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* 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>
178 lines
9.3 KiB
SQL
178 lines
9.3 KiB
SQL
-- name: UpsertTaskUsage :exec
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-- Bumps `updated_at` on INSERT and on conflict so the hourly-rollup worker
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-- detects the row as dirty and re-aggregates its bucket.
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-- Without the conflict-side bump, a correction to historical token counts
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-- would never propagate to the rollup.
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-- cost_usd_ticks is the provider's own price for this usage (1e-10 USD), NULL
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-- when it reports none. It is overwritten like the token counters so a
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-- corrected report replaces the previous figure rather than accumulating.
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INSERT INTO task_usage (task_id, provider, model, input_tokens, output_tokens, cache_read_tokens, cache_write_tokens, cost_usd_ticks, updated_at)
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VALUES ($1, $2, $3, $4, $5, $6, $7, sqlc.narg('cost_usd_ticks'), now())
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ON CONFLICT (task_id, provider, model)
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DO UPDATE SET
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input_tokens = EXCLUDED.input_tokens,
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output_tokens = EXCLUDED.output_tokens,
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cache_read_tokens = EXCLUDED.cache_read_tokens,
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cache_write_tokens = EXCLUDED.cache_write_tokens,
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cost_usd_ticks = EXCLUDED.cost_usd_ticks,
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updated_at = now();
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-- name: GetTaskUsage :many
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SELECT * FROM task_usage
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WHERE task_id = $1
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ORDER BY model;
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-- name: GetIssueUsageSummary :one
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SELECT
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COALESCE(SUM(tu.input_tokens), 0)::bigint AS total_input_tokens,
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COALESCE(SUM(tu.output_tokens), 0)::bigint AS total_output_tokens,
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COALESCE(SUM(tu.cache_read_tokens), 0)::bigint AS total_cache_read_tokens,
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COALESCE(SUM(tu.cache_write_tokens), 0)::bigint AS total_cache_write_tokens,
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COALESCE(SUM(tu.cost_usd_ticks), 0)::bigint AS total_cost_usd_ticks,
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COALESCE(SUM(tu.input_tokens) FILTER (WHERE tu.cost_usd_ticks IS NULL), 0)::bigint AS uncosted_input_tokens,
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COALESCE(SUM(tu.output_tokens) FILTER (WHERE tu.cost_usd_ticks IS NULL), 0)::bigint AS uncosted_output_tokens,
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COALESCE(SUM(tu.cache_read_tokens) FILTER (WHERE tu.cost_usd_ticks IS NULL), 0)::bigint AS uncosted_cache_read_tokens,
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COALESCE(SUM(tu.cache_write_tokens) FILTER (WHERE tu.cost_usd_ticks IS NULL), 0)::bigint AS uncosted_cache_write_tokens,
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COUNT(DISTINCT tu.task_id)::int AS task_count
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FROM task_usage tu
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JOIN agent_task_queue atq ON atq.id = tu.task_id
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WHERE atq.issue_id = $1;
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-- name: ListDashboardUsageDaily :many
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-- Daily per-(date, provider, model) token aggregates for the workspace, served
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-- from the UTC-bucketed `task_usage_hourly` table and
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-- sliced to calendar days under the caller-supplied @tz. Optionally
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-- scoped to a single project via sqlc.narg('project_id'). Powers the
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-- workspace dashboard's daily cost chart.
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-- The viewer's tz is applied here at query time, so a viewer in
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-- Asia/Shanghai gets their "today" cut at +08 and one in
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-- America/Los_Angeles gets theirs at -08 against the same UTC rows.
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--
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-- @since is already the viewer's local start-of-day-(N) as a UTC
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-- instant (computed by parseSinceParamInTZ). It must NOT be re-truncated
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-- with DATE_TRUNC here — DATE_TRUNC operates in the session tz and would
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-- snap the cutoff back to UTC midnight, dragging in an extra partial
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-- local day for any non-UTC viewer.
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-- provider is LOWER()-normalized so mixed-case historical rows (written
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-- before the handler lowercased provider on write) merge with new rows
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-- instead of forming a separate case-variant bucket.
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SELECT
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DATE(bucket_hour AT TIME ZONE sqlc.arg('tz')::text) AS date,
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LOWER(provider) AS provider,
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model,
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SUM(input_tokens)::bigint AS input_tokens,
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SUM(output_tokens)::bigint AS output_tokens,
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SUM(cache_read_tokens)::bigint AS cache_read_tokens,
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SUM(cache_write_tokens)::bigint AS cache_write_tokens,
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SUM(cost_usd_ticks)::bigint AS cost_usd_ticks,
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SUM(COALESCE(uncosted_input_tokens, input_tokens))::bigint AS uncosted_input_tokens,
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SUM(COALESCE(uncosted_output_tokens, output_tokens))::bigint AS uncosted_output_tokens,
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SUM(COALESCE(uncosted_cache_read_tokens, cache_read_tokens))::bigint AS uncosted_cache_read_tokens,
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SUM(COALESCE(uncosted_cache_write_tokens, cache_write_tokens))::bigint AS uncosted_cache_write_tokens,
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SUM(task_count)::int AS task_count
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FROM task_usage_hourly
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WHERE workspace_id = $1
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AND bucket_hour >= sqlc.arg('since')::timestamptz
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AND (sqlc.narg('project_id')::uuid IS NULL OR project_id = sqlc.narg('project_id'))
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GROUP BY DATE(bucket_hour AT TIME ZONE sqlc.arg('tz')::text), LOWER(provider), model
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ORDER BY DATE(bucket_hour AT TIME ZONE sqlc.arg('tz')::text) DESC, LOWER(provider), model;
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-- name: ListDashboardUsageByAgent :many
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-- Per-(agent, provider, model) token aggregates from `task_usage_hourly`. No
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-- date grouping in the result, so this query takes no `@tz` — the
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-- @since cutoff is a raw timestamptz the Go layer has already computed
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-- in the viewer's tz. Model dimension is preserved so the client can
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-- compute cost from its per-model pricing table; the client folds rows
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-- by agent for the "by agent" list on the dashboard.
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--
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-- task_count is summed across hourly buckets — one task that spans
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-- multiple hours lands in multiple buckets, so this over-counts by
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-- hour the same way the daily version over-counted by day. The
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-- frontend prefers `ListDashboardAgentRunTime` for the user-facing
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-- "tasks" column, so this stays informational only.
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-- provider is LOWER()-normalized so mixed-case historical rows merge with
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-- new rows (see ListDashboardUsageDaily).
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SELECT
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agent_id,
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LOWER(provider) AS provider,
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model,
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SUM(input_tokens)::bigint AS input_tokens,
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SUM(output_tokens)::bigint AS output_tokens,
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SUM(cache_read_tokens)::bigint AS cache_read_tokens,
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SUM(cache_write_tokens)::bigint AS cache_write_tokens,
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SUM(cost_usd_ticks)::bigint AS cost_usd_ticks,
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SUM(COALESCE(uncosted_input_tokens, input_tokens))::bigint AS uncosted_input_tokens,
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SUM(COALESCE(uncosted_output_tokens, output_tokens))::bigint AS uncosted_output_tokens,
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SUM(COALESCE(uncosted_cache_read_tokens, cache_read_tokens))::bigint AS uncosted_cache_read_tokens,
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SUM(COALESCE(uncosted_cache_write_tokens, cache_write_tokens))::bigint AS uncosted_cache_write_tokens,
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SUM(task_count)::int AS task_count
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FROM task_usage_hourly
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WHERE workspace_id = $1
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AND bucket_hour >= @since::timestamptz
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AND (sqlc.narg('project_id')::uuid IS NULL OR project_id = sqlc.narg('project_id'))
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GROUP BY agent_id, LOWER(provider), model
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ORDER BY agent_id, LOWER(provider), model;
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-- name: ListDashboardRunTimeDaily :many
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-- Daily per-date run time + task counts for the workspace, optionally
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-- scoped to a single project. Powers the workspace dashboard's "Time"
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-- and "Tasks" metrics on the same toggle as Tokens / Cost. Bucketed by
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-- completed_at (terminal time) sliced into calendar days under the
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-- caller-supplied @tz — same Viewing-tz treatment as ListDashboardUsageDaily
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-- so the Time / Tasks tabs cut their day boundary identically to the
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-- Cost / Tokens tabs (a viewer east of UTC would otherwise see the four
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-- tabs disagree on a "1d" window). Only terminal tasks (completed or
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-- failed) with both started_at and completed_at populated contribute.
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--
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-- @since is already the viewer's local start-of-day-(N) (parseSinceParamInTZ)
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-- — passed straight through, NOT re-truncated; see ListDashboardUsageDaily.
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SELECT
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DATE(atq.completed_at AT TIME ZONE sqlc.arg('tz')::text) AS date,
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COALESCE(
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SUM(EXTRACT(EPOCH FROM (atq.completed_at - atq.started_at)))::bigint,
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0
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)::bigint AS total_seconds,
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COUNT(*)::int AS task_count,
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COUNT(*) FILTER (WHERE atq.status = 'failed')::int AS failed_count
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FROM agent_task_queue atq
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JOIN agent a ON a.id = atq.agent_id
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LEFT JOIN issue i ON i.id = atq.issue_id
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WHERE a.workspace_id = $1
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AND atq.status IN ('completed', 'failed')
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AND atq.started_at IS NOT NULL
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AND atq.completed_at IS NOT NULL
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AND atq.completed_at >= sqlc.arg('since')::timestamptz
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AND (sqlc.narg('project_id')::uuid IS NULL OR i.project_id = sqlc.narg('project_id'))
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GROUP BY DATE(atq.completed_at AT TIME ZONE sqlc.arg('tz')::text)
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ORDER BY DATE(atq.completed_at AT TIME ZONE sqlc.arg('tz')::text) DESC;
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-- name: ListDashboardAgentRunTime :many
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-- Per-agent total task run time and task count for the workspace, optionally
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-- scoped to a single project. Counts only terminal runs (completed or failed)
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-- with both started_at and completed_at populated — queued/running tasks have
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-- no finite duration. Anchored on completed_at so the window matches the
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-- token cost window (which is anchored on tu.created_at, ~= completion time).
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--
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-- No date bucketing, so no @tz — but @since is the viewer's local
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-- start-of-day-(N) so the "last N days" window lines up with the per-agent
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-- cost card; passed straight through without re-truncation.
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SELECT
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atq.agent_id,
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COALESCE(
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SUM(EXTRACT(EPOCH FROM (atq.completed_at - atq.started_at)))::bigint,
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0
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)::bigint AS total_seconds,
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COUNT(*)::int AS task_count,
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COUNT(*) FILTER (WHERE atq.status = 'failed')::int AS failed_count
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FROM agent_task_queue atq
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JOIN agent a ON a.id = atq.agent_id
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LEFT JOIN issue i ON i.id = atq.issue_id
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WHERE a.workspace_id = $1
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AND atq.status IN ('completed', 'failed')
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AND atq.started_at IS NOT NULL
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AND atq.completed_at IS NOT NULL
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AND atq.completed_at >= @since::timestamptz
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AND (sqlc.narg('project_id')::uuid IS NULL OR i.project_id = sqlc.narg('project_id'))
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GROUP BY atq.agent_id
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ORDER BY total_seconds DESC;
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