fix(ai): store chatContextWindow as a JSON number, not a ::text string

chatContextWindow (#189) is the first numeric provider field routed
through WorkspaceRepo.updateAiProviderSettings, whose patch builder cast
every value as `${v}::text`. The DTO validates it as @IsInt(), so a JS
number 200000 was stored as the JSON STRING "200000". The client guards
require `typeof === "number"` (ai-chat-window.tsx, context-badge.tsx),
so the `/ max` badge denominator never rendered and the whole feature
silently no-opped.

Branch the jsonb_build_object value cast by JS runtime type: numbers ->
::numeric (real JSON number), booleans -> ::boolean, everything else ->
::text (unchanged for the existing string fields). This is the root fix
(store as a real number) rather than coercing on read, so every reader
sees the correct type.

Add a DB round-trip int-spec asserting
jsonb_typeof(settings->'ai'->'provider'->'chatContextWindow') = 'number'
and that the value re-reads as the number 200000, including the
partial-merge path. CHANGELOG: Added entry for the chatContextWindow
setting and a Changed entry for the badge's new "used / max" meaning.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

CHANGELOG.md

@@ -43,6 +43,13 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
   OpenRouter, etc.; `openai` uses the official provider (real-OpenAI
   reasoning-model request shaping). Chosen explicitly rather than inferred from
   the base URL, since a custom URL can front real OpenAI too. (#175, #177)
+- **AI chat "Context window (tokens)" setting (`chatContextWindow`).** A new
+  admin field in AI settings that records the chat model's context-window size.
+  When set (> 0) it becomes the denominator of the header context-badge, which
+  now reads "used / max"; `0`/empty clears the limit and the badge shows only
+  the current context as before. There is no provider-independent way to read a
+  model's window automatically, so it is an explicit workspace-level value.
+  (#189)
 - **Per-MCP-server instructions in the agent prompt.** Each external MCP server
   now has an admin-authored `instructions` field ("how/when to use this server's
   tools") that is injected into the agent's system prompt next to that server's
@@ -61,6 +68,12 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
   model's reasoning out of the box. An endpoint that is real OpenAI behind a
   custom base URL should set the new `chatApiStyle` "Protocol" to `openai`. (#177)
 
+- **AI chat header context-badge now shows "used / max".** When an admin sets
+  the new `chatContextWindow`, the badge displays the current context size over
+  the configured window (e.g. `120k / 200k`) instead of switching to a live
+  per-turn token counter during streaming. With no window configured the badge
+  keeps showing just the current context. (#189)
+
 - **Footnotes now reuse (Pandoc semantics).** Multiple `[^a]` references to the
   same id are ONE footnote — one number, one definition, several back-references
   — instead of being renamed to `a__2`, `a__3`. Duplicate `[^a]:` definitions are
@@ -78,13 +91,6 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Fixed
 
-- **AI chat: the desktop app no longer freezes at 100% CPU on long agent runs.**
-  `useChat` re-rendered on every streamed token and `MessageItem`/`ReasoningBlock`
-  re-parsed the whole transcript markdown (marked + DOMPurify) on every delta, so
-  per-turn work grew quadratically and saturated the main thread. The stream is now
-  throttled (`experimental_throttle`) to ~20 Hz and each finalized message row /
-  markdown part / reasoning block is memoized, so a long turn no longer re-parses
-  already-finished content. (#182)
 - **Editor: caret/selection landed on the wrong line when clicking inside code
   blocks and footnotes.** The affected NodeViews rendered their non-editable
   chrome (language menu, footnotes heading, footnote number marker) before the

apps/client/public/locales/en-US/translation.json

@@ -1168,7 +1168,10 @@
   "Built-in assistant persona": "Built-in assistant persona",
   "Minimize": "Minimize",
   "Current context size": "Current context size",
-  "Tokens generated this turn": "Tokens generated this turn",
+  "Context size / model limit": "Context size / model limit",
+  "Context window (tokens)": "Context window (tokens)",
+  "Shows used / total in the chat header badge; empty hides the total.": "Shows used / total in the chat header badge; empty hides the total.",
+  "e.g. 200000": "e.g. 200000",
   "AI agent": "AI agent",
   "Take a look at the current document": "Take a look at the current document",
   "AI agent is typing…": "AI agent is typing…",

apps/client/public/locales/ru-RU/translation.json

@@ -705,7 +705,10 @@
   "Copy chat": "Копировать чат",
   "Created successfully": "Успешно создано",
   "Current context size": "Текущий размер контекста",
-  "Tokens generated this turn": "Токенов сгенерировано за ход",
+  "Context size / model limit": "Размер контекста / лимит модели",
+  "Context window (tokens)": "Размер окна контекста (токены)",
+  "Shows used / total in the chat header badge; empty hides the total.": "Показывает использовано/всего в шапке чата; пусто — скрыть лимит.",
+  "e.g. 200000": "напр. 200000",
   "Delete this chat?": "Удалить этот чат?",
   "Deleted successfully": "Успешно удалено",
   "Edited by AI agent on behalf of {{name}}": "Отредактировано AI-агентом от имени {{name}}",

apps/client/src/features/ai-chat/components/ai-chat-window.tsx

@@ -6,7 +6,7 @@ import {
   useRef,
   useState,
 } from "react";
-import { Group, Loader, Tooltip } from "@mantine/core";
+import { Group, Loader } from "@mantine/core";
 import {
   IconArrowsDiagonal,
   IconCheck,
@@ -39,6 +39,7 @@ import {
 } from "@/features/ai-chat/queries/ai-chat-query.ts";
 import ConversationList from "@/features/ai-chat/components/conversation-list.tsx";
 import ChatThread from "@/features/ai-chat/components/chat-thread.tsx";
+import { ContextBadge } from "@/features/ai-chat/components/context-badge.tsx";
 import { exportAiChat } from "@/features/ai-chat/services/ai-chat-service.ts";
 import { useChatSession } from "@/features/ai-chat/hooks/use-chat-session.ts";
 import {
@@ -60,13 +61,6 @@ const MIN_HEIGHT = 400;
 // Margin kept between the window and the viewport edges while dragging.
 const EDGE_MARGIN = 8;
 
-/** Compact token formatter: 1.2M / 3.4k / 950. */
-function formatTokens(n: number): string {
-  if (n >= 1_000_000) return `${(n / 1_000_000).toFixed(1)}M`;
-  if (n >= 1_000) return `${(n / 1_000).toFixed(1)}k`;
-  return String(n);
-}
-
 // Compute the initial top-right placement at the default size, fitted to the
 // current viewport. Reads `window` only when called (inside an effect).
 function computeInitialGeom() {
@@ -161,12 +155,6 @@ export default function AiChatWindow() {
   const { data: messageRows, isLoading: messagesLoading } =
     useAiChatMessagesQuery(activeChatId ?? undefined);
 
-  // Live turn-token total (reasoning + output) for the in-flight turn, pushed up
-  // (THROTTLED to ~8 Hz inside ChatThread) so the header badge ticks mid-stream.
-  // `null` means no turn is in flight -> the badge falls back to the persisted
-  // context size below.
-  const [liveTurnTokens, setLiveTurnTokens] = useState<number | null>(null);
-
   // The page the user is currently viewing. AiChatWindow lives in a pathless
   // parent layout route, so useParams() can't see :pageSlug. Match the full
   // pathname against the authenticated page route instead so "the current page"
@@ -306,6 +294,21 @@ export default function AiChatWindow() {
     return 0;
   }, [activeChatId, messageRows]);
 
+  // The model's context-window size (badge denominator), read from the most
+  // recent assistant row that carries it. Admin-configured in AI settings and
+  // stamped onto the turn server-side, so it travels with the message metadata —
+  // no client-side model resolution, and it survives public shares / per-role
+  // models automatically. 0 (no limit configured, or older rows) → the badge
+  // hides the denominator and shows only the current context size.
+  const maxContextTokens = useMemo(() => {
+    if (!activeChatId || !messageRows) return 0;
+    for (let i = messageRows.length - 1; i >= 0; i--) {
+      const max = messageRows[i].metadata?.maxContextTokens;
+      if (typeof max === "number" && max > 0) return max;
+    }
+    return 0;
+  }, [activeChatId, messageRows]);
+
   // On (re)open, settle the geometry before paint (useLayoutEffect → no
   // first-frame jump): compute an initial top-right placement the first time,
   // and re-clamp an existing geometry to the current viewport on later opens
@@ -495,23 +498,14 @@ export default function AiChatWindow() {
         )}
 
         <div style={{ flex: 1, display: "flex", justifyContent: "center" }}>
-          {/* While a turn streams, show the LIVE turn-token count (ticks ~8 Hz);
-              once it finishes, fall back to the persisted context size. Require
-              > 0 so the very first emit (an empty tail message, count 0) does not
-              flash a "0" badge before any token streams in (#151 review). */}
-          {liveTurnTokens !== null && liveTurnTokens > 0 ? (
-            <Tooltip label={t("Tokens generated this turn")} withArrow>
-              <span className={classes.badge}>
-                {formatTokens(liveTurnTokens)}
-              </span>
-            </Tooltip>
-          ) : contextTokens > 0 ? (
-            <Tooltip label={t("Current context size")} withArrow>
-              <span className={classes.badge}>
-                {formatTokens(contextTokens)}
-              </span>
-            </Tooltip>
-          ) : null}
+          {/* Context badge: always "current / max" context size (or just current
+              when no model limit is configured). It no longer flips to a live
+              per-turn generation counter mid-stream — that live feedback lives in
+              the chat body's "Thinking · N tokens" block. */}
+          <ContextBadge
+            contextTokens={contextTokens}
+            maxContextTokens={maxContextTokens}
+          />
         </div>
 
         <div style={{ display: "flex", alignItems: "center", gap: 1 }}>
@@ -634,7 +628,6 @@ export default function AiChatWindow() {
               assistantName={currentRole?.name}
               onTurnFinished={onTurnFinished}
               onServerChatId={onServerChatId}
-              onLiveTurnTokens={setLiveTurnTokens}
             />
           )}
         </div>

apps/client/src/features/ai-chat/components/chat-thread.tsx

@@ -20,7 +20,6 @@ import {
 } from "@/features/ai-chat/utils/role-launch.ts";
 import { describeChatError } from "@/features/ai-chat/utils/error-message.ts";
 import { extractServerChatId } from "@/features/ai-chat/utils/adopt-chat-id.ts";
-import { liveTurnTokens } from "@/features/ai-chat/utils/count-stream-tokens.ts";
 import {
   dequeue,
   enqueueMessage,
@@ -29,14 +28,6 @@ import {
 } from "@/features/ai-chat/utils/queue-helpers.ts";
 import classes from "@/features/ai-chat/components/ai-chat.module.css";
 
-// Throttle how often the streamed `messages` state triggers a re-render. Without
-// it, useChat updates state on EVERY token, so the whole transcript's markdown
-// (marked + DOMPurify) is re-parsed per token — on a long agent run that grows
-// into a quadratic CPU storm that pins the main thread and freezes the UI.
-// ~50ms (20 Hz) keeps streaming visually smooth while decoupling re-render cost
-// from the token rate.
-const STREAM_THROTTLE_MS = 50;
-
 /** The page the user is currently viewing, sent as chat context. */
 export interface OpenPageContext {
   id: string;
@@ -75,12 +66,6 @@ interface ChatThreadProps {
    *  Copy/export button available mid-stream). Distinct from onTurnFinished,
    *  which fires only at the terminal outcome. */
   onServerChatId?: (serverChatId?: string) => void;
-  /** Reports the live turn-token total (reasoning + output) for the in-flight
-   *  turn so the parent can show a header badge that ticks mid-stream. THROTTLED
-   *  here (~8 Hz) so the parent re-renders a handful of times a second, not on
-   *  every streamed delta. Called with `null` when no turn is in flight (the
-   *  parent then reverts the badge to the persisted context size). */
-  onLiveTurnTokens?: (tokens: number | null) => void;
 }
 
 /**
@@ -125,7 +110,6 @@ export default function ChatThread({
   assistantName,
   onTurnFinished,
   onServerChatId,
-  onLiveTurnTokens,
 }: ChatThreadProps) {
   const { t } = useTranslation();
 
@@ -254,8 +238,6 @@ export default function ChatThread({
     id: chatStoreId,
     messages: initialMessages,
     transport,
-    // See STREAM_THROTTLE_MS — bounds re-render/markdown-reparse frequency.
-    experimental_throttle: STREAM_THROTTLE_MS,
     // `onFinish` (ai@6 useChat) fires from a `finally` on EVERY terminal outcome
     // — success, user Stop/abort (`isAbort`), network drop (`isDisconnect`), and
     // stream error (`isError`). Keep calling `onTurnFinished()` on all of them
@@ -338,53 +320,6 @@ export default function ChatThread({
   // the SAME on-screen banner text can be mirrored into the export (issue #160).
   const errorView = error ? describeChatError(error.message ?? "", t) : null;
 
-  // Report the live turn-token total to the parent header badge, THROTTLED to
-  // ~8 Hz so the parent re-renders a few times a second instead of on every
-  // streamed delta. The tail assistant message's reasoning+output (estimate while
-  // streaming, authoritative once a step reports usage) is the live figure. When
-  // the turn ends we emit a final exact value, then `null` so the parent reverts
-  // the badge to the persisted context size.
-  const lastEmitRef = useRef(0);
-  const emitTimerRef = useRef<ReturnType<typeof setTimeout> | null>(null);
-  useEffect(() => {
-    if (!onLiveTurnTokens) return;
-    if (!isStreaming) {
-      // Turn ended (or never started): clear any pending throttle and revert.
-      if (emitTimerRef.current) {
-        clearTimeout(emitTimerRef.current);
-        emitTimerRef.current = null;
-      }
-      lastEmitRef.current = 0;
-      onLiveTurnTokens(null);
-      return;
-    }
-    const tail = messages[messages.length - 1];
-    const live = tail?.role === "assistant" ? liveTurnTokens(tail) : null;
-    const total = live ? live.reasoning + live.output : 0;
-    const now = Date.now();
-    const MIN_INTERVAL = 120; // ms (~8 Hz)
-    const elapsed = now - lastEmitRef.current;
-    if (elapsed >= MIN_INTERVAL) {
-      lastEmitRef.current = now;
-      onLiveTurnTokens(total);
-    } else if (!emitTimerRef.current) {
-      // Schedule a trailing emit so the FINAL value of a burst is not dropped.
-      emitTimerRef.current = setTimeout(() => {
-        emitTimerRef.current = null;
-        lastEmitRef.current = Date.now();
-        onLiveTurnTokens(total);
-      }, MIN_INTERVAL - elapsed);
-    }
-  }, [messages, isStreaming, onLiveTurnTokens]);
-
-  // Clear any pending throttle timer on unmount (chat switch via `key`) so a
-  // trailing emit can't fire into a torn-down thread's parent.
-  useEffect(() => {
-    return () => {
-      if (emitTimerRef.current) clearTimeout(emitTimerRef.current);
-    };
-  }, []);
-
   // A role was picked with autoStart=false: the role is bound but NOTHING was
   // sent, so chatId stays null and the empty state would keep showing the cards.
   // This flag hides the cards and reveals the composer (with the role indicated)

apps/client/src/features/ai-chat/components/context-badge.test.tsx

@@ -0,0 +1,69 @@
+import { describe, it, expect } from "vitest";
+import { render, screen, fireEvent } from "@testing-library/react";
+import { MantineProvider } from "@mantine/core";
+import { ContextBadge, formatTokens } from "./context-badge";
+
+// matchMedia (read by MantineProvider) is stubbed globally in vitest.setup.ts.
+// Without an I18nextProvider, `t(key)` returns the key verbatim, so tooltip
+// labels assert against their English source strings.
+
+function renderBadge(props: {
+  contextTokens: number;
+  maxContextTokens?: number;
+}) {
+  return render(
+    <MantineProvider>
+      <ContextBadge {...props} />
+    </MantineProvider>,
+  );
+}
+
+describe("formatTokens", () => {
+  it("formats with k / M suffixes", () => {
+    expect(formatTokens(572)).toBe("572");
+    expect(formatTokens(200_000)).toBe("200.0k");
+    expect(formatTokens(1_500_000)).toBe("1.5M");
+  });
+});
+
+describe("ContextBadge", () => {
+  it("shows `current / max` when a limit is configured", () => {
+    renderBadge({ contextTokens: 572, maxContextTokens: 200_000 });
+    expect(screen.getByText("572 / 200.0k")).toBeDefined();
+  });
+
+  it("shows only the current size when no limit is configured", () => {
+    renderBadge({ contextTokens: 572, maxContextTokens: 0 });
+    expect(screen.getByText("572")).toBeDefined();
+    // No denominator rendered.
+    expect(screen.queryByText(/\//)).toBeNull();
+  });
+
+  it("treats an undefined limit as no limit", () => {
+    renderBadge({ contextTokens: 1234 });
+    expect(screen.getByText("1.2k")).toBeDefined();
+    expect(screen.queryByText(/\//)).toBeNull();
+  });
+
+  it("renders nothing until there is a current context size", () => {
+    const { container } = renderBadge({
+      contextTokens: 0,
+      maxContextTokens: 200_000,
+    });
+    expect(container.querySelector("span")).toBeNull();
+  });
+
+  it("never flips to a live per-turn counter (no live mode); shows context as-is even above max", () => {
+    // `current > max` (estimate drift / smaller-model role) is shown unclamped.
+    renderBadge({ contextTokens: 210_000, maxContextTokens: 200_000 });
+    expect(screen.getByText("210.0k / 200.0k")).toBeDefined();
+  });
+
+  it("exposes the limit tooltip label on hover", async () => {
+    renderBadge({ contextTokens: 572, maxContextTokens: 200_000 });
+    fireEvent.mouseEnter(screen.getByText("572 / 200.0k"));
+    expect(
+      await screen.findByText("Context size / model limit"),
+    ).toBeDefined();
+  });
+});

apps/client/src/features/ai-chat/components/context-badge.tsx

@@ -0,0 +1,61 @@
+import { Tooltip } from "@mantine/core";
+import { useTranslation } from "react-i18next";
+import classes from "@/features/ai-chat/components/ai-chat-window.module.css";
+
+/** Compact token formatter: 1.2M / 3.4k / 950. */
+export function formatTokens(n: number): string {
+  if (n >= 1_000_000) return `${(n / 1_000_000).toFixed(1)}M`;
+  if (n >= 1_000) return `${(n / 1_000).toFixed(1)}k`;
+  return String(n);
+}
+
+interface ContextBadgeProps {
+  // Current context size for the active chat (tokens occupied in the model's
+  // window). 0 = unknown → nothing is rendered.
+  contextTokens: number;
+  // The model's context-window size (tokens), from AI settings. 0/undefined =
+  // no limit known → only the current size is shown (no denominator).
+  maxContextTokens?: number;
+}
+
+/**
+ * Header badge that ALWAYS shows the current context size, and — when the model's
+ * context-window size is configured — appends "/ max" so the badge reads
+ * "current / max" (e.g. `572 / 200k`). This is a single, stable meaning: unlike
+ * the previous design it never flips to a live per-turn generation counter while
+ * streaming (that live feedback lives in the chat body's "Thinking · N tokens").
+ *
+ * No limit configured (or older history rows without it) → the denominator is
+ * hidden and the badge shows the current size only, matching the prior at-rest
+ * behaviour. `context > max` (estimate drift, or a role on a smaller model) is
+ * shown as-is, without clamping.
+ */
+export function ContextBadge({
+  contextTokens,
+  maxContextTokens,
+}: ContextBadgeProps) {
+  const { t } = useTranslation();
+
+  // Nothing to show until the first persisted context figure exists.
+  if (!(contextTokens > 0)) return null;
+
+  const hasMax = typeof maxContextTokens === "number" && maxContextTokens > 0;
+  const label = hasMax
+    ? `${formatTokens(contextTokens)} / ${formatTokens(maxContextTokens)}`
+    : formatTokens(contextTokens);
+
+  return (
+    <Tooltip
+      label={
+        hasMax
+          ? t("Context size / model limit")
+          : t("Current context size")
+      }
+      withArrow
+    >
+      <span className={classes.badge}>{label}</span>
+    </Tooltip>
+  );
+}
+
+export default ContextBadge;

apps/client/src/features/ai-chat/components/message-item-memo.test.tsx

@@ -1,81 +0,0 @@
-import { describe, expect, it, vi } from "vitest";
-import { render } from "@testing-library/react";
-import { MantineProvider } from "@mantine/core";
-import type { UIMessage } from "@ai-sdk/react";
-
-// Stub react-i18next (the component reads `useTranslation`). Mirrors the stub in
-// reasoning-block.test.tsx.
-vi.mock("react-i18next", () => ({
-  useTranslation: () => ({ t: (key: string) => key }),
-}));
-
-// Spy on `renderChatMarkdown` so we can count parse calls per text. We keep every
-// OTHER named export of markdown.ts intact via `importActual`, and override only
-// `renderChatMarkdown` with a `vi.fn()` that returns simple HTML so the component
-// still renders. This is the seam that proves the MarkdownPart memo works: a
-// finalized text part must NOT be re-parsed on a later streamed delta.
-// `vi.hoisted` so the spy exists when the hoisted `vi.mock` factory runs.
-const { renderChatMarkdownSpy } = vi.hoisted(() => ({
-  renderChatMarkdownSpy: vi.fn((text: string) => `<p>${text}</p>`),
-}));
-vi.mock("@/features/ai-chat/utils/markdown.ts", async () => {
-  const actual = await vi.importActual<
-    typeof import("@/features/ai-chat/utils/markdown.ts")
-  >("@/features/ai-chat/utils/markdown.ts");
-  return { ...actual, renderChatMarkdown: renderChatMarkdownSpy };
-});
-
-import MessageItem from "./message-item";
-
-// matchMedia (read by MantineProvider) is stubbed globally in vitest.setup.ts.
-
-const msg = (parts: UIMessage["parts"]): UIMessage =>
-  ({ id: "m1", role: "assistant", parts }) as UIMessage;
-
-const renderRow = (message: UIMessage) =>
-  render(
-    <MantineProvider>
-      <MessageItem message={message} />
-    </MantineProvider>,
-  );
-
-/** Count how many spy calls parsed exactly `text` (filtering by the first arg). */
-const callsFor = (text: string) =>
-  renderChatMarkdownSpy.mock.calls.filter((c) => c[0] === text).length;
-
-describe("MessageItem markdown memoization", () => {
-  it("does not re-parse finalized text parts when only a tail part grows", () => {
-    renderChatMarkdownSpy.mockClear();
-
-    // Two finalized text parts.
-    const first = msg([
-      { type: "text", text: "alpha" },
-      { type: "text", text: "beta" },
-    ]);
-    const { rerender } = renderRow(first);
-
-    // Both finalized parts parsed exactly once on the initial render.
-    expect(callsFor("alpha")).toBe(1);
-    expect(callsFor("beta")).toBe(1);
-
-    // A streamed delta: a NEW message object where only a third tail part grows;
-    // the first two parts' text is byte-identical.
-    const next = msg([
-      { type: "text", text: "alpha" },
-      { type: "text", text: "beta" },
-      { type: "text", text: "gamm" },
-    ]);
-    rerender(
-      <MantineProvider>
-        <MessageItem message={next} />
-      </MantineProvider>,
-    );
-
-    // The finalized parts hit the MarkdownPart memo: still parsed at most once
-    // each across BOTH renders (the resilient invariant). The only new parse is
-    // for the changed/added tail part.
-    expect(callsFor("alpha")).toBe(1);
-    expect(callsFor("beta")).toBe(1);
-    expect(callsFor("gamm")).toBe(1);
-  });
-});

apps/client/src/features/ai-chat/components/message-item.test.ts

@@ -1,73 +0,0 @@
-import { describe, expect, it, vi } from "vitest";
-import type { UIMessage } from "@ai-sdk/react";
-
-// Stub react-i18next: importing the component module pulls in `useTranslation`,
-// and we only exercise the pure `arePropsEqual` comparator (no rendering), so a
-// minimal `t` that echoes the key is enough. Mirrors the stub in
-// reasoning-block.test.tsx.
-vi.mock("react-i18next", () => ({
-  useTranslation: () => ({ t: (key: string) => key }),
-}));
-
-import { arePropsEqual } from "./message-item";
-
-/**
- * Tests for `arePropsEqual`, the `React.memo` comparator for MessageItem. It must
- * return false on any visible prop/content change (so the row re-renders) and
- * true when nothing visible changed (so a finalized row is skipped). A FIXED
- * message id is used so a content-identical clone yields an equal signature.
- */
-const msg = (parts: UIMessage["parts"]): UIMessage =>
-  ({ id: "m1", role: "assistant", parts }) as UIMessage;
-
-const props = (
-  message: UIMessage,
-  over: Record<string, unknown> = {},
-) => ({
-  message,
-  showCitations: true,
-  neutralizeInternalLinks: false,
-  assistantName: "AI",
-  ...over,
-});
-
-describe("arePropsEqual", () => {
-  it("returns false when showCitations differs", () => {
-    const m = msg([{ type: "text", text: "answer" }]);
-    expect(
-      arePropsEqual(props(m), props(m, { showCitations: false })),
-    ).toBe(false);
-  });
-
-  it("returns false when neutralizeInternalLinks differs", () => {
-    const m = msg([{ type: "text", text: "answer" }]);
-    expect(
-      arePropsEqual(props(m), props(m, { neutralizeInternalLinks: true })),
-    ).toBe(false);
-  });
-
-  it("returns false when assistantName differs", () => {
-    const m = msg([{ type: "text", text: "answer" }]);
-    expect(
-      arePropsEqual(props(m), props(m, { assistantName: "Other" })),
-    ).toBe(false);
-  });
-
-  it("returns true on the identity fast path (same message object, equal props)", () => {
-    const m = msg([{ type: "text", text: "answer" }]);
-    expect(arePropsEqual(props(m), props(m))).toBe(true);
-  });
-
-  it("returns true for the same content in a different message object", () => {
-    const a = msg([{ type: "text", text: "answer" }]);
-    const b = msg([{ type: "text", text: "answer" }]);
-    expect(a).not.toBe(b);
-    expect(arePropsEqual(props(a), props(b))).toBe(true);
-  });
-
-  it("returns false when content changed in a different message object", () => {
-    const a = msg([{ type: "text", text: "answer" }]);
-    const b = msg([{ type: "text", text: "answer grown" }]);
-    expect(arePropsEqual(props(a), props(b))).toBe(false);
-  });
-});

apps/client/src/features/ai-chat/components/message-item.tsx

@@ -1,4 +1,3 @@
-import { memo } from "react";
 import { Box, Text } from "@mantine/core";
 import { useTranslation } from "react-i18next";
 import type { UIMessage } from "@ai-sdk/react";
@@ -11,7 +10,6 @@ import { assistantMessageHasVisibleContent } from "@/features/ai-chat/utils/mess
 import { renderChatMarkdown } from "@/features/ai-chat/utils/markdown.ts";
 import { resolveAssistantName } from "@/features/ai-chat/utils/assistant-name.ts";
 import { reasoningTokensForPart } from "@/features/ai-chat/utils/reasoning-tokens.ts";
-import { messageSignature } from "@/features/ai-chat/utils/message-signature.ts";
 import { describeChatError } from "@/features/ai-chat/utils/error-message.ts";
 import classes from "@/features/ai-chat/components/ai-chat.module.css";
 
@@ -36,39 +34,6 @@ interface MessageItemProps {
   assistantName?: string;
 }
 
-/**
- * One assistant text part rendered as sanitized markdown. Memoized on its inputs
- * so a finalized text part is NOT re-parsed on every streamed delta: during a
- * turn only the actively-growing tail part changes its `text`, so every earlier
- * part hits the memo and skips the expensive marked + DOMPurify pass. Props are
- * primitives, so React.memo's default shallow compare is exactly right (the
- * `text` string is compared by value).
- */
-const MarkdownPart = memo(function MarkdownPart({
-  text,
-  neutralizeInternalLinks,
-}: {
-  text: string;
-  neutralizeInternalLinks: boolean;
-}) {
-  const html = renderChatMarkdown(text, { neutralizeInternalLinks });
-  if (html) {
-    return (
-      <div
-        className={classes.markdown}
-        // Sanitized by renderChatMarkdown (DOMPurify) before insertion.
-        dangerouslySetInnerHTML={{ __html: html }}
-      />
-    );
-  }
-  // Fallback when markdown could not render synchronously: raw text.
-  return (
-    <Text className={classes.markdown} style={{ whiteSpace: "pre-wrap" }}>
-      {text}
-    </Text>
-  );
-});
-
 /**
  * Render a single UIMessage by iterating its `parts`:
  *  - `text` parts -> sanitized markdown.
@@ -76,13 +41,12 @@ const MarkdownPart = memo(function MarkdownPart({
  * Other part kinds (reasoning, sources, files, step-start) are ignored for v1.
  * User messages render their text as a right-aligned plain bubble.
  *
- * This component is memoized (see `arePropsEqual` at the bottom) on a cheap
- * per-message content signature: the streaming TAIL message's signature changes
- * on each delta so it still re-renders and streams in, while finalized rows are
- * skipped. Each text part's markdown is itself memoized via `MarkdownPart`, so a
- * long turn no longer re-parses the whole transcript on every token.
+ * This component is intentionally NOT memoized: `useChat` replaces the streaming
+ * assistant message with a freshly cloned object on every streamed delta, so the
+ * `message` prop identity (and its `parts`) changes each tick. Re-rendering the
+ * text parts on each delta is what makes the answer stream in progressively.
  */
-function MessageItem({
+export default function MessageItem({
   message,
   showCitations = true,
   neutralizeInternalLinks = false,
@@ -145,12 +109,24 @@ function MessageItem({
           // starts with an empty text part before the first token arrives); the
           // typing indicator covers that gap until real content streams in.
           if (!part.text.trim()) return null;
+          const html = renderChatMarkdown(part.text, {
+            neutralizeInternalLinks,
+          });
+          if (html) {
+            return (
+              <div
+                key={index}
+                className={classes.markdown}
+                // Sanitized by renderChatMarkdown (DOMPurify) before insertion.
+                dangerouslySetInnerHTML={{ __html: html }}
+              />
+            );
+          }
+          // Fallback when markdown could not render synchronously: raw text.
           return (
-            <MarkdownPart
-              key={index}
-              text={part.text}
-              neutralizeInternalLinks={neutralizeInternalLinks}
-            />
+            <Text key={index} className={classes.markdown} style={{ whiteSpace: "pre-wrap" }}>
+              {part.text}
+            </Text>
           );
         }
 
@@ -201,26 +177,3 @@ function MessageItem({
     </Box>
   );
 }
-
-/** Skip re-rendering a message whose visible content is unchanged. The streaming
- *  TAIL message gets a fresh object whose signature changes each delta, so it
- *  still re-renders and streams in; every FINALIZED message is skipped, turning a
- *  per-token whole-transcript re-render into a tail-only one. */
-export function arePropsEqual(
-  prev: MessageItemProps,
-  next: MessageItemProps,
-): boolean {
-  if (
-    prev.showCitations !== next.showCitations ||
-    prev.neutralizeInternalLinks !== next.neutralizeInternalLinks ||
-    prev.assistantName !== next.assistantName
-  ) {
-    return false;
-  }
-  // Fast path: identical message object (finalized rows keep their identity
-  // across deltas) — skip without building signatures.
-  if (prev.message === next.message) return true;
-  return messageSignature(prev.message) === messageSignature(next.message);
-}
-
-export default memo(MessageItem, arePropsEqual);

apps/client/src/features/ai-chat/components/reasoning-block.tsx

@@ -1,4 +1,4 @@
-import { memo, useMemo, useState } from "react";
+import { useState } from "react";
 import { Box, Collapse, Group, Text, UnstyledButton } from "@mantine/core";
 import { IconChevronDown } from "@tabler/icons-react";
 import { useTranslation } from "react-i18next";
@@ -27,23 +27,19 @@ interface ReasoningBlockProps {
  * Providers that don't stream reasoning TEXT still render this block from the
  * authoritative count alone (header only, empty body) so the cost is visible.
  */
-function ReasoningBlock({ text, tokens }: ReasoningBlockProps) {
+export default function ReasoningBlock({ text, tokens }: ReasoningBlockProps) {
   const { t } = useTranslation();
   const [open, setOpen] = useState(false);
 
   // Authoritative count wins; otherwise estimate live from the streamed text.
   const count = tokens && tokens > 0 ? tokens : estimateTokens(text);
   const trimmed = text.trim();
-  // Memoize the markdown render so toggling `open` (or a parent re-render caused
-  // by an unrelated streamed delta) does not re-parse the reasoning text; it
-  // recomputes only when the reasoning text itself changes (while it streams in).
-  // collapseBlankLines collapses the blank-line gaps the model emits between every
-  // list item / paragraph so the reasoning renders compactly (tight lists, joined
-  // paragraphs) — ONLY here, not in the normal answer.
-  const html = useMemo(
-    () => (trimmed ? renderChatMarkdown(collapseBlankLines(trimmed), {}) : ""),
-    [trimmed],
-  );
+  // Collapse the blank-line gaps the model emits between every list item /
+  // paragraph so the reasoning renders compactly (tight lists, joined
+  // paragraphs) — see collapseBlankLines. ONLY here, not in the normal answer.
+  const html = trimmed
+    ? renderChatMarkdown(collapseBlankLines(trimmed), {})
+    : "";
 
   return (
     <Box className={classes.reasoningBlock} mb={6}>
@@ -91,8 +87,3 @@ function ReasoningBlock({ text, tokens }: ReasoningBlockProps) {
     </Box>
   );
 }
-
-// Memoized: re-renders only when `text`/`tokens` change (primitive props, default
-// shallow compare), so a parent re-render during streaming of OTHER content does
-// not re-run the markdown parse for an already-finalized reasoning block.
-export default memo(ReasoningBlock);

apps/client/src/features/ai-chat/types/ai-chat.types.ts

@@ -113,9 +113,14 @@ export interface IAiChatMessageRow {
     };
     // Current context size for the turn = final-step (input+output) tokens, i.e.
     // how much the conversation occupies in the model's context window after this
-    // turn. Distinct from `usage` (legacy cumulative totalUsage). Shown in the
-    // floating window's header badge.
+    // turn. Distinct from `usage` (legacy cumulative totalUsage). Shown as the
+    // numerator of the floating window's "current / max" header badge.
     contextTokens?: number;
+    // The model's context-window size (tokens), admin-configured in AI settings
+    // and stamped onto the turn server-side. The denominator of the header badge.
+    // Absent/0 (older rows, or no limit configured) → the badge hides the
+    // denominator and shows only the current context size (`contextTokens`).
+    maxContextTokens?: number;
     // Set on an assistant row whose turn ended in a provider/stream error; the
     // raw provider error text (e.g. "402: ...") for inline display in the thread.
     error?: string;

apps/client/src/features/ai-chat/utils/count-stream-tokens.test.ts

@@ -1,17 +1,5 @@
 import { describe, expect, it } from "vitest";
-import type { UIMessage } from "@ai-sdk/react";
-import {
-  estimateTokens,
-  liveTurnTokens,
-} from "@/features/ai-chat/utils/count-stream-tokens.ts";
-
-const msg = (parts: unknown[], metadata?: unknown): UIMessage =>
-  ({
-    id: Math.random().toString(),
-    role: "assistant",
-    parts,
-    metadata,
-  }) as UIMessage;
+import { estimateTokens } from "@/features/ai-chat/utils/count-stream-tokens.ts";
 
 describe("estimateTokens", () => {
   it("returns 0 for the empty string", () => {
@@ -25,147 +13,3 @@ describe("estimateTokens", () => {
     expect(estimateTokens("12345678")).toBe(2);
   });
 });
-
-describe("liveTurnTokens — estimate path", () => {
-  it("is all zeros for an undefined message", () => {
-    expect(liveTurnTokens(undefined)).toEqual({
-      reasoning: 0,
-      output: 0,
-      authoritative: false,
-    });
-  });
-
-  it("is all zeros for a parts-less message", () => {
-    expect(liveTurnTokens({ id: "x", role: "assistant" } as UIMessage)).toEqual({
-      reasoning: 0,
-      output: 0,
-      authoritative: false,
-    });
-  });
-
-  it("estimates output from text parts", () => {
-    // 8 chars -> 2 tokens.
-    const r = liveTurnTokens(msg([{ type: "text", text: "12345678" }]));
-    expect(r).toEqual({ reasoning: 0, output: 2, authoritative: false });
-  });
-
-  it("estimates reasoning from reasoning parts (kept separate from output)", () => {
-    const r = liveTurnTokens(
-      msg([
-        { type: "reasoning", text: "12345678" },
-        { type: "text", text: "abcd" },
-      ]),
-    );
-    expect(r).toEqual({ reasoning: 2, output: 1, authoritative: false });
-  });
-
-  it("accumulates across multiple text + reasoning parts (multi-step)", () => {
-    const r = liveTurnTokens(
-      msg([
-        { type: "reasoning", text: "abcd" }, // 1
-        { type: "text", text: "abcd" }, // 1
-        { type: "tool-getPage", state: "output-available" }, // ignored
-        { type: "reasoning", text: "abcd" }, // 1
-        { type: "text", text: "abcdefgh" }, // 2
-      ]),
-    );
-    expect(r).toEqual({ reasoning: 2, output: 3, authoritative: false });
-  });
-
-  it("ignores non text/reasoning parts (tools, step-start)", () => {
-    const r = liveTurnTokens(
-      msg([
-        { type: "step-start" },
-        { type: "tool-getPage", state: "input-available" },
-      ]),
-    );
-    expect(r).toEqual({ reasoning: 0, output: 0, authoritative: false });
-  });
-});
-
-describe("liveTurnTokens — authoritative path", () => {
-  it("returns authoritative usage verbatim, splitting reasoning out of output", () => {
-    // outputTokens INCLUDES reasoning in the AI SDK shape -> answer = 100 - 30.
-    const r = liveTurnTokens(
-      msg([{ type: "text", text: "estimate would be tiny" }], {
-        usage: { inputTokens: 500, outputTokens: 100, reasoningTokens: 30 },
-      }),
-    );
-    expect(r).toEqual({ reasoning: 30, output: 70, authoritative: true });
-  });
-
-  it("treats missing reasoningTokens as 0 and keeps full output", () => {
-    const r = liveTurnTokens(
-      msg([{ type: "text", text: "x" }], {
-        usage: { inputTokens: 10, outputTokens: 42 },
-      }),
-    );
-    expect(r).toEqual({ reasoning: 0, output: 42, authoritative: true });
-  });
-
-  it("never returns a negative output when reasoning exceeds reported output", () => {
-    const r = liveTurnTokens(
-      msg([], { usage: { outputTokens: 10, reasoningTokens: 40 } }),
-    );
-    expect(r).toEqual({ reasoning: 40, output: 0, authoritative: true });
-  });
-
-  it("falls back to the estimate when metadata has no usage object", () => {
-    const r = liveTurnTokens(
-      msg([{ type: "text", text: "abcd" }], { chatId: "c1" }),
-    );
-    expect(r).toEqual({ reasoning: 0, output: 1, authoritative: false });
-  });
-});
-
-describe("liveTurnTokens — combined authoritative + estimate (#163)", () => {
-  it("ticks the in-flight step above the completed-steps authoritative base", () => {
-    // The authoritative usage is the sum over COMPLETED steps (step 1). The
-    // CURRENT step is streaming and its text is NOT in `usage` yet, but it IS in
-    // the parts -> the running estimate must push the live figure above the base
-    // so the badge keeps growing between step boundaries.
-    const longText = "x".repeat(800); // 800 chars -> 200 est output tokens
-    const r = liveTurnTokens(
-      msg([{ type: "text", text: longText }], {
-        usage: { inputTokens: 500, outputTokens: 40 }, // step-1 base: 40 output
-      }),
-    );
-    // max(authOutput=40, estOutput=200) = 200 -> the counter ticks, not frozen.
-    expect(r.output).toBe(200);
-    expect(r.authoritative).toBe(true);
-  });
-
-  it("ticks reasoning of the in-flight step above the authoritative reasoning base", () => {
-    const longReasoning = "r".repeat(400); // 400 chars -> 100 est reasoning
-    const r = liveTurnTokens(
-      msg([{ type: "reasoning", text: longReasoning }], {
-        usage: { inputTokens: 100, outputTokens: 20, reasoningTokens: 20 },
-      }),
-    );
-    // reasoning: max(20, 100) = 100 ; output: max(max(0,20-20)=0, 0) = 0.
-    expect(r.reasoning).toBe(100);
-    expect(r.output).toBe(0);
-    expect(r.authoritative).toBe(true);
-  });
-
-  it("snaps to the authoritative figure once it exceeds the rough estimate", () => {
-    // Short on-screen text (estimate tiny) but a large authoritative output:
-    // the exact figure wins at the boundary (the counter never under-reports).
-    const r = liveTurnTokens(
-      msg([{ type: "text", text: "abcd" }], {
-        usage: { inputTokens: 10, outputTokens: 5000 },
-      }),
-    );
-    expect(r.output).toBe(5000);
-  });
-
-  it("is monotonic: max never drops below the authoritative base when the estimate is smaller", () => {
-    // Mirrors the legacy 'verbatim' tests: estimate < authoritative -> unchanged.
-    const r = liveTurnTokens(
-      msg([{ type: "text", text: "tiny" }], {
-        usage: { inputTokens: 500, outputTokens: 100, reasoningTokens: 30 },
-      }),
-    );
-    expect(r).toEqual({ reasoning: 30, output: 70, authoritative: true });
-  });
-});

apps/client/src/features/ai-chat/utils/count-stream-tokens.ts

@@ -1,18 +1,16 @@
-import type { UIMessage } from "@ai-sdk/react";
-
 /**
- * Live token counting for a streaming AI-chat turn — split into REASONING
- * (thinking) and OUTPUT (answer) tokens, mirroring how Claude Code shows
- * `Thinking… · 60 tokens` next to its thinking indicator.
+ * Live token ESTIMATION for a streaming AI-chat turn.
  *
  * No provider streams exact per-token usage mid-stream, so the live number is a
- * CLIENT ESTIMATE (chars/≈4 heuristic) that is reconciled to AUTHORITATIVE usage
- * once the server attaches it on a step/turn boundary (see the server's
- * `chatStreamMetadata` + the client's read of `message.metadata.usage`). When
- * authoritative usage is present we return it verbatim (the number "jumps to
- * exact"); otherwise we return the running estimate. Pure + unit-testable: it
- * never runs a real BPE tokenizer (that would be O(n²) on the hot path, bloat the
+ * CLIENT ESTIMATE (chars/≈4 heuristic). It powers the chat body's
+ * `Thinking… · N tokens` indicator (see `ReasoningBlock`), which reconciles to
+ * the authoritative server usage once it lands. Pure + unit-testable: it never
+ * runs a real BPE tokenizer (that would be O(n²) on the hot path, bloat the
  * bundle, and be wrong for Gemini/Ollama anyway).
+ *
+ * The former header-badge `liveTurnTokens()` split was removed with #189 (the
+ * header badge now shows the stable "current / max" context size, not a live
+ * per-turn counter); the live feedback remains in `ReasoningBlock`.
  */
 
 /**
@@ -24,90 +22,3 @@ export function estimateTokens(text: string): number {
   if (!text) return 0;
   return Math.ceil(text.length / 4);
 }
-
-/** Authoritative per-step/turn usage the server attaches to message metadata. */
-export interface AuthoritativeUsage {
-  inputTokens?: number;
-  outputTokens?: number;
-  totalTokens?: number;
-  reasoningTokens?: number;
-}
-
-/** Live token split for a turn's tail (streaming) assistant message. */
-export interface LiveTurnTokens {
-  /** Thinking/reasoning tokens (estimate, or authoritative when available). */
-  reasoning: number;
-  /** Answer/output tokens (estimate, or authoritative when available). */
-  output: number;
-  /** True when the numbers come from authoritative server usage, not estimate. */
-  authoritative: boolean;
-}
-
-/** Read the authoritative usage off a UIMessage's metadata, if the server set it. */
-function metadataUsage(message: UIMessage): AuthoritativeUsage | undefined {
-  const meta = message?.metadata as
-    | { usage?: AuthoritativeUsage }
-    | undefined;
-  const usage = meta?.usage;
-  if (!usage || typeof usage !== "object") return undefined;
-  return usage;
-}
-
-/**
- * Token split for the given (streaming) assistant message.
- *
- * COMBINES the authoritative server usage with the running text estimate so the
- * counter ticks in real time AND lands exact. The server only attaches
- * `metadata.usage` at a step/turn boundary (`finish-step`/`finish`) and it is
- * CUMULATIVE over COMPLETED steps — it does NOT yet include the in-flight step.
- * So a multi-step turn that returned the authoritative figure verbatim would
- * FREEZE between boundaries and jump in steps (issue #163).
- *
- * Instead we always compute the running ESTIMATE (chars/≈4 over the message's
- * `reasoning`/`text` parts, which grows on every streamed delta) and take the
- * per-component MAX of the authoritative base and the estimate:
- *   - between boundaries the estimate of the in-flight step ticks the number up;
- *   - at a boundary the authoritative figure snaps it to exact;
- *   - because the server's usage is cumulative and we only ever take the max, the
- *     number is MONOTONIC — it never drops.
- *
- * Providers that don't stream reasoning text still surface a reasoning count once
- * the authoritative usage arrives (`max(reasoningTokens, 0)`); on the pure
- * estimate path (no usage yet) such a turn shows `reasoning: 0` until then.
- */
-export function liveTurnTokens(message: UIMessage | undefined): LiveTurnTokens {
-  if (!message) return { reasoning: 0, output: 0, authoritative: false };
-
-  // Running ESTIMATE over every reasoning/text part — grows on each delta. This
-  // includes the IN-FLIGHT step, which the authoritative usage does not cover yet.
-  let estReasoning = 0;
-  let estOutput = 0;
-  for (const part of message.parts ?? []) {
-    if (part.type === "reasoning") {
-      estReasoning += estimateTokens((part as { text?: string }).text ?? "");
-    } else if (part.type === "text") {
-      estOutput += estimateTokens((part as { text?: string }).text ?? "");
-    }
-  }
-
-  const usage = metadataUsage(message);
-  if (!usage) {
-    // No authoritative usage streamed yet: the estimate IS the live figure.
-    return { reasoning: estReasoning, output: estOutput, authoritative: false };
-  }
-
-  // Authoritative sum over COMPLETED steps. `outputTokens` already INCLUDES
-  // reasoning in the AI SDK usage shape, so subtract it out for the "answer"
-  // figure (never go negative if a provider reports them inconsistently).
-  const authReasoning = usage.reasoningTokens ?? 0;
-  const authOutput = Math.max(0, (usage.outputTokens ?? 0) - authReasoning);
-
-  // Per-component max: the in-flight step's estimate ticks above the completed-
-  // steps base between boundaries, and the authoritative figure wins once it
-  // exceeds the (rough) estimate at the next boundary. Monotonic by construction.
-  return {
-    reasoning: Math.max(authReasoning, estReasoning),
-    output: Math.max(authOutput, estOutput),
-    authoritative: true,
-  };
-}

apps/client/src/features/ai-chat/utils/message-signature.test.ts

@@ -1,241 +0,0 @@
-import { describe, expect, it } from "vitest";
-import type { UIMessage } from "@ai-sdk/react";
-import { messageSignature } from "@/features/ai-chat/utils/message-signature.ts";
-
-/**
- * Pure-helper tests for `messageSignature`, the cheap per-message content
- * signature that drives MessageItem's memo (a streaming row's signature must
- * change on every delta so it re-renders, while a finalized row's stays stable
- * so it is skipped). Each test exercises ONE change signal and asserts it flips
- * the signature; a content-identical clone must keep an EQUAL signature.
- *
- * The signature embeds `message.id` and `message.role`, so the `msg` factory
- * uses a FIXED id/role here (not `Math.random()`): otherwise two messages with
- * identical content would get different signatures and the negative case would
- * be impossible to express.
- */
-const msg = (
-  parts: UIMessage["parts"],
-  metadata?: unknown,
-): UIMessage =>
-  ({
-    id: "m1",
-    role: "assistant",
-    parts,
-    metadata,
-  }) as UIMessage;
-
-describe("messageSignature", () => {
-  it("changes when a text part grows", () => {
-    const before = msg([{ type: "text", text: "alpha" }]);
-    const after = msg([{ type: "text", text: "alpha beta" }]);
-    expect(messageSignature(before)).not.toBe(messageSignature(after));
-  });
-
-  it("changes when a new part is appended", () => {
-    const before = msg([{ type: "text", text: "alpha" }]);
-    const after = msg([
-      { type: "text", text: "alpha" },
-      { type: "text", text: "beta" },
-    ]);
-    expect(messageSignature(before)).not.toBe(messageSignature(after));
-  });
-
-  it("changes when a part's state flips", () => {
-    const before = msg([
-      { type: "tool-getPage", state: "input-streaming" } as never,
-    ]);
-    const after = msg([
-      { type: "tool-getPage", state: "output-available" } as never,
-    ]);
-    expect(messageSignature(before)).not.toBe(messageSignature(after));
-  });
-
-  it("changes when a tool part gains an output", () => {
-    const before = msg([
-      { type: "tool-getPage", state: "output-available" } as never,
-    ]);
-    const after = msg([
-      {
-        type: "tool-getPage",
-        state: "output-available",
-        output: { ok: true },
-      } as never,
-    ]);
-    expect(messageSignature(before)).not.toBe(messageSignature(after));
-  });
-
-  it("changes when a part gains an errorText", () => {
-    const before = msg([
-      { type: "tool-getPage", state: "output-error" } as never,
-    ]);
-    const after = msg([
-      {
-        type: "tool-getPage",
-        state: "output-error",
-        errorText: "boom",
-      } as never,
-    ]);
-    expect(messageSignature(before)).not.toBe(messageSignature(after));
-  });
-
-  it("changes when usage.reasoningTokens arrives on finish-step (text/state already frozen)", () => {
-    // The specifically-commented edge case: the authoritative turn total lands on
-    // the final finish-step AFTER the reasoning text length and state are frozen.
-    // Only the token count appears between these two snapshots, so the signature
-    // MUST still flip — otherwise the "Thinking · N tokens" header would never
-    // snap from the live estimate to the exact figure.
-    const before = msg([
-      { type: "reasoning", text: "thinking", state: "done" } as never,
-    ]);
-    const after = msg(
-      [{ type: "reasoning", text: "thinking", state: "done" } as never],
-      { usage: { reasoningTokens: 42 } },
-    );
-    expect(messageSignature(before)).not.toBe(messageSignature(after));
-  });
-
-  it("changes when metadata.error appears", () => {
-    const before = msg([{ type: "text", text: "answer" }]);
-    const after = msg([{ type: "text", text: "answer" }], { error: "boom" });
-    expect(messageSignature(before)).not.toBe(messageSignature(after));
-  });
-
-  it("changes when metadata.finishReason changes (e.g. to 'aborted')", () => {
-    const before = msg([{ type: "text", text: "answer" }], {
-      finishReason: "stop",
-    });
-    const after = msg([{ type: "text", text: "answer" }], {
-      finishReason: "aborted",
-    });
-    expect(messageSignature(before)).not.toBe(messageSignature(after));
-  });
-
-  it("is UNCHANGED for a content-identical clone (different object, same values)", () => {
-    // A finalized row that is re-created as a fresh object (different parts array
-    // by reference, same parts by value) must keep an EQUAL signature, so the
-    // memo skips re-rendering it.
-    const a = msg([
-      { type: "text", text: "alpha" },
-      { type: "tool-getPage", state: "output-available", output: { ok: true } } as never,
-    ]);
-    const b = msg([
-      { type: "text", text: "alpha" },
-      { type: "tool-getPage", state: "output-available", output: { ok: true } } as never,
-    ]);
-    expect(a).not.toBe(b);
-    expect(messageSignature(a)).toBe(messageSignature(b));
-  });
-});
-
-/**
- * Per-part-kind coupling guard for the load-bearing invariant documented at the
- * top of message-signature.ts: the signature MUST sample every VISIBLE field the
- * MessageItem render body draws, or the memo freezes a stale row. This is an
- * executable lock for the part kinds rendered TODAY — read alongside
- * `MessageItem` (message-item.tsx) and the `assistantMessageHasVisibleContent`
- * helper (message-content.ts), which "mirrors MessageItem's render decisions
- * EXACTLY". For each kind, mutating a field the render body DRAWS must flip the
- * signature. If a new visible field is rendered without being added here AND to
- * the signature, the corresponding assertion below should fail — that is the
- * guard. (This intentionally stops short of the render-descriptor refactor:
- * adding a part kind or a visible field still requires a human to extend both
- * the signature and this block.)
- */
-describe("messageSignature ↔ render coupling (per visible part kind)", () => {
-  describe("text part — render draws part.text (MarkdownPart text={part.text})", () => {
-    it("flips when the visible text changes", () => {
-      // Streaming is append-only, so the visible text only grows; the signature
-      // samples its length, so the growth is the change signal.
-      const before = msg([{ type: "text", text: "answer" }]);
-      const after = msg([{ type: "text", text: "answer extended" }]);
-      expect(messageSignature(before)).not.toBe(messageSignature(after));
-    });
-  });
-
-  describe("reasoning part — render draws text + tokens (ReasoningBlock)", () => {
-    it("flips when the visible reasoning text changes", () => {
-      const before = msg([
-        { type: "reasoning", text: "think", state: "streaming" } as never,
-      ]);
-      const after = msg([
-        { type: "reasoning", text: "think harder", state: "streaming" } as never,
-      ]);
-      expect(messageSignature(before)).not.toBe(messageSignature(after));
-    });
-
-    it("flips when the visible token count (metadata.usage.reasoningTokens) lands", () => {
-      // The header's "Thinking · N tokens" reads reasoningTokensForPart, fed by
-      // metadata.usage.reasoningTokens — a VISIBLE field that arrives on the final
-      // finish-step after text length and state are frozen.
-      const before = msg([
-        { type: "reasoning", text: "think", state: "done" } as never,
-      ]);
-      const after = msg(
-        [{ type: "reasoning", text: "think", state: "done" } as never],
-        { usage: { reasoningTokens: 99 } },
-      );
-      expect(messageSignature(before)).not.toBe(messageSignature(after));
-    });
-  });
-
-  describe("tool-* part — render draws state/errorText/citations (ToolCallCard)", () => {
-    it("flips when the run state changes (running ↔ done icon + label)", () => {
-      // toolRunState(part.state) selects the spinner/check/error icon.
-      const before = msg([
-        { type: "tool-getPage", state: "input-available" } as never,
-      ]);
-      const after = msg([
-        { type: "tool-getPage", state: "output-available" } as never,
-      ]);
-      expect(messageSignature(before)).not.toBe(messageSignature(after));
-    });
-
-    it("flips when output arrives (drives the rendered citation links)", () => {
-      // toolCitations reads part.output to render the "/p/{id}" anchors.
-      const before = msg([
-        { type: "tool-getPage", state: "output-available" } as never,
-      ]);
-      const after = msg([
-        {
-          type: "tool-getPage",
-          state: "output-available",
-          output: { id: "page-1", title: "Doc" },
-        } as never,
-      ]);
-      expect(messageSignature(before)).not.toBe(messageSignature(after));
-    });
-
-    it("flips when errorText appears (the visible red error detail line)", () => {
-      const before = msg([
-        { type: "tool-getPage", state: "output-error" } as never,
-      ]);
-      const after = msg([
-        {
-          type: "tool-getPage",
-          state: "output-error",
-          errorText: "permission denied",
-        } as never,
-      ]);
-      expect(messageSignature(before)).not.toBe(messageSignature(after));
-    });
-  });
-
-  describe("metadata banners — render draws error / aborted notices", () => {
-    it("flips when metadata.error appears (ChatErrorAlert banner)", () => {
-      const before = msg([{ type: "text", text: "answer" }]);
-      const after = msg([{ type: "text", text: "answer" }], { error: "boom" });
-      expect(messageSignature(before)).not.toBe(messageSignature(after));
-    });
-
-    it("flips when metadata.finishReason becomes 'aborted' (ChatStoppedNotice)", () => {
-      const before = msg([{ type: "text", text: "answer" }], {
-        finishReason: "stop",
-      });
-      const after = msg([{ type: "text", text: "answer" }], {
-        finishReason: "aborted",
-      });
-      expect(messageSignature(before)).not.toBe(messageSignature(after));
-    });
-  });
-});

apps/client/src/features/ai-chat/utils/message-signature.ts

@@ -1,44 +0,0 @@
-import type { UIMessage } from "@ai-sdk/react";
-
-/** Cheap content signature for one message: changes iff something VISIBLE in the
- *  row changed. Streaming is APPEND-ONLY (text parts only grow, parts are only
- *  appended, a tool/text part flips state once), so a per-part [type, text
- *  length, state, error/output presence] tuple + the persisted metadata
- *  (error/finishReason) is a sufficient change signal without comparing full
- *  strings on every delta. WARNING — load-bearing for the MessageItem memo:
- *  if a future part kind's VISIBLE content can change WITHOUT changing [type,
- *  text length, state, error/output presence] (e.g. a tool that streams
- *  `preliminary` output, or a client-side regenerate that edits a finalized
- *  row in place), extend this signature or the memo will freeze a stale row. */
-export function messageSignature(message: UIMessage): string {
-  const parts = message.parts
-    .map((p) => {
-      const any = p as {
-        type: string;
-        text?: string;
-        state?: string;
-        errorText?: string;
-        output?: unknown;
-      };
-      return [
-        any.type,
-        any.text?.length ?? 0,
-        any.state ?? "",
-        any.errorText ? 1 : 0,
-        any.output !== undefined ? 1 : 0,
-      ].join(":");
-    })
-    .join("|");
-  const meta = message.metadata as
-    | { error?: string; finishReason?: string; usage?: { reasoningTokens?: number } }
-    | undefined;
-  // `usage.reasoningTokens` is neither append-only nor part-bound: the authoritative
-  // turn total arrives on the final `finish-step` AFTER the reasoning text length and
-  // state are already frozen. Without it in the signature the row's signature would be
-  // unchanged at that point and the re-render skipped, so the "Thinking · N tokens"
-  // header (reasoningTokensForPart) would keep the live estimate instead of snapping
-  // to the exact figure.
-  return `${message.id}#${message.role}#${parts}#${meta?.error ?? ""}#${
-    meta?.finishReason ?? ""
-  }#${meta?.usage?.reasoningTokens ?? ""}`;
-}

apps/client/src/features/workspace/components/settings/components/ai-provider-settings.tsx

@@ -7,6 +7,7 @@ import {
   Button,
   Group,
   Modal,
+  NumberInput,
   Paper,
   PasswordInput,
   Select,
@@ -85,6 +86,9 @@ const formSchema = z.object({
   chatModel: z.string(),
   // Chat provider implementation (reasoning surfacing). Default openai-compatible.
   chatApiStyle: z.enum(["openai-compatible", "openai"]),
+  // Model context-window size (tokens) shown as the chat header badge's "max".
+  // Empty string = no limit (NumberInput emits "" when cleared).
+  chatContextWindow: z.union([z.number(), z.literal("")]),
   // Cheap model id for the anonymous public-share assistant; empty = use chatModel.
   publicShareChatModel: z.string(),
   // Agent-role id whose persona the public-share assistant adopts; empty =
@@ -312,6 +316,7 @@ export default function AiProviderSettings() {
     initialValues: {
       chatModel: "",
       chatApiStyle: "openai-compatible" as ChatApiStyle,
+      chatContextWindow: "" as number | "",
       publicShareChatModel: "",
       publicShareAssistantRoleId: "",
       embeddingModel: "",
@@ -335,6 +340,10 @@ export default function AiProviderSettings() {
     form.setValues({
       chatModel: settings.chatModel ?? "",
       chatApiStyle: settings.chatApiStyle ?? "openai-compatible",
+      // 0/unset = no limit → show an empty field (not a literal "0").
+      chatContextWindow: settings.chatContextWindow
+        ? settings.chatContextWindow
+        : "",
       publicShareChatModel: settings.publicShareChatModel ?? "",
       publicShareAssistantRoleId: settings.publicShareAssistantRoleId ?? "",
       embeddingModel: settings.embeddingModel ?? "",
@@ -365,6 +374,11 @@ export default function AiProviderSettings() {
       driver: "openai",
       chatModel: values.chatModel,
       chatApiStyle: values.chatApiStyle,
+      // Empty → 0, which clears the limit server-side (badge shows current only).
+      chatContextWindow:
+        typeof values.chatContextWindow === "number"
+          ? values.chatContextWindow
+          : 0,
       // Cheap model id for the anonymous public-share assistant; empty falls
       // back to chatModel server-side.
       publicShareChatModel: values.publicShareChatModel,
@@ -785,6 +799,22 @@ export default function AiProviderSettings() {
           {...form.getInputProps("chatApiStyle")}
         />
 
+        <NumberInput
+          mt="sm"
+          label={t("Context window (tokens)")}
+          description={t(
+            "Shows used / total in the chat header badge; empty hides the total.",
+          )}
+          placeholder={t("e.g. 200000")}
+          min={0}
+          step={1000}
+          allowDecimal={false}
+          allowNegative={false}
+          thousandSeparator=" "
+          disabled={isLoading}
+          {...form.getInputProps("chatContextWindow")}
+        />
+
         {/* Anonymous public-share assistant: a single master toggle + an
             optional cheaper model id. Reuses this card's driver/URL/key. */}
         <Group justify="space-between" align="center" wrap="nowrap" mt="md">

apps/client/src/features/workspace/services/ai-settings-service.ts

@@ -23,6 +23,9 @@ export interface IAiSettings {
   driver?: AiDriver;
   chatModel?: string;
   chatApiStyle?: ChatApiStyle;
+  // Chat model context-window size (tokens); shown as the "max" in the chat
+  // header context badge. 0/unset = no limit (badge shows the current size only).
+  chatContextWindow?: number;
   // Cheap model id for the anonymous public-share assistant; empty = chatModel.
   publicShareChatModel?: string;
   // Agent-role id whose persona the public-share assistant adopts; empty =
@@ -57,6 +60,8 @@ export interface IAiSettingsUpdate {
   driver?: AiDriver;
   chatModel?: string;
   chatApiStyle?: ChatApiStyle;
+  // Chat model context-window size (tokens); 0 clears the limit.
+  chatContextWindow?: number;
   publicShareChatModel?: string;
   // Agent-role id whose persona the public-share assistant adopts; empty =
   // built-in locked persona.

apps/server/src/core/ai-chat/ai-chat.service.spec.ts

@@ -292,6 +292,26 @@ describe('flushAssistant', () => {
     expect(f.metadata.contextTokens).toBe(15);
   });
 
+  it('completed: writes maxContextTokens when the model limit is > 0', () => {
+    const f = flushAssistant([toolStep], '', 'completed', {
+      contextTokens: 15,
+      maxContextTokens: 200_000,
+    });
+    expect(f.metadata.maxContextTokens).toBe(200_000);
+  });
+
+  it('omits maxContextTokens when the limit is unset or 0', () => {
+    const unset = flushAssistant([toolStep], '', 'completed', {
+      contextTokens: 15,
+    });
+    expect('maxContextTokens' in unset.metadata).toBe(false);
+    const zero = flushAssistant([toolStep], '', 'completed', {
+      contextTokens: 15,
+      maxContextTokens: 0,
+    });
+    expect('maxContextTokens' in zero.metadata).toBe(false);
+  });
+
   it('error: records the error and a derived finishReason', () => {
     const f = flushAssistant([], 'partial answer', 'error', { error: 'boom' });
     expect(f.status).toBe('error');

apps/server/src/core/ai-chat/ai-chat.service.ts

@@ -616,6 +616,9 @@ export class AiChatService implements OnModuleInit {
               contextTokens:
                 (usage?.inputTokens ?? 0) + (usage?.outputTokens ?? 0) ||
                 undefined,
+              // Admin-configured context-window size for this model (badge max).
+              // Resolved once per turn above; written to metadata only when > 0.
+              maxContextTokens: resolved?.chatContextWindow,
             }),
           );
           // Lifecycle: release the external MCP clients leased for this turn.
@@ -1223,6 +1226,10 @@ export function flushAssistant(
     finishReason?: string;
     usage?: ChatStreamUsage | StreamUsage | undefined;
     contextTokens?: number;
+    // Admin-configured context-window size (tokens) for this turn's model; the
+    // denominator of the client's "current / max" header badge. Written only
+    // when > 0 (0/unset = no limit known → the badge shows current only).
+    maxContextTokens?: number;
     error?: string;
   },
 ): AssistantFlush {
@@ -1253,6 +1260,9 @@ export function flushAssistant(
       normalizeStreamUsage(extra.usage as StreamUsage) ?? extra.usage;
   }
   if (extra?.contextTokens) metadata.contextTokens = extra.contextTokens;
+  if (extra?.maxContextTokens && extra.maxContextTokens > 0) {
+    metadata.maxContextTokens = extra.maxContextTokens;
+  }
   if (extra?.error) metadata.error = extra.error;
 
   return {

apps/server/src/database/repos/workspace/workspace.repo.ts

@@ -21,6 +21,7 @@ export const AI_PROVIDER_SETTINGS_ALLOWED: readonly string[] = [
   'driver',
   'chatModel',
   'chatApiStyle',
+  'chatContextWindow',
   'embeddingModel',
   'baseUrl',
   'embeddingBaseUrl',
@@ -255,11 +256,17 @@ export class WorkspaceRepo {
   ): Promise<Workspace> {
     const db = dbOrTx(this.db, trx);
     // Assemble the provider object IN SQL. Keys are fixed provider field names
-    // (sql.lit -> inlined literals, no injection); values are bound params cast
-    // to ::text — postgres.js sends bound params untyped, and jsonb_build_object's
-    // value args are polymorphic ("any"), so without the explicit ::text cast
-    // Postgres throws "could not determine data type of parameter $1". The result
-    // is a real jsonb object, never a double-encoded string. The CASE self-heals
+    // (sql.lit -> inlined literals, no injection); values are bound params with
+    // an explicit cast — postgres.js sends bound params untyped, and
+    // jsonb_build_object's value args are polymorphic ("any"), so without the
+    // cast Postgres throws "could not determine data type of parameter $1". The
+    // cast is branched by the JS runtime type so the value lands in jsonb with
+    // the matching JSON type: a number stays a JSON number (e.g.
+    // chatContextWindow → `{"chatContextWindow":200000}`, jsonb_typeof 'number'),
+    // a boolean a JSON boolean, everything else a JSON string. A plain `::text`
+    // for all would store a numeric field as the JSON STRING `"200000"`, which
+    // the client's `typeof === "number"` guards reject. The result is a real
+    // jsonb object, never a double-encoded string. The CASE self-heals
     // workspaces whose settings.ai.provider was previously corrupted into an
     // array/string.
     const entries = Object.entries(provider).filter(
@@ -267,7 +274,14 @@ export class WorkspaceRepo {
     );
     const patch = entries.length
       ? sql`jsonb_build_object(${sql.join(
-          entries.flatMap(([k, v]) => [sql.lit(k), sql`${v}::text`]),
+          entries.flatMap(([k, v]) => [
+            sql.lit(k),
+            typeof v === 'number'
+              ? sql`${v}::numeric`
+              : typeof v === 'boolean'
+                ? sql`${v}::boolean`
+                : sql`${v}::text`,
+          ]),
         )})`
       : sql`'{}'::jsonb`;
     return db

apps/server/src/integrations/ai/ai-provider-settings-keys.spec.ts

@@ -41,3 +41,35 @@ describe('UpdateAiSettingsDto.chatApiStyle', () => {
     expect(errs.find((e) => e.property === 'chatApiStyle')).toBeUndefined();
   });
 });
+
+/** DTO validation for chatContextWindow (@IsOptional @IsInt @Min(0)). */
+describe('UpdateAiSettingsDto.chatContextWindow', () => {
+  const errorsFor = async (chatContextWindow: unknown) =>
+    validate(plainToInstance(UpdateAiSettingsDto, { chatContextWindow }));
+
+  it('accepts a non-negative integer (incl. 0 = clear the limit)', async () => {
+    for (const v of [0, 200000]) {
+      const errs = await errorsFor(v);
+      expect(
+        errs.find((e) => e.property === 'chatContextWindow'),
+      ).toBeUndefined();
+    }
+  });
+
+  it('rejects a negative value', async () => {
+    const errs = await errorsFor(-1);
+    expect(errs.find((e) => e.property === 'chatContextWindow')).toBeDefined();
+  });
+
+  it('rejects a non-integer value', async () => {
+    const errs = await errorsFor(1.5);
+    expect(errs.find((e) => e.property === 'chatContextWindow')).toBeDefined();
+  });
+
+  it('accepts the field being omitted (optional)', async () => {
+    const errs = await validate(plainToInstance(UpdateAiSettingsDto, {}));
+    expect(
+      errs.find((e) => e.property === 'chatContextWindow'),
+    ).toBeUndefined();
+  });
+});

apps/server/src/integrations/ai/ai-settings.service.ts

@@ -27,6 +27,8 @@ export interface UpdateAiSettingsInput {
   driver?: AiDriver;
   chatModel?: string;
   chatApiStyle?: ChatApiStyle;
+  // Chat context-window size (tokens); 0/empty clears the limit.
+  chatContextWindow?: number;
   embeddingModel?: string;
   baseUrl?: string;
   embeddingBaseUrl?: string;
@@ -162,6 +164,8 @@ export class AiSettingsService {
       chatModel: provider.chatModel,
       // Plain passthrough; getChatModel defaults unset to 'openai-compatible'.
       chatApiStyle: provider.chatApiStyle,
+      // Admin-configured context-window size; 0/unset = no limit (badge denominator).
+      chatContextWindow: provider.chatContextWindow,
       // Cheap model id for the anonymous public-share assistant; reuses the chat
       // driver/baseUrl/apiKey. Empty/unset → callers fall back to chatModel.
       publicShareChatModel: provider.publicShareChatModel,
@@ -244,6 +248,7 @@ export class AiSettingsService {
       driver: provider.driver,
       chatModel: provider.chatModel,
       chatApiStyle: provider.chatApiStyle,
+      chatContextWindow: provider.chatContextWindow,
       embeddingModel: provider.embeddingModel,
       baseUrl: provider.baseUrl,
       embeddingBaseUrl: provider.embeddingBaseUrl,

apps/server/src/integrations/ai/ai.types.ts

@@ -35,6 +35,13 @@ export interface AiProviderSettings {
   // Chat provider implementation for the `openai` driver. Unset → defaults to
   // 'openai-compatible' (so reasoning is surfaced by default). See ChatApiStyle.
   chatApiStyle?: ChatApiStyle;
+  // Admin-configured chat model context-window size, in tokens. There is no
+  // provider-independent way to discover this (OpenAI's /v1/models usually omits
+  // it, Gemini/Ollama/OpenRouter each expose it differently), so it is entered
+  // manually. Surfaced to the chat client (via assistant message metadata) as the
+  // denominator of the header "current / max" context badge. Empty/0 = no limit
+  // known → the badge shows only the current context size.
+  chatContextWindow?: number;
   embeddingModel?: string;
   baseUrl?: string;
   // Embedding-specific base URL. Falls back to `baseUrl` when empty/unset.
@@ -73,6 +80,7 @@ export const PROVIDER_SETTINGS_KEYS = [
   'driver',
   'chatModel',
   'chatApiStyle',
+  'chatContextWindow',
   'embeddingModel',
   'baseUrl',
   'embeddingBaseUrl',
@@ -98,6 +106,10 @@ export const PROVIDER_SETTINGS_KEYS = [
 export interface ResolvedAiConfig extends Partial<AiProviderSettings> {
   driver?: AiDriver;
   chatModel?: string;
+  // Admin-configured chat context-window size (tokens); 0/unset = no limit. Used
+  // as the header context-badge denominator. Re-declared for parity with the
+  // explicit fields above.
+  chatContextWindow?: number;
   // Cheap model id for the public-share assistant; reuses the chat creds.
   publicShareChatModel?: string;
   // Agent-role id whose persona the public-share assistant adopts (empty/unset
@@ -117,6 +129,8 @@ export interface MaskedAiSettings {
   driver?: AiDriver;
   chatModel?: string;
   chatApiStyle?: ChatApiStyle;
+  // Admin-configured chat context-window size (tokens); 0/unset = no limit.
+  chatContextWindow?: number;
   embeddingModel?: string;
   baseUrl?: string;
   embeddingBaseUrl?: string;

apps/server/src/integrations/ai/dto/update-ai-settings.dto.ts

@@ -1,4 +1,4 @@
-import { IsIn, IsOptional, IsString } from 'class-validator';
+import { IsIn, IsInt, IsOptional, IsString, Min } from 'class-validator';
 import {
   AI_DRIVERS,
   AiDriver,
@@ -29,6 +29,13 @@ export class UpdateAiSettingsDto {
   @IsIn(CHAT_API_STYLES)
   chatApiStyle?: ChatApiStyle;
 
+  // Chat model context-window size in tokens (header context-badge denominator).
+  // 0 (or empty) clears the limit so the badge shows only the current context.
+  @IsOptional()
+  @IsInt()
+  @Min(0)
+  chatContextWindow?: number;
+
   @IsOptional()
   @IsString()
   embeddingModel?: string;

apps/server/test/integration/workspace-repo-ai-provider-settings.int-spec.ts

@@ -0,0 +1,91 @@
+import { Kysely, sql } from 'kysely';
+import { WorkspaceRepo } from '@docmost/db/repos/workspace/workspace.repo';
+import { getTestDb, destroyTestDb, createWorkspace } from './db';
+
+/**
+ * WorkspaceRepo.updateAiProviderSettings numeric round-trip (#189, #213).
+ *
+ * `chatContextWindow` is the first NUMERIC provider field routed through this
+ * generic SQL layer. The patch builder must cast a JS number so it lands in
+ * jsonb as a JSON NUMBER, not the JSON STRING `"200000"` — the client guards
+ * (`typeof === "number"`) reject a string, silently killing the `/ max` badge
+ * denominator. A plain `::text` cast (the prior code) regressed exactly this.
+ * These specs are real SQL and assert both the JS value type and the on-disk
+ * `jsonb_typeof`.
+ */
+describe('WorkspaceRepo.updateAiProviderSettings (numeric round-trip) [integration]', () => {
+  let db: Kysely<any>;
+  let repo: WorkspaceRepo;
+
+  beforeAll(() => {
+    db = getTestDb();
+    repo = new WorkspaceRepo(db as any);
+  });
+
+  afterAll(async () => {
+    await destroyTestDb();
+  });
+
+  it('stores chatContextWindow as a JSON number (not a "200000" string)', async () => {
+    const ws = await createWorkspace(db, { settings: undefined });
+
+    const updated = await repo.updateAiProviderSettings(ws.id, {
+      driver: 'openai',
+      chatModel: 'gpt-4o',
+      chatContextWindow: 200000,
+    });
+
+    // Returned row: the number survives as a real JS number, alongside the
+    // string fields which stay strings.
+    const provider = (updated.settings as any)?.ai?.provider;
+    expect(provider.chatContextWindow).toBe(200000);
+    expect(typeof provider.chatContextWindow).toBe('number');
+    expect(provider.driver).toBe('openai');
+    expect(provider.chatModel).toBe('gpt-4o');
+
+    // On disk: the jsonb value is typed 'number' (the must-fix assertion), and
+    // sibling string fields are typed 'string'.
+    const typed = await db
+      .selectFrom('workspaces')
+      .select([
+        sql<string>`jsonb_typeof(settings->'ai'->'provider'->'chatContextWindow')`.as(
+          'windowType',
+        ),
+        sql<string>`jsonb_typeof(settings->'ai'->'provider'->'chatModel')`.as(
+          'modelType',
+        ),
+      ])
+      .where('id', '=', ws.id)
+      .executeTakeFirstOrThrow();
+
+    expect(typed.windowType).toBe('number');
+    expect(typed.modelType).toBe('string');
+  });
+
+  it('re-reads chatContextWindow as a number after a partial-merge update', async () => {
+    const ws = await createWorkspace(db, {
+      settings: { ai: { provider: { driver: 'openai', chatModel: 'x' } } },
+    });
+
+    // Merge in only the numeric field; siblings must be preserved and the value
+    // must still be a JSON number, not a string.
+    await repo.updateAiProviderSettings(ws.id, { chatContextWindow: 128000 });
+
+    const row = await db
+      .selectFrom('workspaces')
+      .select([
+        'settings',
+        sql<string>`jsonb_typeof(settings->'ai'->'provider'->'chatContextWindow')`.as(
+          'windowType',
+        ),
+      ])
+      .where('id', '=', ws.id)
+      .executeTakeFirstOrThrow();
+
+    expect(row.windowType).toBe('number');
+    const provider = (row.settings as any)?.ai?.provider;
+    expect(provider.chatContextWindow).toBe(128000);
+    expect(provider.driver).toBe('openai');
+    expect(provider.chatModel).toBe('x');
+  });
+});