fix(spend): refresh expired dashboard snapshots on return - #3107
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🦞👀 Pull request received. I will update this pull request when review starts. ClawSweeper review completeClawSweeper finished reviewing this revision. The review result is being finalized. |
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| if !force, | ||
| let lastAt = self.lastSpendDashboardTokenFetchAt[provider.instanceID], | ||
| let lastScope = self.lastSpendDashboardTokenFetchScope[provider.instanceID], | ||
| lastScope == costScopeSignature, | ||
| self.spendDashboardTokenSnapshotPublicationForCurrentConfig(for: provider) != nil, |
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Route a non-forced request through the TTL check
This TTL cannot fire through production code: the sole caller in SpendDashboardSource.makeRequest always passes force: true, while .refreshMissing invokes that caller only when no current publication exists—even though this condition requires one. Consequently, the new five-minute guard cannot suppress any dashboard token scan; the caller needs to preserve the build mode's forced/non-forced semantics or perform the TTL decision before the missing-publication predicate.
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Codex review: needs maintainer review before merge. Reviewed September 8, 2026, 12:07 AM ET / 04:07 UTC. ClawSweeper reviewWhat this changesRefresh expired Usage & Spend snapshots when the pane reopens or the app becomes active, retaining the chart during loading and adding freshness-boundary tests. Merge readiness✅ Ready for maintainer review Keep open as a useful, merge-ready fix. Current main and v0.56.8 lack the expiry refresh path; no actionable introduced defects remain, and the maintainer’s head-specific native verification satisfies the proof requirement. Priority: P2 Review scores
Verification
How this fits togetherCodexBar’s shared spend controller combines local usage scans and provider publications into a snapshot used by Usage & Spend and Overview. Pane lifecycle events now check snapshot age before requesting another ordinary load. flowchart TD
A[Pane opens or app activates] --> B[Check snapshot freshness]
B -->|Fresh or loading| C[Keep current chart]
B -->|Expired or failed| D[Ordinary spend load]
E[Local scans and provider publications] --> D
D --> F[Publish refreshed snapshot]
F --> G[Usage and Spend and Overview]
Before mergeNone. Agent review detailsSecurityNone. Review metrics
Technical reviewBest possible solution: Use the existing ordinary-load pipeline to refresh expired snapshots on return while preserving visible data, provider refresh policies, and manual-refresh semantics. Do we have a high-confidence way to reproduce the issue? Yes, from source: with unchanged configuration and no intervening publication, reopening or activating on the same day does not reload current-main inputs. This review did not execute a failing main build. Is this the best way to solve the issue? Yes. A completion-based freshness check at the two lifecycle entrypoints is a narrow repair that reuses the established load and publication machinery. AGENTS.md: found and applied where relevant. Codex review notes: model internal, reasoning medium; reviewed against 2a71b479a5d4. LabelsLabel changes:
Label justifications:
EvidenceWhat I checked:
Likely related people:
Rating scale
Overall follows the weaker of proof and patch quality. Workflow
HistoryReview history (48 earlier review cycles; latest 8 shown)
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| let shouldPrimeCachedCodex: Bool = self.cachedLoader != nil | ||
| && !Set(Self.codexOwnershipByID(configuration.codexAccountIdentities).keys) | ||
| .isSubset(of: Set(self.loadedInputs.map(\.id))) | ||
| && (phase == .ordinary || self.loadedInputs.isEmpty) |
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Pattern-match the load phase instead of comparing it
LoadPhase does not conform to Equatable, and its reconciling(ForcedOutcome) payload prevents synthesized conformance, so phase == .ordinary produces a “binary operator '==' cannot be applied” compiler error and blocks every build. Preserve the prior if case .ordinary = phase pattern or introduce an explicit case-checking property; the repository-required test run would have caught this before handoff.
AGENTS.md reference: AGENTS.md:L23-L24
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| let identity = "\(logURL.path)|\(size)|\(mtime)" | ||
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| if let cached = self.readCachedEntries(identity: identity), !cached.isEmpty { | ||
| if let cached = self.readCachedEntries(identity: identity, since: since) { |
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Apply the report cutoff on cache misses
When usage.jsonl has changed since the previous read—as it normally does whenever a new request is appended—the identity check here misses and loadEntries reparses, deduplicates, sorts, and returns the entire lifetime log without applying since. Consequently, the new window only limits SQLite cache-hit reads, while active users continue hitting the unbounded latency and memory path this change is meant to avoid; apply the cutoff in the parser/miss path as well, while retaining the full cache if needed.
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| for baseline in providerBaselines where mode.shouldRefresh( | ||
| hasPublication: baseline.publication != nil, | ||
| isDashboardTokenStale: store.spendDashboardTokenFetchIsStale(for: baseline.provider)) |
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Trigger the TTL check when reopening the pane
When the pane is reopened after five minutes without a configuration change, SpendDashboardPane.onAppear calls update(configuration:), but the equality guard in SpendDashboardController.update returns before building a request, so the stale predicate added here is never evaluated. Fresh evidence in the current tree is that the patch now correctly passes the non-forced mode to the loader, while the unchanged controller guard still prevents that path from running on an ordinary reopen. The cached snapshot can therefore remain beyond the advertised TTL until a configuration/date change or manual refresh triggers another load.
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When usage.jsonl changes, this cache-miss path still parses the entire lifetime file, materializes every entry in unique, sorts the full collection, and rewrites all entries before the since filter runs. Thus active logs remain subject to unbounded peak memory and refresh latency even though the returned array is windowed. Fresh evidence in the current tree is that the follow-up only filters deduped after these full-history operations; pass the cutoff into parsing or otherwise avoid materializing old entries on the report path.
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| let rowsByPath = mode == .scanReady | ||
| ? Dictionary(grouping: snapshot.usageRows, by: \.path) | ||
| : [:] |
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Preserve row metadata in aggregate report hydration
When cached Codex usage contains reasoning tokens or usage preceding a historical pricing cutoff, .aggregateReport discards the persisted rows and reconstructs them from day/model aggregates. Those synthesized rows omit both reasoning and timestampUnixMs, while buildCodexReportFromCache derives displayed reasoning totals and date-sensitive pricing from those fields. Consequently, the cache-first snapshot can report zero reasoning and price historical usage at current rates; retain the required metadata in the aggregate representation or decode the rows needed for an equivalent report.
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| guard self.tokenSnapshotPublicationForCurrentProviderConfig(for: provider) != nil, | ||
| let legacyLast = self.lastTokenFetchAt[provider.instanceID] | ||
| else { return true } | ||
| return Date().timeIntervalSince(legacyLast) >= 5 * 60 |
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Require full dashboard coverage before adopting legacy freshness
When the regular token pipeline has just published its default 30-day snapshot before the first dashboard open, this branch treats it as fresh solely from its timestamp even though the dashboard requests scanDays == 365. capturedTokenPublication then falls back to that legacy snapshot and skips the independent dashboard fetch, so the dashboard's 365-day/All view is populated with only 30 days of history until another refresh is triggered. Reuse legacy freshness only when its history coverage and scope satisfy the dashboard request.
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| || snapshot.metadata.timeZoneIdentifier == calendar.timeZone.identifier | ||
| else { return CostUsageCache() } | ||
| return Self.cache(from: snapshot) | ||
| return Self.cache(from: snapshot, mode: mode) |
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Skip row tables in aggregate cache reads
When the Codex cache approaches its 25,000-row or 256 MB budget, .aggregateReport still calls readSnapshot(), whose implementation reads and copies every usage_rows.payload blob and every token snapshot before cache(from:mode:) discards those arrays. As a result, the new dashboard path avoids JSON decoding but still incurs full-cache SQLite I/O and memory allocation on first paint; use a mode-specific snapshot reader that does not query these tables.
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| if let cached = self.readCachedEntries(identity: identity, since: since) { | ||
| return cached |
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Fall back when the cache read fails
When the matching SQLite cache cannot be read completely—for example, sqlite3_step returns SQLITE_BUSY/SQLITE_ERROR, or every cached payload fails decoding—readCachedEntries currently returns an empty array, and this newly unconditional cache-hit branch accepts it instead of reparsing the valid JSONL source. The OpenCodex source is then published as confirmed empty and remains so until the log identity changes; distinguish a successfully completed zero-row query from read/decoding failures and return nil for the latter.
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| WHERE timestamp >= ? | ||
| ORDER BY timestamp, request_id |
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Index the timestamp used by windowed cache reads
When an existing OpenCodex cache contains a large lifetime history, this query still performs a full scan of entries and sorts the matches because the schema only indexes the request_id primary key, not timestamp. Thus every dashboard cache hit remains proportional to the entire cache rather than the 365-day window this change is intended to load; add a (timestamp, request_id) index and ensure existing schema-version-1 databases receive it.
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| let snapshot = self.readSnapshot(skipRowTables: mode == .aggregateReport) | ||
| guard snapshot.metadata.timeZoneIdentifier == nil | ||
| || snapshot.metadata.timeZoneIdentifier == calendar.timeZone.identifier | ||
| else { return CostUsageCache() } | ||
| return Self.cache(from: snapshot) | ||
| return Self.cache(from: snapshot, mode: mode) |
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Keep aggregate-hydrated pricing rows trustworthy
When cache-first hydration must rebuild a report from aggregates rather than use an exact previous report, the synthesized token-bearing rows have no eventIndex, so codexRowCostBreakdown marks them unstable and rowCostIsTrusted is always false. Standard usage then falls back to aggregate pricing that excludes the newly separated reasoning tokens, while priority evidence disables that fallback entirely and produces a nil cost. Fresh evidence is that the current patch now synthesizes reasoning/timestamp metadata, but this aggregate-mode path still discards its row-level pricing, so cached spend remains lower or unavailable until the live scan finishes.
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| Self.bindAggregateValues(aggregate, to: insert, startingAt: 4) | ||
| Self.bind(aggregate.earliestTimestampUnixMs, to: insert, at: 20) |
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Bind timestamps to the actual SQL placeholders
For every persisted file aggregate, this statement has only 18 parameters: the 14 values bound starting at index 4 end at 17, making earliest_timestamp_ms parameter 18 rather than 20. SQLite therefore returns SQLITE_RANGE for this ignored bind and inserts NULL for the timestamp; the global aggregate insert repeats the same off-by-two error at index 19 instead of 17. Fresh evidence is that the patch added timestamp persistence to preserve date-sensitive pricing, but cached historical rows still lose that metadata and resolve without their original pricing date.
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| $0 + ($1.inputTokens ?? 0) + ($1.cacheReadTokens ?? 0) | ||
| + max(0, ($1.outputTokens ?? 0) - ($1.reasoningTokens ?? 0)) |
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Stop subtracting reasoning from exclusive output
For this fixture, stored.data already exposes output exclusive of reasoning because the changed scanner stores deltaOutput - deltaReasoningTokens; expectedUnits was likewise updated to count exclusive output. Subtracting reasoningTokens here a second time therefore undercounts every reasoning-bearing entry and makes the final storedUnits == expectedUnits assertion fail. The repository-required full test run would expose this regression.
AGENTS.md reference: AGENTS.md:L23-L23
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| if self.spendDashboardTokenSnapshotPublicationForCurrentConfig(for: provider) != nil { | ||
| return false |
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Persist the timestamp after a completed dashboard fetch
After the first successful or confirmed-empty dashboard scan, this branch treats the current publication as fresh whenever lastSpendDashboardTokenFetchAt is absent, but this change also removes the only production assignment to that dictionary and no success path replaces it. With an unchanged provider scope, the five-minute comparison is consequently never reached and ordinary pane reopens reuse the publication indefinitely; record the completion time when publishing a successful or empty result while leaving failures timestamp-free.
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| let rowsByPath = mode == .scanReady | ||
| ? Dictionary(grouping: snapshot.usageRows, by: \.path) | ||
| : [:] |
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Preserve request boundaries in aggregate hydration
When a cached day/model contains multiple standard requests, this aggregate-only path discards their individual rows and later synthesizes one row containing the entire daily input. Long-context pricing is request-scoped, so two 150k-token requests below a 200k threshold become one 300k-token row; because that synthetic row has no eventIndex, makeCodexBilledDayEntry rejects its row cost and codexAggregateCostUSD returns nil once the aggregate exceeds the threshold. The cache-first dashboard therefore loses an otherwise computable cost until the live scan finishes; retain per-request threshold evidence or a trustworthy persisted computed cost.
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| // back at the output rate (see `codexResolvedCostUSD`), keeping USD unchanged while | ||
| // making token buckets additive. | ||
| let deltaReasoningTokens = deltaReasoning ?? 0 | ||
| let outputExcludingReasoning = max(0, deltaOutput - deltaReasoningTokens) |
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Preserve reasoning after making stored output exclusive
When reasoning exceeds the non-reasoning output remainder, this representation change truncates reasoning in project/model analytics. For example, an event with 100 output and 60 reasoning now stores (output: 40, reasoning: 60); CodexLocalProjectUsageIndexer forwards those values to CodexModelsUsageFragment, whose initializer in CodexModelsAnalyticsModels.swift clamps reasoning to outputTokens, reducing it to 40. Update that downstream invariant for the new exclusive-output representation so analytics retain the actual reasoning count.
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| Dictionary(uniqueKeysWithValues: request.capturedInputs | ||
| .filter { $0.sourceKind == .native } | ||
| .map { ($0.id, $0) }) |
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Preserve loaded Codex inputs before enrichment
When retained OpenCodex data is merged into exactly one native Codex account, that native input was created by codexSnapshotLoader and is not present in request.capturedInputs (Codex is represented there by codexRequests). Consequently this backup omits it, and clearExpiredOpenCodexSnapshot() cannot undo the enrichment at the missing-log deadline; if the subsequent Codex refresh is slow or fails and retains the previous input, expired OpenCodex spend remains embedded in the native row. Capture the complete pre-merge input set from the loader result rather than only the request's provider publications.
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| failedSourceIDs: request.unavailableSourceIDs, | ||
| openCodexObservation: openCodex.observation) | ||
| openCodexObservation: openCodex.observation, | ||
| freshUntil: openCodex.freshUntil) |
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Schedule expiry for cached prime results
When an initial cache prime serves retained OpenCodex entries shortly before their missing-source deadline, this propagates freshUntil, but startLoad passes the result to applyCached, which ignores the deadline and schedules no expiry. The subsequent provider/Codex load can run well past that deadline, leaving expired OpenCodex spend visible until the full load completes; arm the expiry timer when applying the cached result as well.
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Follow-up on the current head: refreshed the Spend dashboard gatekeeper anchors after subsequent upstream source shifts. The local ProviderArchitectureGatekeeperTests and full make check pass; CI is now queued for 2c1362d. |
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Integrate current main and retain the visible chart while ordinary loads refresh an expired snapshot. Refresh across bucket-day rollover even inside the TTL, and cover repeated activations during an in-flight load. Co-authored-by: Yuxin Qiao <104957188+Yuxin-Qiao@users.noreply.github.com>
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Maintainer verification complete on
The inspected synthetic screenshots are in the PR body. Changelog entry is consolidated in #3491. Land-ready; no merge performed here. Thanks @Yuxin-Qiao. |
Returning to Usage & Spend on the same day could keep an old chart indefinitely because the date-window refresh did not load new inputs. This refreshes an expired dashboard snapshot on pane appearance or app activation, retaining the chart while the load runs.
The five-minute TTL starts when a load completes. Repeated activations do not interrupt an in-flight or manual refresh, and source failures or a bucket-day rollover bypass the TTL. The ordinary load preserves existing provider refresh policies: it rescans local Codex sources and captures independent-provider publications without forcing every provider's network refresh.
Maintainer repair of @Yuxin-Qiao's contribution, integrated with current main. Regression coverage includes the 299/300-second boundary, retained chart during loading, repeated activations, and reopening across midnight.
Validation on
db18c43927d55349cda11edd1cb2058d701c2647:make checkpassed; local and committed-branch autoreview are clean through P2.make testpassed: 1,033 selections across 87 groups; one existing OAuth-cache test recovered on the runner's single group retry, with no timeouts. Exact-head CI and all nine PR checks are green. Land-ready.Native pane before expiry:
Expired snapshot retained during the new load:
Completed refresh:
Release-note context (collected in the batch's separate notes PR): Refresh stale Usage & Spend charts when returning to the pane, retain cached data while loading, and handle midnight rollover; thanks @Yuxin-Qiao.