feat(web): show LLM model name in stage view toolbar

Extracts the model from `stage.prompt`, `agent.session.activated`, and
`agent.cli.started` events that the stage already loads, and renders it
on the right side of the events toolbar with a CpuChipIcon.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

apps/fabro-web/app/routes/run-stages.test.ts

@@ -1,7 +1,7 @@
 import { describe, expect, test } from "bun:test";
 import type { EventEnvelope } from "@qltysh/fabro-api-client";
 
-import { eventsToActivity } from "./run-stages";
+import { eventsToActivity, extractStageModel } from "./run-stages";
 
 function envelope(seq: number, partial: Partial<EventEnvelope>): EventEnvelope {
   return {
@@ -163,6 +163,63 @@ describe("eventsToActivity", () => {
     }
   });
 
+  test("extractStageModel pulls model from agent.session.activated, ignoring other stages", () => {
+    const events: EventEnvelope[] = [
+      envelope(1, {
+        event: "agent.session.activated",
+        stage_id: "simplify@1",
+        node_id: "simplify",
+        properties: { provider: "anthropic", model: "claude-sonnet-4-5" },
+      }),
+      envelope(2, {
+        event: "agent.session.activated",
+        stage_id: "verify@1",
+        node_id: "verify",
+        properties: { provider: "openai", model: "gpt-5" },
+      }),
+    ];
+
+    expect(extractStageModel(events, "simplify@1")).toBe("claude-sonnet-4-5");
+    expect(extractStageModel(events, "verify@1")).toBe("gpt-5");
+    expect(extractStageModel(events, "fmt@1")).toBe(null);
+  });
+
+  test("extractStageModel uses latest stage event with a model", () => {
+    const events: EventEnvelope[] = [
+      envelope(1, {
+        event: "stage.prompt",
+        stage_id: "agent@1",
+        node_id: "agent",
+        properties: { model: "claude-opus-4-5" },
+      }),
+      envelope(2, {
+        event: "agent.cli.started",
+        stage_id: "agent@1",
+        node_id: "agent",
+        properties: {
+          provider: "anthropic",
+          model: "claude-sonnet-4-6",
+          command: "claude",
+        },
+      }),
+    ];
+
+    expect(extractStageModel(events, "agent@1")).toBe("claude-sonnet-4-6");
+  });
+
+  test("extractStageModel ignores model from unrelated event types", () => {
+    const events: EventEnvelope[] = [
+      envelope(1, {
+        event: "agent.message",
+        stage_id: "agent@1",
+        node_id: "agent",
+        properties: { text: "hi", model: "should-be-ignored" },
+      }),
+    ];
+
+    expect(extractStageModel(events, "agent@1")).toBe(null);
+  });
+
   test("ignores unknown event types and events for other stages", () => {
     const events: EventEnvelope[] = [
       envelope(1, {

apps/fabro-web/app/routes/run-stages.tsx

@@ -10,6 +10,7 @@ import { XMarkIcon } from "@heroicons/react/24/outline";
 import {
   CheckIcon,
   ChevronUpDownIcon,
+  CpuChipIcon,
   FunnelIcon,
   MagnifyingGlassIcon,
 } from "@heroicons/react/16/solid";
@@ -195,6 +196,26 @@ export function eventsToActivity(events: EventEnvelope[], stageId: string): Turn
   return turns;
 }
 
+const STAGE_MODEL_EVENT_NAMES = new Set([
+  "stage.prompt",
+  "agent.session.activated",
+  "agent.cli.started",
+]);
+
+export function extractStageModel(
+  events: EventEnvelope[],
+  stageId: string,
+): string | null {
+  let model: string | null = null;
+  for (const e of events) {
+    if (activityEventStageId(e) !== stageId) continue;
+    if (!e.event || !STAGE_MODEL_EVENT_NAMES.has(e.event)) continue;
+    const candidate = getString(e.properties ?? {}, "model");
+    if (candidate) model = candidate;
+  }
+  return model;
+}
+
 function turnLabel(turn: TurnType): string {
   switch (turn.kind) {
     case "system":
@@ -816,6 +837,7 @@ function EventsToolbar({
   onSearchChange,
   filteredCount,
   totalCount,
+  model,
 }: {
   tab: EventsTab;
   onTabChange: (tab: EventsTab) => void;
@@ -828,6 +850,7 @@ function EventsToolbar({
   onSearchChange: (value: string) => void;
   filteredCount: number;
   totalCount: number;
+  model: string | null;
 }) {
   const transcriptAllSelected = selectedKinds.length === EVENT_KINDS.length;
   const debugAllSelected =
@@ -879,6 +902,15 @@ function EventsToolbar({
           {filteredCount.toLocaleString()} of {totalCount.toLocaleString()} events
         </span>
       )}
+      {model && (
+        <span
+          className="inline-flex items-center gap-1.5 text-xs text-fg-muted"
+          title="LLM model used for this stage"
+        >
+          <CpuChipIcon className="size-3.5" aria-hidden="true" />
+          <span className="font-mono">{model}</span>
+        </span>
+      )}
     </div>
   );
 }
@@ -949,6 +981,14 @@ export default function RunStages() {
     }
     return Array.from(set).sort();
   }, [debugEvents]);
+  const stageModel = useMemo(
+    () =>
+      selectedStageId
+        ? extractStageModel(stageEventsQuery.data ?? [], selectedStageId)
+        : null,
+    [stageEventsQuery.data, selectedStageId],
+  );
+
   const filteredDebugEvents = useMemo<EventEnvelope[]>(() => {
     const useCategoryFilter = selectedDebugCategories.length > 0;
     const cats = new Set(selectedDebugCategories);
@@ -1008,6 +1048,7 @@ export default function RunStages() {
               onSearchChange={setSearch}
               filteredCount={tab === "transcript" ? filteredTurns.length : filteredDebugEvents.length}
               totalCount={tab === "transcript" ? turns.length : debugEvents.length}
+              model={stageModel}
             />
           </div>
         </div>