ export const FULL_PROPS = [
   "header:Precedence:asText",
   "header:Authentication-Results:asText",
   ...SPAM_HEADER_PROPS,
+  // inbuxa: the language model's opinion, when the server wrote one
+  LLM_HEADER_PROP,
 ];
 
 export const BODY_PROPS = ["partId", "blobId", "size", "name", "type", "charset", "disposition", "cid", "language", "location", "subParts", "headers"];

web/src/styles/app.css

@@ -2387,6 +2387,13 @@ button.dp-open:disabled { cursor: default; opacity: .5; }
 .spam-weight.bad { color: var(--danger); }
 .spam-weight.good { color: var(--success); }
 
+/* inbuxa: the language model's opinion, in the details and above a message in
+   Junk (views/mail/LlmOpinion.tsx). The explanation is the model's own words,
+   so it keeps its line breaks out and wraps rather than widening the pane. */
+.llm-opinion { display: flex; flex-direction: column; gap: 4px; }
+.llm-heading { display: inline-flex; flex-wrap: wrap; gap: .4em; align-items: baseline; }
+.llm-explanation { overflow-wrap: anywhere; }
+
 /* The placeholder reference under a template's body. */
 .placeholder-list { display: grid; grid-template-columns: auto 1fr; gap: 4px 12px; align-items: baseline; }
 .placeholder-row { display: contents; }

web/src/views/mail/LlmOpinion.tsx

@@ -0,0 +1,67 @@
+import { Bot } from "lucide-react";
+import type { LlmOpinion } from "@/lib/llmOpinion";
+import { t as translate } from "@/lib/i18n";
+
+/*
+ * inbuxa: the language model's opinion on a message, where the server's AI
+ * spam classification recorded one (lib/llmOpinion).
+ *
+ * Two rules, both from the server's spec. It is always labeled as one signal
+ * the spam filter weighed among several, never as the reason a message was
+ * filed where it was: the model can add a bounded amount to the score and no
+ * more. And the explanation is the model's own output, so it is only ever
+ * rendered as text.
+ *
+ * The category and confidence come from the server's configuration and aren't
+ * translated; only the two framing strings are.
+ */
+
+function Verdict({ opinion }: { opinion: LlmOpinion }) {
+  return (
+    <>
+      <strong>{opinion.category}</strong>
+      {opinion.confidence && <span className="hint">{` · ${opinion.confidence}`}</span>}
+    </>
+  );
+}
+
+/** In the message details, beside the spam filter's own working. */
+export function LlmOpinionDetail({ opinion }: { opinion: LlmOpinion }) {
+  return (
+    <div className="llm-opinion">
+      <div>
+        <Verdict opinion={opinion} />
+      </div>
+      {opinion.explanation && <div className="llm-explanation">{opinion.explanation}</div>}
+      <div className="hint">{translate("One of several signals the spam filter weighed")}</div>
+    </div>
+  );
+}
+
+/** Above a message that's in Junk. */
+export function LlmOpinionBanner({ opinion }: { opinion: LlmOpinion }) {
+  return (
+    <div className="remote-banner llm-banner" role="note" style={{ margin: "0 16px 8px" }}>
+      <Bot size={16} />
+      <span className="grow llm-opinion">
+        <span className="llm-heading">
+          <span>{translate("Language model's opinion")}</span>
+          <span>
+            <Verdict opinion={opinion} />
+          </span>
+        </span>
+        {opinion.explanation && <span className="llm-explanation">{opinion.explanation}</span>}
+        <span className="hint">{translate("One of several signals the spam filter weighed")}</span>
+      </span>
+    </div>
+  );
+}
+
+/** The banner shows only for a message in Junk that carries an opinion. */
+export function llmBannerOpinion(
+  opinion: LlmOpinion | null,
+  mailboxIds: Record<string, boolean>,
+  junkId: string | null | undefined,
+): LlmOpinion | null {
+  return opinion && junkId && mailboxIds[junkId] ? opinion : null;
+}

web/src/views/mail/MessageView.tsx

@@ -15,6 +15,8 @@ import { emlFilename } from "@/lib/text/emlName";
 import { isTnef, parseTnef, type TnefAttachment } from "@/lib/tnef";
 import { internalDomains, isExternalSender, linkVerdict } from "@/lib/warnings";
 import { spamReport, type SpamReport } from "@/lib/spamScore";
+import { llmOpinion } from "@/lib/llmOpinion";
+import { LlmOpinionBanner, LlmOpinionDetail, llmBannerOpinion } from "./LlmOpinion";
 import { formatFullDate, formatListDate, formatSize } from "@/lib/format";
 import { displayName, domainOf, formatAddress } from "@/lib/address";
 import { EMAIL_BASE_CSS, TEXT_EMAIL_CSS, hasHtmlAlternative, htmlDeclaresColors, markKeptSurfaces, sanitizeEmailHtml } from "@/lib/text/html";
@@ -187,6 +189,10 @@ export const MessageView = memo(function MessageView({ email: e, expanded, wasUn
   const receiptRequested = Boolean(e["header:Disposition-Notification-To:asAddresses"]?.length);
   const authFailed = /\b(dkim|spf|dmarc)=fail\b/i.test(e["header:Authentication-Results:asText"] ?? "");
   const spam = useMemo(() => spamReport(e), [e]);
+  // inbuxa: the language model's opinion, where the server's AI spam classification wrote one
+  const llm = useMemo(() => llmOpinion(e), [e]);
+  const junkId = useMail((st) => st.roleId("junk"));
+  const llmBanner = llmBannerOpinion(llm, e.mailboxIds, junkId);
   const identities = useMail((st) => st.identities);
   /*
    * Only computed when the warning is on, because the domains it compares
@@ -374,6 +380,7 @@ export const MessageView = memo(function MessageView({ email: e, expanded, wasUn
               {e["header:List-Id:asText"] && <><dt>{translate("List")}</dt><dd>{e["header:List-Id:asText"]}</dd></>}
               <dt>{translate("Size")}</dt><dd>{formatSize(e.size)}</dd>
               {spam && <><dt>{translate("Spam filter")}</dt><dd><SpamSummary report={spam} /></dd></>}
+              {llm && <><dt>{translate("Language model's opinion")}</dt><dd><LlmOpinionDetail opinion={llm} /></dd></>}
               {receiptRequested && <><dt>{translate("Receipt")}</dt><dd>{receipt.offer ? translate("Requested, to {address}. Never sent automatically.", { address: receipt.to!.email }) : translate(refusalText(receipt.refusal!))}</dd></>}
             </dl>
           )}
@@ -425,6 +432,7 @@ export const MessageView = memo(function MessageView({ email: e, expanded, wasUn
             </div>
           )}
           <SignatureBanner state={signature} />
+          {llmBanner && <LlmOpinionBanner opinion={llmBanner} />}
           {externalSender && (
             <div className="remote-banner external-banner" style={{ margin: "0 16px 8px" }}>
               <ShieldAlert size={16} />

web/src/views/mail/__tests__/llm-opinion.test.tsx

@@ -0,0 +1,73 @@
+import { act } from "react";
+import { createRoot, type Root } from "react-dom/client";
+import { afterEach, beforeEach, describe, expect, it } from "vitest";
+import { LlmOpinionBanner, LlmOpinionDetail, llmBannerOpinion } from "../LlmOpinion";
+import { parseLlmOpinion, type LlmOpinion } from "@/lib/llmOpinion";
+
+(globalThis as { IS_REACT_ACT_ENVIRONMENT?: boolean }).IS_REACT_ACT_ENVIRONMENT = true;
+
+/*
+ * The framing is the feature: the model's opinion is always one signal among
+ * several, never presented as why a message is where it is, and its
+ * explanation is model output, so it must never be rendered as markup.
+ */
+const opinion = (raw: string) => parseLlmOpinion(raw) as LlmOpinion;
+
+describe("the language model's opinion", () => {
+  let host: HTMLDivElement;
+  let root: Root;
+
+  const render = async (node: React.ReactNode) => {
+    await act(async () => {
+      root.render(node);
+    });
+  };
+
+  beforeEach(() => {
+    host = document.createElement("div");
+    document.body.appendChild(host);
+    root = createRoot(host);
+  });
+
+  afterEach(async () => {
+    await act(async () => root.unmount());
+    host.remove();
+  });
+
+  it("shows category, confidence and explanation, as one signal of several", async () => {
+    await render(<LlmOpinionDetail opinion={opinion("LLM_UNSOLICITED_HIGH (Sells something unasked)")} />);
+    expect(host.textContent).toContain("Unsolicited");
+    expect(host.textContent).toContain("High");
+    expect(host.textContent).toContain("Sells something unasked");
+    expect(host.textContent).toContain("One of several signals the spam filter weighed");
+  });
+
+  it("renders the explanation as text, never markup", async () => {
+    await render(<LlmOpinionDetail opinion={opinion('LLM_HARMFUL_HIGH (<img src=x onerror="alert(1)"> <b>bold</b>)')} />);
+    expect(host.querySelector("img")).toBeNull();
+    expect(host.querySelector("b")).toBeNull();
+    expect(host.textContent).toContain('<img src=x onerror="alert(1)">');
+  });
+
+  it("leaves out what the header didn't carry", async () => {
+    await render(<LlmOpinionDetail opinion={opinion("LLM_LEGITIMATE")} />);
+    expect(host.querySelector(".llm-explanation")).toBeNull();
+    expect(host.textContent).not.toContain("·");
+  });
+
+  it("banners a message in Junk with the same framing", async () => {
+    await render(<LlmOpinionBanner opinion={opinion("LLM_UNSOLICITED_MEDIUM (Bulk newsletter)")} />);
+    expect(host.textContent).toContain("Language model's opinion");
+    expect(host.textContent).toContain("Unsolicited");
+    expect(host.textContent).toContain("Bulk newsletter");
+    expect(host.textContent).toContain("One of several signals the spam filter weighed");
+  });
+
+  it("banners only a message that's in Junk and carries an opinion", () => {
+    const o = opinion("LLM_UNSOLICITED_HIGH");
+    expect(llmBannerOpinion(o, { junk1: true }, "junk1")).toBe(o);
+    expect(llmBannerOpinion(o, { inbox1: true }, "junk1")).toBeNull();
+    expect(llmBannerOpinion(o, { junk1: true }, null)).toBeNull();
+    expect(llmBannerOpinion(null, { junk1: true }, "junk1")).toBeNull();
+  });
+});