feat(ai-chat): add Markdown export button for agent chat

Add an "Export chat" button to the AI agent chat window header that
downloads the active conversation as a Markdown file. The export is
client-only: it serializes the already-loaded persisted message rows
(no new network call, no server/DB change) and includes the request
internals the chat already holds — tool calls with their input/output,
per-message token usage, finish reason and error info.

- New util apps/client/src/features/ai-chat/utils/export-chat.ts:
  buildChatMarkdown() + exportChatAsMarkdown(); reuses tool-parts
  helpers so tool labels match the on-screen labels; fence() escapes
  embedded code fences; slugify() yields a safe filename with a chatId
  fallback; downloads via file-saver's saveAs.
- ai-chat-window.tsx: IconFileExport button in the header, shown only
  for a saved chat with loaded rows (canExport); drag is unaffected.
- en-US: add "Export chat" and "You" i18n keys.

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

@@ -947,6 +947,8 @@
   "Try a different search term.": "Try a different search term.",
   "Try again": "Try again",
   "Untitled chat": "Untitled chat",
+  "Export chat": "Export chat",
+  "You": "You",
   "What can I help you with?": "What can I help you with?",
   "Are you sure you want to revoke this {{credential}}": "Are you sure you want to revoke this {{credential}}",
   "Automatically provision users and groups from your identity provider via SCIM.": "Automatically provision users and groups from your identity provider via SCIM.",

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

@@ -10,6 +10,7 @@ import { Group, Loader, Tooltip } from "@mantine/core";
 import {
   IconArrowsDiagonal,
   IconChevronDown,
+  IconFileExport,
   IconGripVertical,
   IconMinus,
   IconPlus,
@@ -33,6 +34,7 @@ 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 { exportChatAsMarkdown } from "@/features/ai-chat/utils/export-chat.ts";
 import classes from "@/features/ai-chat/components/ai-chat-window.module.css";
 
 // Default window geometry (from the GitmostAgent.jsx design).
@@ -154,6 +156,26 @@ export default function AiChatWindow() {
     queryClient.invalidateQueries({ queryKey: AI_CHATS_RQ_KEY });
   }, [activeChatId, queryClient]);
 
+  // The active chat object (for its title) and an export gate: only enable the
+  // export button when an existing chat with loaded persisted rows is active.
+  const activeChat = useMemo(
+    () => chats?.items?.find((c) => c.id === activeChatId) ?? null,
+    [chats, activeChatId],
+  );
+  const canExport = !!activeChatId && !!messageRows && messageRows.length > 0;
+
+  // Build a Markdown export from the already-loaded persisted rows (no network
+  // call) and trigger a browser download. The download dialog is the feedback.
+  const handleExport = useCallback(() => {
+    if (!activeChatId || !messageRows || messageRows.length === 0) return;
+    exportChatAsMarkdown({
+      title: activeChat?.title ?? null,
+      chatId: activeChatId,
+      rows: messageRows,
+      t,
+    });
+  }, [activeChatId, messageRows, activeChat, t]);
+
   // When awaiting a new chat's id, adopt the most-recent chat (the list is
   // ordered newest-first) once it appears.
   useEffect(() => {
@@ -308,6 +330,17 @@ export default function AiChatWindow() {
         </div>
 
         <div style={{ display: "flex", alignItems: "center", gap: 1 }}>
+          {canExport && (
+            <button
+              type="button"
+              className={classes.headerBtn}
+              title={t("Export chat")}
+              aria-label={t("Export chat")}
+              onClick={handleExport}
+            >
+              <IconFileExport size={14} />
+            </button>
+          )}
           <button
             type="button"
             className={classes.headerBtn}

apps/client/src/features/ai-chat/utils/export-chat.ts

@@ -0,0 +1,194 @@
+/**
+ * Client-only Markdown exporter for an AI agent chat. Serializes the already
+ * persisted message rows (loaded via `useAiChatMessagesQuery`) into a single
+ * Markdown document and triggers a browser download. NO network call is made
+ * and NO server/DB code is touched — this reuses the rich "request internals"
+ * (tool calls with input/output, per-message token usage, finish/error info)
+ * that the chat already holds client-side.
+ *
+ * Only role labels and tool action labels are localized via the passed-in `t`
+ * translator; the structural document words (Input/Output/Error/Tokens/...) are
+ * plain English constants because the export is a technical artifact.
+ */
+
+import { saveAs } from "file-saver";
+import type { IAiChatMessageRow } from "@/features/ai-chat/types/ai-chat.types.ts";
+import {
+  ToolUiPart,
+  getToolName,
+  toolRunState,
+  toolLabelKey,
+} from "@/features/ai-chat/utils/tool-parts.tsx";
+
+// Minimal translator signature compatible with react-i18next's `t`.
+type Translate = (key: string, values?: Record<string, unknown>) => string;
+
+interface ExportChatArgs {
+  title: string | null;
+  chatId: string;
+  rows: IAiChatMessageRow[];
+  t: Translate;
+}
+
+/** A single AI SDK UIMessage part (text part or other). */
+interface TextLikePart {
+  type: string;
+  text?: string;
+}
+
+/**
+ * Stringify an arbitrary tool input/output value for a fenced block. Strings
+ * pass through as-is; everything else is pretty-printed JSON, falling back to
+ * `String(value)` if serialization throws (e.g. a circular structure).
+ */
+function stringify(value: unknown): string {
+  if (typeof value === "string") return value;
+  try {
+    return JSON.stringify(value, null, 2);
+  } catch {
+    return String(value);
+  }
+}
+
+/**
+ * Wrap `code` in a fenced code block whose backtick delimiter is LONGER than
+ * the longest backtick run inside the content, so embedded backticks (or even
+ * a literal ``` fence) never break out of the block. Minimum 3 backticks.
+ */
+function fence(code: string, lang = ""): string {
+  const runs: string[] = code.match(/`+/g) ?? [];
+  const longest = runs.reduce((m, s) => Math.max(m, s.length), 0);
+  const delim = "`".repeat(Math.max(3, longest + 1));
+  return `${delim}${lang}\n${code}\n${delim}`;
+}
+
+/**
+ * Build a filesystem-safe slug from a chat title: lowercase, collapse any run
+ * of non-alphanumeric characters to a single "-", trim stray dashes, cap the
+ * length. Falls back to `chatId` when the title yields an empty slug.
+ */
+function slugify(title: string | null, chatId: string): string {
+  const slug = (title ?? "")
+    .toLowerCase()
+    .replace(/[^a-z0-9]+/g, "-")
+    .replace(/^-+|-+$/g, "")
+    .slice(0, 50)
+    .replace(/-+$/g, "");
+  return slug.length > 0 ? slug : chatId;
+}
+
+/** Per-row token count, mirroring the header sum in ai-chat-window.tsx. */
+function rowTokens(usage: {
+  inputTokens?: number;
+  outputTokens?: number;
+  totalTokens?: number;
+}): number {
+  return (
+    usage.totalTokens ?? (usage.inputTokens ?? 0) + (usage.outputTokens ?? 0)
+  );
+}
+
+/**
+ * Serialize a chat to a Markdown string. Pure (apart from `new Date()` for the
+ * export timestamp), so it is straightforward to unit-test.
+ */
+export function buildChatMarkdown(args: ExportChatArgs): string {
+  const { title, chatId, rows, t } = args;
+  const blocks: string[] = [];
+
+  const heading = (title ?? "").trim() || t("Untitled chat");
+  blocks.push(`# ${heading}`);
+
+  // Metadata bullet list. Total tokens is only shown when there is a sum.
+  const totalTokens = rows.reduce((sum, row) => {
+    const usage = row.metadata?.usage;
+    return usage ? sum + rowTokens(usage) : sum;
+  }, 0);
+  const meta = [
+    `- Chat ID: \`${chatId}\``,
+    `- Exported: ${new Date().toISOString()}`,
+    `- Messages: ${rows.length}`,
+  ];
+  if (totalTokens > 0) meta.push(`- Total tokens: ${totalTokens}`);
+  blocks.push(meta.join("\n"));
+
+  rows.forEach((row, index) => {
+    blocks.push("---");
+
+    const roleLabel = row.role === "assistant" ? t("AI agent") : t("You");
+    blocks.push(`## ${index + 1}. ${roleLabel}`);
+
+    // Created-at kept in source as an HTML comment (out of the rendered prose).
+    blocks.push(`<!-- ${row.createdAt} -->`);
+
+    // Resolve parts: prefer the rich persisted parts, else a single text part
+    // built from the plain-text content (mirrors `rowToUiMessage`).
+    const parts: TextLikePart[] =
+      Array.isArray(row.metadata?.parts) && row.metadata.parts.length > 0
+        ? (row.metadata.parts as TextLikePart[])
+        : [{ type: "text", text: row.content ?? "" }];
+
+    for (const part of parts) {
+      if (part.type === "text") {
+        const text = (part.text ?? "").trim();
+        // Skip empty/whitespace-only text parts (matches MessageItem).
+        if (text.length > 0) blocks.push(text);
+        continue;
+      }
+
+      const isToolPart =
+        part.type.startsWith("tool-") || part.type === "dynamic-tool";
+      if (!isToolPart) continue;
+
+      const tp = part as unknown as ToolUiPart;
+      const name = getToolName(tp);
+      const { key, values } = toolLabelKey(name);
+      const label = t(key, values);
+      const state = toolRunState(tp.state);
+
+      const toolLines: string[] = [
+        `**Tool: ${label}** (\`${name}\`) — ${state}`,
+      ];
+      if (tp.input !== undefined) {
+        toolLines.push("Input:");
+        toolLines.push(fence(stringify(tp.input), "json"));
+      }
+      if (tp.output !== undefined) {
+        toolLines.push("Output:");
+        toolLines.push(fence(stringify(tp.output), "json"));
+      }
+      if (tp.errorText) {
+        toolLines.push(`**Error:** ${tp.errorText}`);
+      }
+      blocks.push(toolLines.join("\n\n"));
+    }
+
+    if (row.metadata?.error) {
+      blocks.push(`**⚠️ Error:** ${row.metadata.error}`);
+    }
+
+    const usage = row.metadata?.usage;
+    if (usage) {
+      const total = usage.totalTokens ?? rowTokens(usage);
+      blocks.push(
+        `_Tokens — in: ${usage.inputTokens ?? "?"}, out: ${usage.outputTokens ?? "?"}, total: ${total}_`,
+      );
+    }
+  });
+
+  // Blank line between blocks so the Markdown renders cleanly.
+  return blocks.join("\n\n");
+}
+
+/**
+ * Build the Markdown, wrap it in a Blob, and trigger a browser download. The
+ * file name is `gitmost-chat-<slug>-<YYYYMMDD>.md`.
+ */
+export function exportChatAsMarkdown(args: ExportChatArgs): void {
+  const markdown = buildChatMarkdown(args);
+  const slug = slugify(args.title, args.chatId);
+  const date = new Date().toISOString().slice(0, 10).replace(/-/g, "");
+  const filename = `gitmost-chat-${slug}-${date}.md`;
+  const blob = new Blob([markdown], { type: "text/markdown;charset=utf-8" });
+  saveAs(blob, filename);
+}