Scrum4Me/lib/insights/token-history.ts
Janpeter Visser 8c63ba377d
feat(PBI-67): model + mode-selectie per ClaudeJob-kind (#169)
* feat(PBI-67/ST-1297): datamodel-velden voor job-model-selectie

Voegt 8 nieuwe optionele velden toe verspreid over Product, Task en
ClaudeJob ten dienste van de override-cascade:

  task.requires_opus → job.requested_* → product.preferred_* → kind-default

Bestaande rijen krijgen NULL (Product/ClaudeJob) of false (Task) en
vallen daarmee terug op de kind-defaults uit de resolver (ST-1298).

Migration is additief: alleen ALTER TABLE ADD COLUMN, geen RENAME of
DROP. Bestaande factories en seed-script blijven werken zonder
aanpassing omdat alle nieuwe velden default-waardes hebben.

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

* feat(PBI-67/ST-1299): job-config snapshot bij enqueue + worker-flag-runbook

T-789: Snapshot van resolved JobConfig in ClaudeJob.requested_*
bij elke job-creatie. Helper in lib/job-config-snapshot.ts laadt
product (preferred_*) en task (requires_opus) en draait de resolver
uit lib/job-config.ts (mirror van scrum4me-mcp/src/lib/job-config.ts —
zelfde matrix, sync-comment in bestand). Toegepast op alle 5
enqueue-locaties:

  - actions/user-questions.ts          (PLAN_CHAT)
  - actions/sprint-runs.ts × 3         (SPRINT_IMPLEMENTATION x2,
                                        TASK_IMPLEMENTATION loop)
  - actions/ideas.ts                   (IDEA_GRILL / IDEA_MAKE_PLAN)

Test-mocks uitgebreid met product.findUnique en task.findUnique zodat
de helper bij unit tests veilig terugvalt op kind-defaults (alle 563
tests groen).

T-790: Sectie 'Config doorgeven aan Claude Code' toegevoegd aan
docs/runbooks/worker-idempotency.md met CLI-flag-mapping en de
verwachte aanroep per kind. Forward-link naar
docs/runbooks/job-model-selection.md (volgt in T-794).

Plus: docs/plans/job-model-selection.md (de approved plan-doc).

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

* feat(PBI-67/ST-1300): cost-attribution voor thinking-tokens + admin UI

T-792: token-stats + token-history rekenen actual_thinking_tokens nu
mee in de totale kosten (tegen input-rate, conform Anthropic billing).
COALESCE-veilig zodat oude rijen 0 bijdragen i.p.v. NaN. Nieuwe export
`getTokenStatsByKind` aggregeert tokens en kosten per ClaudeJob.kind
zodat we relatieve uitgaven van IDEA_GRILL/IDEA_MAKE_PLAN/PLAN_CHAT/
TASK_IMPLEMENTATION/SPRINT_IMPLEMENTATION kunnen zien.

T-793: admin/jobs Kosten-tabel toont:
  - Nieuwe kolom 'Thinking' (aantal verbruikte thinking-tokens)
  - Mismatch-marker (rood) als requested_model afwijkt van actuele
    model_id — duidt op een worker die de CLI-flag niet doorgaf.
    Tooltip toont aangevraagd model. Geen Sentry/log-noise.

Page-level cost-berekening volgt dezelfde formule (input_price ×
thinking_tokens). 563 tests groen.

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

* docs(PBI-67/ST-1301): runbook + CLAUDE.md updates voor model/mode-selectie

T-794: Nieuwe runbook docs/runbooks/job-model-selection.md met
override-cascade, kind-default-matrix, override-voorbeelden,
auditspoor en cost-attribution-formule. 107 regels.

T-795: CLAUDE.md hardstop-bullet voor 'Model/mode per ClaudeJob'
(verwijst naar nieuwe runbook) + patterns-quickref-rij voor
job-config resolver. CLAUDE.md blijft 139 regels (≤ 150).

T-796: docs:check-links groen — 108 files, geen broken links. Twee
externe-repo verwijzingen (scrum4me-mcp/...) ge-de-linked tot plain
text omdat de check-links script de zustertree niet traverseert; de
referenties blijven leesbaar.

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

---------

Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-08 11:20:10 +02:00

185 lines
6.4 KiB
TypeScript

import { prisma } from '@/lib/prisma'
export interface SprintTokenRow {
sprintId: string
sprintCode: string
sprintGoal: string
totalTokens: number
totalCostUsd: number
jobCount: number
}
export interface DayTokenRow {
day: string
totalTokens: number
totalCostUsd: number
}
export interface PbiTokenRow {
pbiId: string
pbiCode: string
pbiTitle: string
totalTokens: number
totalCostUsd: number
}
type RawSprintRow = {
sprint_id: string
sprint_code: string
sprint_goal: string
total_tokens: bigint
total_cost: number | null
job_count: bigint
}
type RawDayRow = {
day: Date
total_tokens: bigint
total_cost: number | null
}
type RawPbiRow = {
pbi_id: string
pbi_code: string
pbi_title: string
total_tokens: bigint
total_cost: number | null
}
export async function getSprintTokenHistory(
userId: string,
productId?: string,
limit = 8,
): Promise<SprintTokenRow[]> {
const rows = productId
? await prisma.$queryRaw<RawSprintRow[]>`
SELECT
sp.id AS sprint_id,
sp.code AS sprint_code,
sp.sprint_goal,
COALESCE(SUM(cj.input_tokens + cj.output_tokens + cj.cache_read_tokens + cj.cache_write_tokens + COALESCE(cj.actual_thinking_tokens, 0)), 0) AS total_tokens,
SUM(
cj.input_tokens * mp.input_price_per_1m / 1000000.0
+ cj.output_tokens * mp.output_price_per_1m / 1000000.0
+ cj.cache_read_tokens * mp.cache_read_price_per_1m / 1000000.0
+ cj.cache_write_tokens * mp.cache_write_price_per_1m / 1000000.0
+ COALESCE(cj.actual_thinking_tokens, 0) * mp.input_price_per_1m / 1000000.0
) FILTER (WHERE cj.input_tokens IS NOT NULL) AS total_cost,
COUNT(*) FILTER (WHERE cj.input_tokens IS NOT NULL) AS job_count
FROM claude_jobs cj
JOIN tasks t ON cj.task_id = t.id
JOIN stories s ON t.story_id = s.id
JOIN sprints sp ON s.sprint_id = sp.id
LEFT JOIN model_prices mp ON mp.model_id = cj.model_id
WHERE cj.user_id = ${userId}
AND cj.status = 'DONE'
AND cj.product_id = ${productId}
GROUP BY sp.id, sp.code, sp.sprint_goal
ORDER BY sp.created_at DESC
LIMIT ${limit}
`
: await prisma.$queryRaw<RawSprintRow[]>`
SELECT
sp.id AS sprint_id,
sp.code AS sprint_code,
sp.sprint_goal,
COALESCE(SUM(cj.input_tokens + cj.output_tokens + cj.cache_read_tokens + cj.cache_write_tokens + COALESCE(cj.actual_thinking_tokens, 0)), 0) AS total_tokens,
SUM(
cj.input_tokens * mp.input_price_per_1m / 1000000.0
+ cj.output_tokens * mp.output_price_per_1m / 1000000.0
+ cj.cache_read_tokens * mp.cache_read_price_per_1m / 1000000.0
+ cj.cache_write_tokens * mp.cache_write_price_per_1m / 1000000.0
+ COALESCE(cj.actual_thinking_tokens, 0) * mp.input_price_per_1m / 1000000.0
) FILTER (WHERE cj.input_tokens IS NOT NULL) AS total_cost,
COUNT(*) FILTER (WHERE cj.input_tokens IS NOT NULL) AS job_count
FROM claude_jobs cj
JOIN tasks t ON cj.task_id = t.id
JOIN stories s ON t.story_id = s.id
JOIN sprints sp ON s.sprint_id = sp.id
LEFT JOIN model_prices mp ON mp.model_id = cj.model_id
WHERE cj.user_id = ${userId}
AND cj.status = 'DONE'
GROUP BY sp.id, sp.code, sp.sprint_goal
ORDER BY sp.created_at DESC
LIMIT ${limit}
`
return rows.map(r => ({
sprintId: r.sprint_id,
sprintCode: r.sprint_code,
sprintGoal: r.sprint_goal,
totalTokens: Number(r.total_tokens),
totalCostUsd: Number(r.total_cost ?? 0),
jobCount: Number(r.job_count),
}))
}
export async function getDayTokenData(userId: string, sprintId: string): Promise<DayTokenRow[]> {
if (!sprintId) return []
const rows = await prisma.$queryRaw<RawDayRow[]>`
SELECT
DATE(cj.finished_at) AS day,
COALESCE(SUM(cj.input_tokens + cj.output_tokens + cj.cache_read_tokens + cj.cache_write_tokens + COALESCE(cj.actual_thinking_tokens, 0)), 0) AS total_tokens,
SUM(
cj.input_tokens * mp.input_price_per_1m / 1000000.0
+ cj.output_tokens * mp.output_price_per_1m / 1000000.0
+ cj.cache_read_tokens * mp.cache_read_price_per_1m / 1000000.0
+ cj.cache_write_tokens * mp.cache_write_price_per_1m / 1000000.0
+ COALESCE(cj.actual_thinking_tokens, 0) * mp.input_price_per_1m / 1000000.0
) FILTER (WHERE cj.input_tokens IS NOT NULL) AS total_cost
FROM claude_jobs cj
JOIN tasks t ON cj.task_id = t.id
JOIN stories s ON t.story_id = s.id
LEFT JOIN model_prices mp ON mp.model_id = cj.model_id
WHERE cj.user_id = ${userId}
AND s.sprint_id = ${sprintId}
AND cj.status = 'DONE'
AND cj.finished_at IS NOT NULL
GROUP BY DATE(cj.finished_at)
ORDER BY day ASC
`
return rows.map(r => ({
day: r.day.toISOString().slice(0, 10),
totalTokens: Number(r.total_tokens),
totalCostUsd: Number(r.total_cost ?? 0),
}))
}
export async function getPbiTokenAggregates(userId: string, sprintId: string): Promise<PbiTokenRow[]> {
if (!sprintId) return []
const rows = await prisma.$queryRaw<RawPbiRow[]>`
SELECT
p.id AS pbi_id,
p.code AS pbi_code,
p.title AS pbi_title,
COALESCE(SUM(cj.input_tokens + cj.output_tokens + cj.cache_read_tokens + cj.cache_write_tokens + COALESCE(cj.actual_thinking_tokens, 0)), 0) AS total_tokens,
SUM(
cj.input_tokens * mp.input_price_per_1m / 1000000.0
+ cj.output_tokens * mp.output_price_per_1m / 1000000.0
+ cj.cache_read_tokens * mp.cache_read_price_per_1m / 1000000.0
+ cj.cache_write_tokens * mp.cache_write_price_per_1m / 1000000.0
+ COALESCE(cj.actual_thinking_tokens, 0) * mp.input_price_per_1m / 1000000.0
) FILTER (WHERE cj.input_tokens IS NOT NULL) AS total_cost
FROM claude_jobs cj
JOIN tasks t ON cj.task_id = t.id
JOIN stories s ON t.story_id = s.id
JOIN pbis p ON s.pbi_id = p.id
LEFT JOIN model_prices mp ON mp.model_id = cj.model_id
WHERE cj.user_id = ${userId}
AND s.sprint_id = ${sprintId}
AND cj.status = 'DONE'
GROUP BY p.id, p.code, p.title
ORDER BY total_cost DESC
`
return rows.map(r => ({
pbiId: r.pbi_id,
pbiCode: r.pbi_code,
pbiTitle: r.pbi_title,
totalTokens: Number(r.total_tokens),
totalCostUsd: Number(r.total_cost ?? 0),
}))
}