Files
PaperClipAI/ui/src/components/transcript/useLiveRunTranscripts.ts
T
DottaandClaude Opus 4.8 3e348b96b9 perf(ui): cut live-updates churn that inflates tab memory (#9624)
## Thinking Path

> - Paperclip is the open source app people use to manage AI agents for
work
> - Its web UI keeps live views (issue threads, run transcripts,
dashboard) fresh via React Query polling plus a live-events websocket,
coordinated across tabs with a `BroadcastChannel` layer
> - Long-lived tabs viewing live agent runs grew to multi-GB memory
footprints while their JS heap stayed ~60–200 MB — so the memory is
off-heap (Blink/native + committed allocator arenas), not a classic JS
leak
> - Live profiling of a reproduced 2.7 GB / 66 MB tab showed 15–30% idle
CPU, ~3 fetches/sec across overlapping poll loops, and ~8 `setInterval`
create/clear cycles per second whose rate grew ~7× as the tab aged —
relentless allocation churn that inflates committed memory the OS never
reclaims, amplified across tabs by the cross-tab fan-out
> - This pull request cuts that churn at its four largest sources
(invalidation storm, per-instance 1 s timers, redundant polling,
unbounded streamed-run set)
> - The benefit is that idle tabs do far less periodic work, so their
off-heap footprint stops ballooning over a long session

## Linked Issues or Issue Description

No public GitHub issue exists; describing inline per CONTRIBUTING.md →
"Link Issues or Describe Them In-PR", following the bug report template.

**What happened?**

Browser tabs viewing live agent runs grew to 8–16 GB memory footprint
over a long session (multiple tabs open), while each tab's "live" JS
heap stayed only ~150–250 MB. Every idle tab also burned 15–30% CPU.
Tabs eventually approached the ~4 GB V8 heap ceiling / OS pressure and
could crash.

**Expected behavior**

Tabs viewing live runs should hold a bounded footprint and do minimal
work while idle, regardless of how long they stay open or how many tabs
are open.

**Steps to reproduce**

Open several issue/run tabs that have agents actively streaming and
leave them open for a while. Watch Chrome's Task Manager: Memory
Footprint climbs into the GBs while "JavaScript Memory" stays small, and
CPU stays high on idle tabs. Reproduced in ~90 minutes: a tab reached
2.7 GB footprint on a 66 MB JS heap, and the per-second timer-churn rate
was ~7× higher on a 90-minute-old tab than a fresh one.

**Paperclip version or commit**

Branch `fix/live-updates-churn`, off `master`.

**Deployment mode**

Local dev (`pnpm dev`), web UI. Not adapter-specific — core UI
live-updates plumbing (observed with `claude_local` / `codex_local`
runs).

## What Changed

- **`ui/src/lib/query-invalidation-batcher.ts` (new)** —
`createInvalidationBatcher` throttles + de-dupes React Query
invalidations into one flush per ~300 ms, and
`createCoalescingQueryClient` wraps the client via a `Proxy` so only
`invalidateQueries` is batched (optimistic `setQueryData` writes stay
immediate). Wired into `LiveUpdatesProvider`, which previously
invalidated synchronously on every websocket event.
- **`ui/src/hooks/useSecondTick.ts` (new)** — one shared, ref-counted,
page-wide 1 s ticker. `useLiveElapsed` in `IssueChatThread` now uses it
instead of a per-instance `setInterval` that forced a full-thread
re-render every second per live element.
- **`ui/src/components/transcript/useLiveRunTranscripts.ts`** — when the
realtime websocket is enabled, the recurring log poll backs off to a 30
s safety-net cadence instead of polling every 2 s on top of the live
stream. Added a marker for the durable poll→push rearchitecture.
- **`ui/src/lib/issueChatTranscriptRuns.ts`** —
`resolveIssueChatTranscriptRuns` now caps the streamed run set
(live/active runs always kept; most-recent linked runs fill up to 20) so
a large run history can't open a live-transcript poll per historical
run.
- **`ui/src/main.tsx`** — explicit `gcTime` so cross-tab-published cache
entries for unobserved resources are collected promptly.
- Tests for the batcher, shared ticker, and run cap.

## Verification

- `vitest`: new suites `query-invalidation-batcher.test.ts` (batcher
collapses 20 invalidations → 1 flush; keeps distinct keys/variants;
dispose cancels; proxy passes non-invalidate methods through),
`useSecondTick.test.tsx` (single ref-counted timer, stops when idle),
`issueChatTranscriptRuns.test.ts` (cap keeps newest + live). All pass.
- Existing affected suites pass: `LiveUpdatesProvider` (23),
`IssueChatThread` (), `useLiveRunTranscripts`,
`AgentDetail.instructions` — 109 tests across affected files.
- `tsc -b` clean.
- Behavior confirmed by live profiling before the change (2.7 GB / 66 MB
tab, ~8 interval churns/sec growing 7× with age). Runtime churn
reduction should be re-measured against a rebuilt bundle with the same
instrumentation.

## Risks

Low-to-moderate; all changes reduce work rather than add features.
- **Invalidation batching** delays live-driven refetches by up to ~300
ms. Optimistic `setQueryData` writes (e.g. the visible issue's new
comment) remain immediate, so foreground updates still feel instant;
only the safety-net refetch is throttled. Non-live invalidations (user
actions, mutations) are unaffected — they use the real client.
- **Poll back-off** relies on the websocket as the live source when
realtime is enabled; a 30 s fallback poll still covers gaps/reconnects
(both the transcript hook and `LiveUpdatesProvider` also
auto-reconnect).
- **Run cap (20)** means an issue with a very large run history streams
live transcripts only for its live/active + 20 most-recent runs; older
runs still open normally via their run pages.
- Downstream test fallout (timing-sensitive tests around
invalidation/polling) may need adjustment — flagged intentionally for
follow-up.

Durable follow-up (out of scope, marked in code): replace transcript/run
polling with server push (SSE/websocket deltas) so idle tabs do no
periodic work at all.

## Model Used

- **Provider:** Anthropic, via the Claude Code CLI.
- **Model:** Claude Opus 4.8 (`claude-opus-4-8`).
- **Reasoning mode:** Extended thinking enabled.
- **Capabilities used:** tool use (shell, file editing), sub-agent
fan-out for codebase analysis, and the Chrome DevTools MCP to reproduce
and profile the memory/CPU churn on a live instance.

## Checklist

- [x] I have included a thinking path that traces from project context
to this change
- [x] I have specified the model used (with version and capability
details)
- [x] I have checked ROADMAP.md and confirmed this PR does not duplicate
planned core work (a bug/perf fix, not planned core feature work)
- [x] I have searched GitHub for duplicate or related PRs and linked
them above (none found)
- [x] I have either (a) linked existing issues with `Fixes: #` / `Closes
#` / `Refs #` OR (b) described the issue in-PR following the relevant
issue template
- [x] I have not referenced internal/instance-local Paperclip issues or
links (only public GitHub `#NNN` / `github.com/paperclipai/paperclip`
URLs)
- [x] My branch name describes the change (e.g. `docs/...`, `fix/...`)
and contains no internal Paperclip ticket id or instance-derived details
- [x] I have run tests locally and they pass
- [x] I have added or updated tests where applicable
- [x] I have considered and documented any risks above
- [ ] I have updated relevant documentation to reflect my changes (N/A —
no user-facing docs; rationale documented inline)
- [x] All Paperclip CI gates are green
- [x] Greptile is 5/5 with no open P2s, recommendations, or follow-ups
- [x] I will address all Greptile and reviewer comments before
requesting merge

🤖 Generated with [Claude Code](https://claude.com/claude-code)

---------

Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
2026-07-15 14:17:37 -05:00

506 lines
18 KiB
TypeScript

import { useEffect, useMemo, useRef, useState } from "react";
import { useQuery } from "@tanstack/react-query";
import type { LiveEvent } from "@paperclipai/shared";
import { ApiError } from "../../api/client";
import { instanceSettingsApi } from "../../api/instanceSettings";
import { heartbeatsApi } from "../../api/heartbeats";
import { buildTranscript, getUIAdapter, onAdapterChange, type RunLogChunk, type TranscriptEntry } from "../../adapters";
import { queryKeys } from "../../lib/queryKeys";
import { buildSameOriginWebSocketUrl } from "../../lib/websocket-url";
// TODO(perf): this whole hook polls the log/runs endpoints on an interval. The
// durable fix is server push (SSE/websocket) for transcript deltas so idle tabs
// do no periodic work at all; the constants below only reduce the churn of the
// current polling approach.
const LOG_POLL_INTERVAL_MS = 2000;
const LOG_READ_LIMIT_BYTES = 256_000;
// When realtime websocket updates are enabled, the frequent log poll is
// redundant with the live stream; keep only a slow safety-net poll to cover
// gaps and reconnects instead of polling every couple of seconds.
const REALTIME_FALLBACK_POLL_INTERVAL_MS = 30_000;
const EMPTY_RUN_LOG_CHUNKS: RunLogChunk[] = [];
export interface RunTranscriptSource {
id: string;
status: string;
adapterType: string;
hasStoredOutput?: boolean;
logBytes?: number | null;
lastOutputBytes?: number | null;
}
interface UseLiveRunTranscriptsOptions {
runs: RunTranscriptSource[];
companyId?: string | null;
maxChunksPerRun?: number;
logPollIntervalMs?: number;
logReadLimitBytes?: number;
enableRealtimeUpdates?: boolean;
}
function readString(value: unknown): string | null {
return typeof value === "string" && value.trim().length > 0 ? value : null;
}
function isTerminalStatus(status: string): boolean {
return status === "failed" || status === "timed_out" || status === "cancelled" || status === "interrupted" || status === "succeeded";
}
function runKnownLogBytes(run: RunTranscriptSource): number | null {
const bytes = run.status === "queued"
? run.logBytes
: run.lastOutputBytes ?? run.logBytes;
return typeof bytes === "number" && Number.isFinite(bytes) && bytes > 0 ? bytes : null;
}
export function resolveInitialLogOffset(run: RunTranscriptSource, limitBytes: number): number {
const knownBytes = runKnownLogBytes(run);
if (knownBytes === null) return 0;
return Math.max(0, knownBytes - Math.max(0, limitBytes));
}
function readChunkSeq(value: unknown): number | undefined {
return typeof value === "number" && Number.isFinite(value) ? value : undefined;
}
function isStructuredStreamingTextDelta(chunk: string) {
return /"type"\s*:\s*"(?:acpx\.text_delta|text)"/.test(chunk);
}
function parsePersistedLogContent(
runId: string,
content: string,
pendingByRun: Map<string, string>,
): Array<RunLogChunk & { dedupeKey: string }> {
if (!content) return [];
const pendingKey = `${runId}:records`;
const combined = `${pendingByRun.get(pendingKey) ?? ""}${content}`;
const split = combined.split("\n");
pendingByRun.set(pendingKey, split.pop() ?? "");
const parsed: Array<RunLogChunk & { dedupeKey: string }> = [];
for (const line of split) {
const trimmed = line.trim();
if (!trimmed) continue;
try {
const raw = JSON.parse(trimmed) as { ts?: unknown; stream?: unknown; chunk?: unknown; seq?: unknown };
const stream = raw.stream === "stderr" || raw.stream === "system" ? raw.stream : "stdout";
const chunk = typeof raw.chunk === "string" ? raw.chunk : "";
const ts = typeof raw.ts === "string" ? raw.ts : new Date().toISOString();
if (!chunk) continue;
parsed.push({
ts,
stream,
chunk,
seq: readChunkSeq(raw.seq),
dedupeKey: `log:${runId}:${ts}:${stream}:${chunk}`,
});
} catch {
// Ignore malformed log rows.
}
}
return parsed;
}
export function useLiveRunTranscripts({
runs,
companyId,
maxChunksPerRun = 200,
logPollIntervalMs = LOG_POLL_INTERVAL_MS,
logReadLimitBytes = LOG_READ_LIMIT_BYTES,
enableRealtimeUpdates = true,
}: UseLiveRunTranscriptsOptions) {
const runsKey = useMemo(
() =>
runs
.map((run) => {
const logBytes = typeof run.logBytes === "number" ? run.logBytes : "";
const lastOutputBytes = typeof run.lastOutputBytes === "number" ? run.lastOutputBytes : "";
return `${run.id}:${run.status}:${run.adapterType}:${run.hasStoredOutput === true ? "1" : "0"}:${logBytes}:${lastOutputBytes}`;
})
.sort((a, b) => a.localeCompare(b))
.join(","),
[runs],
);
const normalizedRuns = useMemo(() => runs.map((run) => ({ ...run })), [runsKey]);
const [chunksByRun, setChunksByRun] = useState<Map<string, RunLogChunk[]>>(new Map());
const [hydratedRunIds, setHydratedRunIds] = useState<Set<string>>(new Set());
const seenChunkKeysRef = useRef(new Set<string>());
// Highest sequenced chunk trimmed out of a run's retained window; older
// records re-delivered by the other transport are dropped instead of being
// re-inserted ahead of newer output.
const trimmedSeqFloorByRunRef = useRef(new Map<string, number>());
const pendingLogRowsByRunRef = useRef(new Map<string, string>());
const logOffsetByRunRef = useRef(new Map<string, number>());
const missingTerminalLogRunIdsRef = useRef(new Set<string>());
const transcriptCacheRef = useRef(new Map<string, {
adapterType: string;
chunks: RunLogChunk[];
censorUsernameInLogs: boolean;
parserTick: number;
transcript: TranscriptEntry[];
}>());
// Tick counter to force transcript recomputation when dynamic parser loads
const [parserTick, setParserTick] = useState(0);
useEffect(() => {
return onAdapterChange(() => setParserTick((t) => t + 1));
}, []);
const { data: generalSettings } = useQuery({
queryKey: queryKeys.instance.generalSettings,
queryFn: () => instanceSettingsApi.getGeneral(),
});
const runById = useMemo(() => new Map(normalizedRuns.map((run) => [run.id, run])), [normalizedRuns]);
const activeRunIds = useMemo(
() => new Set(normalizedRuns.filter((run) => !isTerminalStatus(run.status)).map((run) => run.id)),
[normalizedRuns],
);
const runIdsKey = useMemo(
() => normalizedRuns.map((run) => run.id).sort((a, b) => a.localeCompare(b)).join(","),
[normalizedRuns],
);
const appendChunks = (runId: string, chunks: Array<RunLogChunk & { dedupeKey: string }>) => {
if (chunks.length === 0) return;
setChunksByRun((prev) => {
const next = new Map(prev);
const existing = [...(next.get(runId) ?? [])];
let changed = false;
for (const chunk of chunks) {
// Sequenced log chunks (persisted rows and websocket log payloads)
// dedupe and order by the server-assigned monotonic seq. Identical
// token deltas from ACP-style adapters often share the same
// millisecond ts and chunk text, so content-based keys drop real
// output; seq keeps every record and restores emit order when the
// websocket and the poller interleave.
if (typeof chunk.seq === "number") {
const seqFloor = trimmedSeqFloorByRunRef.current.get(runId) ?? 0;
if (chunk.seq <= seqFloor) continue;
const duplicateAt = existing.findIndex((item) => item.seq === chunk.seq);
if (duplicateAt !== -1) {
// Same record arrived via the other delivery path. Prefer the
// longer payload: websocket chunks may be tail-truncated while
// the persisted row is complete.
if (chunk.chunk.length > existing[duplicateAt]!.chunk.length) {
existing[duplicateAt] = { ts: chunk.ts, stream: chunk.stream, chunk: chunk.chunk, seq: chunk.seq };
changed = true;
}
continue;
}
// Insert in seq order relative to the trailing sequenced chunks so
// late-arriving records from the slower delivery path land where
// they were emitted. Unsequenced chunks act as an ordering barrier.
let insertAt = existing.length;
while (insertAt > 0) {
const prior = existing[insertAt - 1]!;
if (typeof prior.seq !== "number" || prior.seq < chunk.seq) break;
insertAt -= 1;
}
existing.splice(insertAt, 0, { ts: chunk.ts, stream: chunk.stream, chunk: chunk.chunk, seq: chunk.seq });
changed = true;
continue;
}
if (!isStructuredStreamingTextDelta(chunk.chunk)) {
if (seenChunkKeysRef.current.has(chunk.dedupeKey)) continue;
seenChunkKeysRef.current.add(chunk.dedupeKey);
}
existing.push({ ts: chunk.ts, stream: chunk.stream, chunk: chunk.chunk });
changed = true;
}
if (!changed) return prev;
if (seenChunkKeysRef.current.size > 12000) {
seenChunkKeysRef.current.clear();
}
if (existing.length > maxChunksPerRun) {
const trimmed = existing.splice(0, existing.length - maxChunksPerRun);
let seqFloor = trimmedSeqFloorByRunRef.current.get(runId) ?? 0;
for (const item of trimmed) {
if (typeof item.seq === "number" && item.seq > seqFloor) seqFloor = item.seq;
}
if (seqFloor > 0) trimmedSeqFloorByRunRef.current.set(runId, seqFloor);
}
next.set(runId, existing);
return next;
});
};
useEffect(() => {
const knownRunIds = new Set(normalizedRuns.map((run) => run.id));
setChunksByRun((prev) => {
const next = new Map<string, RunLogChunk[]>();
for (const [runId, chunks] of prev) {
if (knownRunIds.has(runId)) {
next.set(runId, chunks);
}
}
return next.size === prev.size ? prev : next;
});
setHydratedRunIds((prev) => {
const next = new Set<string>();
for (const runId of prev) {
if (knownRunIds.has(runId)) {
next.add(runId);
}
}
return next.size === prev.size ? prev : next;
});
for (const key of pendingLogRowsByRunRef.current.keys()) {
const runId = key.replace(/:records$/, "");
if (!knownRunIds.has(runId)) {
pendingLogRowsByRunRef.current.delete(key);
}
}
for (const runId of logOffsetByRunRef.current.keys()) {
if (!knownRunIds.has(runId)) {
logOffsetByRunRef.current.delete(runId);
}
}
for (const runId of trimmedSeqFloorByRunRef.current.keys()) {
if (!knownRunIds.has(runId)) {
trimmedSeqFloorByRunRef.current.delete(runId);
}
}
for (const runId of missingTerminalLogRunIdsRef.current.keys()) {
if (!knownRunIds.has(runId)) {
missingTerminalLogRunIdsRef.current.delete(runId);
}
}
for (const runId of transcriptCacheRef.current.keys()) {
if (!knownRunIds.has(runId)) {
transcriptCacheRef.current.delete(runId);
}
}
}, [normalizedRuns]);
useEffect(() => {
if (normalizedRuns.length === 0) return;
let cancelled = false;
const readRunLog = async (run: RunTranscriptSource) => {
if (missingTerminalLogRunIdsRef.current.has(run.id)) {
return;
}
const offset = logOffsetByRunRef.current.get(run.id) ?? resolveInitialLogOffset(run, logReadLimitBytes);
try {
const result = await heartbeatsApi.log(run.id, offset, logReadLimitBytes);
if (cancelled) return;
appendChunks(run.id, parsePersistedLogContent(run.id, result.content, pendingLogRowsByRunRef.current));
if (result.nextOffset !== undefined) {
logOffsetByRunRef.current.set(run.id, result.nextOffset);
return;
}
if (result.content.length > 0) {
logOffsetByRunRef.current.set(run.id, offset + result.content.length);
}
} catch (error) {
if (error instanceof ApiError && error.status === 404 && isTerminalStatus(run.status)) {
missingTerminalLogRunIdsRef.current.add(run.id);
}
} finally {
if (!cancelled) {
setHydratedRunIds((prev) => {
if (prev.has(run.id)) return prev;
const next = new Set(prev);
next.add(run.id);
return next;
});
}
}
};
const readAll = async () => {
await Promise.all(normalizedRuns.map((run) => readRunLog(run)));
};
void readAll();
const activeRuns = normalizedRuns.filter((run) => !isTerminalStatus(run.status));
// The realtime websocket is the primary live source when enabled, so the
// recurring poll only needs to run as a slow fallback rather than doubling
// the live update work every couple of seconds.
const effectivePollMs = enableRealtimeUpdates
? Math.max(logPollIntervalMs, REALTIME_FALLBACK_POLL_INTERVAL_MS)
: logPollIntervalMs;
const interval = activeRuns.length > 0 && effectivePollMs > 0
? window.setInterval(() => {
void Promise.all(activeRuns.map((run) => readRunLog(run)));
}, effectivePollMs)
: null;
return () => {
cancelled = true;
if (interval !== null) window.clearInterval(interval);
};
}, [enableRealtimeUpdates, logPollIntervalMs, logReadLimitBytes, normalizedRuns, runIdsKey]);
useEffect(() => {
if (!enableRealtimeUpdates) return;
if (!companyId || activeRunIds.size === 0) return;
let closed = false;
let reconnectTimer: number | null = null;
let socket: WebSocket | null = null;
const scheduleReconnect = () => {
if (closed) return;
reconnectTimer = window.setTimeout(connect, 1500);
};
const connect = () => {
if (closed) return;
const url = buildSameOriginWebSocketUrl(
`/api/companies/${encodeURIComponent(companyId)}/events/ws`,
);
socket = new WebSocket(url);
socket.onmessage = (message) => {
const raw = typeof message.data === "string" ? message.data : "";
if (!raw) return;
let event: LiveEvent;
try {
event = JSON.parse(raw) as LiveEvent;
} catch {
return;
}
if (event.companyId !== companyId) return;
const payload = event.payload ?? {};
const runId = readString(payload["runId"]);
if (!runId || !activeRunIds.has(runId)) return;
if (!runById.has(runId)) return;
if (event.type === "heartbeat.run.log") {
const chunk = readString(payload["chunk"]);
if (!chunk) return;
const ts = readString(payload["ts"]) ?? event.createdAt;
const stream =
readString(payload["stream"]) === "stderr"
? "stderr"
: readString(payload["stream"]) === "system"
? "system"
: "stdout";
appendChunks(runId, [{
ts,
stream,
chunk,
seq: readChunkSeq(payload["seq"]),
dedupeKey: `log:${runId}:${ts}:${stream}:${chunk}`,
}]);
return;
}
if (event.type === "heartbeat.run.event") {
const seq = typeof payload["seq"] === "number" ? payload["seq"] : null;
const eventType = readString(payload["eventType"]) ?? "event";
const messageText = readString(payload["message"]) ?? eventType;
appendChunks(runId, [{
ts: event.createdAt,
stream: eventType === "error" ? "stderr" : "system",
chunk: messageText,
dedupeKey: `socket:event:${runId}:${seq ?? `${eventType}:${messageText}:${event.createdAt}`}`,
}]);
return;
}
if (event.type === "heartbeat.run.status") {
const status = readString(payload["status"]) ?? "updated";
appendChunks(runId, [{
ts: event.createdAt,
stream: isTerminalStatus(status) && status !== "succeeded" ? "stderr" : "system",
chunk: `run ${status}`,
dedupeKey: `socket:status:${runId}:${status}:${readString(payload["finishedAt"]) ?? ""}`,
}]);
}
};
socket.onerror = () => {
socket?.close();
};
socket.onclose = () => {
scheduleReconnect();
};
};
connect();
return () => {
closed = true;
if (reconnectTimer !== null) window.clearTimeout(reconnectTimer);
if (socket) {
socket.onmessage = null;
socket.onerror = null;
socket.onclose = null;
if (socket.readyState === WebSocket.CONNECTING) {
// Defer the close until the handshake completes so the browser
// does not emit a noisy "closed before the connection is established"
// warning during rapid run teardown.
socket.onopen = () => {
socket?.close(1000, "live_run_transcripts_unmount");
};
} else if (socket.readyState === WebSocket.OPEN) {
socket.close(1000, "live_run_transcripts_unmount");
}
}
};
}, [activeRunIds, companyId, enableRealtimeUpdates, runById]);
const transcriptByRun = useMemo(() => {
const next = new Map<string, TranscriptEntry[]>();
const censorUsernameInLogs = generalSettings?.censorUsernameInLogs === true;
const cache = transcriptCacheRef.current;
const currentRunIds = new Set<string>();
for (const run of normalizedRuns) {
currentRunIds.add(run.id);
const chunks = chunksByRun.get(run.id) ?? EMPTY_RUN_LOG_CHUNKS;
const cached = cache.get(run.id);
if (
cached &&
cached.adapterType === run.adapterType &&
cached.chunks === chunks &&
cached.censorUsernameInLogs === censorUsernameInLogs &&
cached.parserTick === parserTick
) {
next.set(run.id, cached.transcript);
continue;
}
const adapter = getUIAdapter(run.adapterType);
const transcript = buildTranscript(chunks, adapter, {
censorUsernameInLogs,
});
cache.set(run.id, {
adapterType: run.adapterType,
chunks,
censorUsernameInLogs,
parserTick,
transcript,
});
next.set(run.id, transcript);
}
for (const runId of cache.keys()) {
if (!currentRunIds.has(runId)) {
cache.delete(runId);
}
}
return next;
}, [chunksByRun, generalSettings?.censorUsernameInLogs, normalizedRuns, parserTick]);
return {
transcriptByRun,
isInitialHydrating: normalizedRuns.some((run) => !hydratedRunIds.has(run.id)),
hasOutputForRun(runId: string) {
return (chunksByRun.get(runId)?.length ?? 0) > 0 || runById.get(runId)?.hasStoredOutput === true;
},
};
}