mirror of
https://github.com/multica-ai/multica.git
synced 2026-07-26 12:35:35 +02:00
fix/transcript-reading-hierarchy
5 Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
|
|
ffa8e16369 |
MUL-5228 fix(usage): bill Grok at xAI's reported cost, fix $0 resumed sessions (#5841)
* fix(agent): attribute Grok usage from the turn's own model id A resumed Grok session with no configured model recorded its entire spend under the model id "unknown", which matches no pricing row — so the task reported $0 cost instead of its real spend. grok.go only learned the model from the session handshake, and ACP's `session/load` carries no model id (only `session/new` does). When neither the agent nor MULTICA_GROK_MODEL pins a model, `daemon.go` legitimately passes an empty model, leaving nothing to attribute the usage to. Every Grok turn stamps `result._meta.modelId` with what it actually billed against. Parse it in the shared ACP result parser and use it as the fallback in grok.go. Other ACP backends are untouched — they keep whatever the handshake gave them. Co-authored-by: J <agent@multica.ai> Co-authored-by: multica-agent <github@multica.ai> * fix(metrics): price the Grok catalog in server-side cost metrics server/internal/metrics/pricing.go carried no Grok rows at all, so RecordLLMUsage took the unpriced branch for every Grok turn: llm_cost_usd reported zero Grok spend while the tokens accumulated in llm_unpriced_tokens. Internal cost monitoring simply could not see Grok. Add the six SKUs xAI publishes rates for, mirroring the frontend table in packages/views/runtimes/utils.ts. Aliases are anchored exact matches like the gpt-5.6 rows, so `grok-composer-*` (in the catalog, absent from the price sheet) stays unmapped instead of inheriting a guessed rate. Short-context tier on purpose: xAI bills a request at 2x once its prompt reaches 200K tokens, but a usage record aggregates every model call in a turn and cannot say which tier an individual request hit. A regression test re-derives the cost of a real grok 0.2.106 turn from the table and checks it against the costUsdTicks xAI returned for that turn. Co-authored-by: J <agent@multica.ai> Co-authored-by: multica-agent <github@multica.ai> * docs(changelog): scope the Grok cost claim to what was actually fixed The v0.4.9 entry promised "accurate cost" in all four languages, but the fix corrected catalog pricing and cached-input double-counting — it did not implement xAI's 2x long-context tier, so a turn whose requests reach 200K prompt tokens still under-reports by up to 50%. Say what was fixed instead. Also correct two stale claims in the pricing comment: the daemon tags usage rows with the runtime provider `grok`, not `xai` (the bare `grok-*` keys are what make them resolve), and record why thresholding the long-context tier on an aggregated row would be worse than not pricing it at all. Co-authored-by: J <agent@multica.ai> Co-authored-by: multica-agent <github@multica.ai> * feat(usage): carry the provider's own cost through to the usage record Cost has always been derived client-side as tokens x a static rate, which cannot express request-level pricing rules. xAI bills a Grok request at 2x once its prompt reaches 200K tokens, and a task_usage row aggregates every model call in a turn — so the stored token counts genuinely cannot say which tier any individual request hit. Thresholding on the aggregate would be worse than the status quo: it turns a bounded 50% under-estimate into an unbounded over-estimate for turns made of many short requests. Grok already reports what it charged, per turn, in `_meta.usage.costUsdTicks`. Parse it, carry it through agent -> daemon -> API, and store it on task_usage as a nullable BIGINT of 1e-10 USD ticks (integer, so sub-cent turns stay exact end to end). NULL means the provider reported no cost — every pre-existing row and every provider that doesn't return one. No backfill: there is no authoritative figure to recover for those, and inventing one is the guess this removes. A single hourly bucket can mix rows that carry a cost with rows that don't, so task_usage_hourly gains both halves: `cost_usd_ticks` sums the authoritative side, and `uncosted_*_tokens` carry exactly the tokens that still need a rate-table estimate. Consumers report authoritative + estimate(uncosted), which degrades to today's behaviour when nothing in the bucket is authoritative. The existing token columns keep covering every row, so token displays are untouched. The new columns are additive with defaults, so the unique key, the dirty-queue shape, and migration 102's triggers are unaffected. Co-authored-by: J <agent@multica.ai> Co-authored-by: multica-agent <github@multica.ai> * feat(usage): prefer the provider's own cost over the rate table With the authoritative figure now stored, both cost consumers use it: the usage dashboard (estimateCost / estimateCostBreakdown) and the server-side llm_cost_usd metric. Each reports `authoritative + estimate(uncosted tokens)`, so a row or bucket that mixes priced and unpriced sources stays whole. The static rate tables remain, but for Grok they are now a fallback — they still price usage recorded by a daemon too old to report cost, and every provider that reports none. Custom pricing overrides likewise apply only to the estimated half: they are a user's guess at a rate, and the authoritative half is not a guess. A model with no rate-table row but a provider-reported cost now also drops out of the "unmapped models" banner, since asking the user to supply a rate for it would invite overriding a real bill. llm_cost_usd is labelled by token_type and the provider reports one number per turn, so the charge is distributed across the buckets in the rate table's own proportions. Only the total is authoritative; the split stays an estimate, which is why this scales the existing buckets rather than inventing a label. estimateCostBreakdown does the same, keeping the stacked chart summing to the headline figure instead of silently under-drawing every Grok row. Co-authored-by: J <agent@multica.ai> Co-authored-by: multica-agent <github@multica.ai> * docs(changelog): say Grok cost now follows xAI's actual charge The earlier wording scoped the claim down to catalog pricing and cached input because the long-context tier was still unhandled. It is handled now — the cost comes from what xAI charged for the turn — so the entry can say so. Co-authored-by: J <agent@multica.ai> Co-authored-by: multica-agent <github@multica.ai> * fix(usage): keep the provider's cost when the model has no rate row Both cost consumers bailed out before reading the authoritative figure when the rate table had no row for the model. A `grok-composer-*` turn — in the Grok Build catalog, absent from xAI's price sheet — was therefore reported as $0 spend even though xAI told us exactly what it charged. Worse on the client: estimateCost returned the real cost while estimateCostBreakdown returned zeros, so the headline and the stacked chart disagreed on precisely the rows whose cost is exact — and the unmapped-models banner was (correctly) hidden, so nothing explained the discrepancy. Handle the charge before the rate lookup in both places. Without rates there is nothing to split a total by, so it lands whole in the `input` bucket, the same fallback distributeAuthoritativeCost already uses when it has no shape to scale. Tokens with no rate keep going to llm_unpriced_tokens: "unpriced" describes the rate table, not the money. Co-authored-by: J <agent@multica.ai> Co-authored-by: multica-agent <github@multica.ai> * perf(usage): drop the historical rewrite from the cost-split migration Migration 213 rewrote every existing task_usage_hourly row to seed the uncosted counters. That is a full-table UPDATE inside a schema migration — lock time, WAL and bloat all scaling with table size — for rows this issue explicitly does not care about. Deleting the UPDATE alone would have zeroed historical cost: with `NOT NULL DEFAULT 0`, an untouched row asserts "nothing here needs estimating", so every pre-split bucket would report $0 until the rollup happened to touch it. Make the uncosted columns nullable with no default instead. NULL means "never recomputed since the split existed", readers COALESCE it to the row's own token total ("estimate all of it"), and the pre-split behaviour is preserved exactly — with nothing to seed, so no rewrite. A bare ADD COLUMN is metadata-only, so this is now fast DDL. Rows heal into the split naturally as the rollup recomputes their buckets. Verified on a fresh database: a legacy-shaped row reads back as its full tokens to estimate, and a group mixing legacy and post-split buckets sums to the authoritative cost plus both rows' estimable tokens. Co-authored-by: J <agent@multica.ai> Co-authored-by: multica-agent <github@multica.ai> --------- Co-authored-by: Bohan-J <bohan@devv.ai> Co-authored-by: J <agent@multica.ai> Co-authored-by: multica-agent <github@multica.ai> |
||
|
|
da4f278330 |
fix(usage): disambiguate model pricing by provider (MUL-3346)
Disambiguate client-side model pricing by provider: generic ids (e.g. `auto`) resolve ${provider}/${model} first, so they only price under their real provider instead of borrowing Cursor's rate. Provider is LOWER()-normalized on read and write so mixed-case historical rows merge.
Closes #4199. MUL-3346
|
||
|
|
614dfae884 |
MUL-2488 feat(timezone): Scheduling / Viewing two-layer timezone architecture (#2968)
* docs(timezone): add scheduling/viewing timezone architecture RFC * feat(db): replace daily rollups with task_usage_hourly, add user.timezone Migrations 100-104: add "user".timezone (Viewing tz), build the UTC hourly task_usage_hourly rollup with its pipeline, drop the legacy task_usage_daily / task_usage_dashboard_daily pipelines, and drop the agent_runtime.timezone column. Report queries now slice day boundaries at read time by the caller-supplied @tz instead of materialising in a fixed tz. Regenerate sqlc. * feat(server): add task_usage_hourly backfill command Replace the two legacy backfill commands (daily / dashboard_daily) with a single backfill_task_usage_hourly that loads historical task_usage into the new UTC hourly rollup, sliced per workspace. * refactor(server): resolve viewing timezone in report handlers Report handlers resolve the Viewing tz per request (?tz query param, then user.timezone, then UTC) and pass it to the hourly-rollup queries. Drop the UseDailyRollup feature flags and the old raw-scan/daily-rollup dual paths, remove the /api/usage endpoints, and stop the daemon from reporting and the runtime handler from accepting host timezone. * refactor(core): switch report queries to viewing timezone API client and dashboard/runtime queries send ?tz with each report request, the user schema/types carry the new timezone field, and the runtime timezone field/mutation is removed. * feat(views): add viewing timezone preference and UI Add the useViewingTimezone hook and a Timezone setting in Preferences; report charts and the dashboard week boundary follow the viewer tz. Remove the runtime detail timezone editor and its locale strings. * fix(test): update fixtures and stabilize tests for timezone refactor The timezone architecture refactor changed several types without updating dependent test code: - RuntimeDevice no longer has a timezone field — drop it from the create-agent-dialog runtime fixture. - User now requires a timezone field — add it to the apps/web mockUser fixture. - The PreferencesTab timezone tests asserted on the async save handler (PATCH then store update) with a bare expect, racing the mutation's settle callback, and timed out querying the Select's ~600-option IANA list on a loaded CI runner. Wrap the assertions in waitFor and extend the timeout for those three tests. * docs(timezone): document self-host migration order and trigger invariant Add a SELF-HOST UPGRADE ORDER runbook to the backfill command's package comment: applying migrations 100-104 in a single migrate-up drops the legacy daily rollups before the hourly backfill runs, leaving dashboards empty until cron catches up. Add an INVARIANT comment on trg_atq_dirty_hourly noting that agent_id must be added to the trigger's OF list if it ever becomes mutable, otherwise dirty buckets for the old agent_id are silently missed. * style(runtimes): drop trailing blank line in runtime-detail |
||
|
|
380c6b5122 |
feat(usage): add Time and Tasks to daily-trend toggle (MUL-2283) (#2709)
Extends the workspace /usage page Daily tokens chart toggle from Tokens | Cost to Tokens | Cost | Time | Tasks, so users see daily run-time and task-count trends alongside spend without leaving the page. - New SQL `ListDashboardRunTimeDaily`: per-date totals from agent_task_queue (terminal tasks only), scoped to workspace and optionally project. Same time anchor as ListDashboardAgentRunTime so day boundaries line up. - New handler GET /api/dashboard/runtime/daily + TanStack Query option. - New DailyTimeChart (single-series, smart h/m/s unit) and DailyTasksChart (completed + failed stacked). - Empty-state is per-metric so a workspace with tokens but no terminal runs (or vice-versa) doesn't get a false "no data". - i18n: en + zh-Hans daily.metric_time / metric_tasks + titles. Co-authored-by: multica-agent <github@multica.ai> |
||
|
|
96695a79c5 |
feat(dashboard): workspace/project token + run-time dashboard MUL-1882 (#2462)
* feat(dashboard): workspace/project token + run-time dashboard
Add a `/{slug}/dashboard` page showing per-agent token spend and execution
time across the whole workspace, with an optional project filter.
Backend:
- Three new sqlc queries against task_usage + agent_task_queue: daily
usage, per-agent usage, per-agent total run-time. All optionally
scoped to a project via sqlc.narg('project_id'), reaching project
through the issue join.
- Handlers under /api/dashboard return the same wire shape the runtime
page already consumes (model preserved for client-side cost math).
Frontend: - Shared DashboardPage in packages/views/dashboard reusing KpiCard,
DailyCostChart, ActorAvatar, and estimateCost from the runtime page
so the visual style and pricing math stay in lock-step.
- Period selector (7/30/90d), project dropdown, four KPI tiles
(cost, tokens, run time, tasks), daily cost chart, and a combined
"cost + run time by agent" list.
- Routed in both web (app/[slug]/(dashboard)/dashboard) and desktop
(memory router); sidebar nav entry added under Workspace group.
Co-authored-by: multica-agent <github@multica.ai>
* fix(dashboard): drop stale project filter and stop double-counting tasks
Two issues caught in PR #2462 review:
1. Project filter held the previous selection's UUID across workspace
switches and project deletions: the dropdown gracefully showed
"All projects" (because the title lookup missed) while the three
dashboard queries kept forwarding the dead UUID, leaving the UI
looking like a full-workspace view but populated with empty
project-scoped data. Validate the picked UUID against the current
projects list before passing it to the queries.
2. The "by agent" table read its task count from the token rollup,
which is grouped per (agent, model). A single task that spans two
models lands twice and the agent's row reads e.g. "2 tasks" when
the real count is 1. Prefer `ListDashboardAgentRunTime`'s per-agent
distinct count when available; fall back to the token aggregate
only for agents with no terminal run yet (in-flight tasks).
Extract the merge into `mergeAgentDashboardRows` so the precedence
rules are unit-tested directly.
Co-authored-by: multica-agent <github@multica.ai>
* test(dashboard): allocate per-workspace issue.number explicitly
TestDashboardEndpoints creates two issues in the shared fixture
workspace. issue.number defaults to 0 (migration 020), and the table
carries UNIQUE (workspace_id, number), so the second insert raced the
first on the same default and failed in CI.
Allocate MAX(number) + 1 per insert so each row gets a fresh number
without stepping on rows other tests left behind in the same workspace.
Co-authored-by: multica-agent <github@multica.ai>
* feat(dashboard): rollup table + cron-driven aggregation for dashboard
Mirror the per-runtime rollup in `task_usage_daily` (migrations 073/077/082)
to remove the per-request raw aggregation the dashboard was doing.
Migration 084 adds:
- `task_usage_dashboard_daily` keyed on
(bucket_date, workspace_id, agent_id, project_id, model) — the
dimensions the dashboard actually queries, with project_id nullable
via UNIQUE NULLS NOT DISTINCT (PG15+) so "no-project" buckets
upsert cleanly.
- `task_usage_dashboard_rollup_state` watermark table.
- `task_usage_dashboard_dirty` invalidation queue.
- Triggers on agent_task_queue DELETE, task_usage DELETE, and
issue.project_id UPDATE — the cases the updated_at watermark can't
see. The project_id trigger re-attributes existing rollup rows when
a user moves an issue across projects.
- `rollup_task_usage_dashboard_daily_window(from, to)` —
idempotent recompute primitive (same shape as 077).
- `rollup_task_usage_dashboard_daily()` cron entry — own advisory
lock (4244) so it serialises independently of the runtime rollup.
- `task_usage_dashboard_rollup_lag_seconds()` health helper.
Sqlc queries `ListDashboardUsageDailyRollup` /
`ListDashboardUsageByAgentRollup` read from the new table; the handler
dispatches between rollup and raw on a separate
`UseDailyRollupForDashboard` config flag
(`USAGE_DASHBOARD_ROLLUP_ENABLED` env). Same fail-safe default (false →
raw) so operators can roll out independently of the per-runtime flag.
Bucket date is UTC (the dashboard aggregates across runtimes that may
sit in different tzs; there's no single correct local boundary).
Adds `cmd/backfill_task_usage_dashboard_daily` mirroring the existing
per-runtime backfill — operator runs it once before flipping the flag.
Tests: - TestDashboardEndpoints now also exercises the rollup read path
(raw vs. rollup, same project-scoped totals).
- TestDashboardRollupReattributesOnProjectChange verifies the
issue.project_id trigger enqueues both old + new buckets and the
next rollup tick zeroes the old project + populates the new one.
Co-authored-by: multica-agent <github@multica.ai>
* fix(dashboard-rollup): close two invalidation gaps
Two leak paths missed by migration 084 review:
1. Issue cascade DELETE — the atq BEFORE DELETE trigger runs AFTER the
issue row is gone, so `LEFT JOIN issue` returns NULL project_id and
the original-project bucket never gets cleared (issue 077 calls this
out for the runtime rollup but didn't need to act on it). Adds an
`issue BEFORE DELETE` trigger that enqueues using OLD.project_id
while the issue row is still readable.
2. `LinkTaskToIssue` (quick-create task attaching to a real issue post-
completion) UPDATEs `agent_task_queue.issue_id` from NULL to a real
id. Migration 084 only watched DELETE on atq, so usage already
rolled up under the no-project bucket stayed attributed to NULL
forever. Extends the atq trigger to fire on UPDATE OF issue_id too,
enqueueing both OLD (NULL project) and NEW (linked issue's project).
Tests: - TestDashboardRollupClearsOnIssueDelete asserts rollup row drops to
zero after issue delete + rollup tick.
- TestDashboardRollupReattributesOnLinkTaskToIssue verifies tokens
move from the NULL bucket to the project bucket after the UPDATE.
Co-authored-by: multica-agent <github@multica.ai>
---------
Co-authored-by: multica-agent <github@multica.ai>
|