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* feat(agent-status): add workspace live-tasks endpoint and TaskFailureReason type Lays the API + type contract for the front-end agent presence cache: - New `GET /api/active-tasks` returns active (queued/dispatched/running) tasks plus failed tasks within the last 2 minutes for the current workspace. The 2-minute window powers a UI-side auto-clearing "Failed" agent state without back-end pollers. - `agent_task_queue` has no workspace_id column, so the query JOINs agent; `SELECT atq.*` keeps `failure_reason` (migration 055) on the wire. - Adds `TaskFailureReason` to `AgentTask` so the UI can map the 5 backend classifiers (agent_error / timeout / runtime_offline / runtime_recovery / manual) to copy without parsing free-text errors. - New `api.getActiveTasksForWorkspace()` client method; workspace is resolved server-side from the X-Workspace-Slug header (no path param, matching /api/agents and /api/runtimes conventions). Includes the joint engineering plan and designer brief that scope the broader Agent / Runtime status redesign — Phase 0 is this contract plus the front-end derivation layer landing in the next commit. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * feat(agent-status): derive presence/health states with WS sync and desktop IPC bridge Adds the front-end derivation layer that turns raw server data into the user-facing 5-state agent / 4-state runtime enums. UI files are deliberately untouched in this commit — derivation lives behind hooks (useAgentPresence, useRuntimeHealth) that any component can call with zero additional network traffic. Architecture: - Derivation is pure functions in packages/core/{agents,runtimes}; the back-end stays free of UI translation. Agents algorithm: runtime offline > recent failed (2-min window) > running > queued > available. Runtimes algorithm: status + last_seen_at -> online / recently_lost / offline / about_to_gc. - A single workspace-wide active-tasks query backs all per-agent presence reads, eliminating N+1 across hover cards, list rows, and pickers. 30-second tick re-renders the hooks so the failed window expires even when no underlying data changes. - WS task lifecycle events (dispatch / completed / failed / cancelled) invalidate active-tasks via the prefix dispatcher. completed/failed were removed from specificEvents so they go through both the prefix invalidate and the existing chat ws.on() handlers. Reconnect refetch picks up active-tasks too. - Desktop bridges window.daemonAPI.onStatusChange directly into the runtimes cache via setQueryData, giving the local daemon sub-second feedback (vs. 75s server sweep). Bridge is wsId-bound so workspace switches automatically rebind the subscription; daemon_id matching covers the same-daemon-multiple-providers case. 24 derivation unit tests cover all branches plus null/empty/boundary inputs (FAILED_WINDOW_MS edges, null last_seen_at, missing completed_at). Full core suite: 112 tests passing. Typecheck green across all 8 workspace packages. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * feat(agent-status): redesign agent runtime status as two orthogonal dimensions Splits the conflated 5-state agent presence into two independent axes: - AgentAvailability (3-state): online / unstable / offline — drives the dot indicator everywhere a dot appears. Pure runtime reachability; never sticky-red because of a past task outcome. - LastTaskState (5-state): running / completed / failed / cancelled / idle — surfaced as text + icon on focused surfaces (hover card, agent detail page, agents list, runtime detail). Never colours the dot. Major changes: * Domain layer: AgentPresence union → AgentAvailability + LastTaskState. derive-presence split into deriveAgentAvailability + deriveLastTaskState + deriveAgentPresenceDetail orchestrator. Tests reorganised into three groups (availability invariants, last-task invariants, composition). * Visual config: presenceConfig (5 entries) → availabilityConfig (3) + taskStateConfig (5). availabilityOrder + lastTaskOrder for filter chips. * Workspace-level presence prefetch: new useWorkspacePresencePrefetch hook + WorkspacePresencePrefetch mount component, wired into DashboardLayout (web) and WorkspaceRouteLayout (desktop). Hover cards render synchronously with no skeleton flash on first hover. * ActorAvatar hover: flipped default — disableHoverCard removed, enableHoverCard added (default false). Opt-in at ~14 decision-moment surfaces; pickers / decoration sub-chips stay plain. Status dot decoupled (showStatusDot prop) so picker rows can show presence without nesting popovers. * Hover cards: AgentProfileCard simplified — availability dot only, Detail link top-right (logs live on the detail page). New MemberProfileCard mirrors the structure: name + role + email + top-2 owned agents (sorted by 30d run count) with click-through to agent detail. * Agents list: split Status into two columns — availability (3-color dot + label) and Last run (task icon + label, optional running counts). Two independent filter chip groups (Status + Last run); combination acts as intersection ("online + failed" finds broken- but-alive agents). * Other UI surfaces (issue list/board/detail, comments, autopilots, projects, runtimes, mention autocomplete, subscribers picker) updated to the new dot semantics; status dot now strictly 3-color. Server changes accompany the client redesign — workspace-wide agent-task-snapshot endpoint, runtime usage queries, etc. — to feed the derive layer with the data it needs. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * refactor(agent-detail): drop last-task chip from detail header + inspector The Recent work section on the agent detail page already shows the same data (with task titles, timestamps, error context) — surfacing "Completed" / "Failed" / etc. up in the header was redundant chrome. Detail surfaces now show only the 3-state availability dot. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * fix(tables): handle narrow viewports across agents / skills / runtimes Three table layouts were squeezing content into adjacent cells at intermediate widths. Each fix is small and targeted: * runtime-list: the Runtime cell's base name had `shrink-0`, so it refused to truncate when its grid column was narrowed under width pressure — the name visually overflowed into the Health column ("ClaudeOnline" etc). Removed shrink-0, added truncate. The Health column was also a fixed 9.5rem reservation for the worst-case "Recently lost · 2m 14s ago" copy; switched to minmax(0,1fr) so it competes fairly with Runtime. * skills-page: had a single grid template with no responsive breakpoints — all 6 columns were rendered at any width and got visually jammed below md. Added a <md template that drops Source + Updated; the row markup hides those cells via `hidden md:block` / `md:contents`. * agent-list-item: the new Last run column was reserved at minmax(8rem, max-content); on narrow md viewports the 8rem floor pushed the row past available width. Changed to minmax(0,max-content) so the cell shrinks under pressure (its content already truncates). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * refactor(agent-card): hover-only Detail + add Runtime row + breathing room Three small polish tweaks to the agent hover card: - Detail link gets `mr-1` + fades in only on card hover (group-hover). It was visually flush against the popover edge and competing for attention; now it stays out of the way during a quick glance and surfaces only when the user is dwelling on the card. - Runtime row is back, in the meta block (cloud/local icon + runtime name). The earlier removal was over-aggressive — knowing where an agent runs is part of "who is this agent". The wifi badge stays dropped because the availability dot in the header already conveys reachability. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * feat(runtime): wifi-style health icon (4-state) for runtime list + agent card Replaces the 6px coloured dot with a wifi-shape icon that carries both state (Wifi vs WifiOff) and severity (success/warning/muted/destructive). Mapping: - online → Wifi (success) - recently_lost → WifiHigh (warning) — transient hiccup, fewer bars - offline → WifiOff (muted) — long unreachable - about_to_gc → WifiOff (destructive) — sweeper coming soon Used in two places: - Runtime list: replaces HealthDot in the dedicated leading-icon column. Bumped the column from 0.5rem (dot-sized) to 0.875rem (icon-sized). - Agent profile card RuntimeRow: derives runtime health from runtime + clock (matching the 4-state semantics) and renders HealthIcon next to the runtime name. Cloud runtimes always read as online. The duplicate signal with the header availability dot is intentional — it confirms WHICH runtime is the one currently in the dot's state. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
241 lines
7.4 KiB
Go
241 lines
7.4 KiB
Go
// Code generated by sqlc. DO NOT EDIT.
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// versions:
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// sqlc v1.30.0
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// source: runtime_usage.sql
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package db
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import (
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"context"
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"github.com/jackc/pgx/v5/pgtype"
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)
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const getRuntimeTaskHourlyActivity = `-- name: GetRuntimeTaskHourlyActivity :many
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SELECT EXTRACT(HOUR FROM started_at)::int AS hour, COUNT(*)::int AS count
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FROM agent_task_queue
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WHERE runtime_id = $1 AND started_at IS NOT NULL
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GROUP BY hour
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ORDER BY hour
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`
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type GetRuntimeTaskHourlyActivityRow struct {
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Hour int32 `json:"hour"`
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Count int32 `json:"count"`
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}
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func (q *Queries) GetRuntimeTaskHourlyActivity(ctx context.Context, runtimeID pgtype.UUID) ([]GetRuntimeTaskHourlyActivityRow, error) {
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rows, err := q.db.Query(ctx, getRuntimeTaskHourlyActivity, runtimeID)
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if err != nil {
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return nil, err
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}
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defer rows.Close()
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items := []GetRuntimeTaskHourlyActivityRow{}
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for rows.Next() {
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var i GetRuntimeTaskHourlyActivityRow
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if err := rows.Scan(&i.Hour, &i.Count); err != nil {
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return nil, err
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}
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items = append(items, i)
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}
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if err := rows.Err(); err != nil {
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return nil, err
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}
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return items, nil
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}
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const getRuntimeUsageByHour = `-- name: GetRuntimeUsageByHour :many
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SELECT
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EXTRACT(HOUR FROM tu.created_at)::int AS hour,
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tu.model,
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SUM(tu.input_tokens)::bigint AS input_tokens,
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SUM(tu.output_tokens)::bigint AS output_tokens,
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SUM(tu.cache_read_tokens)::bigint AS cache_read_tokens,
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SUM(tu.cache_write_tokens)::bigint AS 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.runtime_id = $1
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AND tu.created_at >= DATE_TRUNC('day', $2::timestamptz)
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GROUP BY EXTRACT(HOUR FROM tu.created_at), tu.model
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ORDER BY hour, tu.model
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`
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type GetRuntimeUsageByHourParams struct {
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RuntimeID pgtype.UUID `json:"runtime_id"`
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Since pgtype.Timestamptz `json:"since"`
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}
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type GetRuntimeUsageByHourRow struct {
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Hour int32 `json:"hour"`
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Model string `json:"model"`
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InputTokens int64 `json:"input_tokens"`
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OutputTokens int64 `json:"output_tokens"`
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CacheReadTokens int64 `json:"cache_read_tokens"`
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CacheWriteTokens int64 `json:"cache_write_tokens"`
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TaskCount int32 `json:"task_count"`
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}
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// Per-(hour, model) token aggregates (hour ∈ 0..23) for a runtime since a
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// cutoff. Powers the "By hour" tab — shows when in the day this runtime is
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// doing real work, with model preserved for client-side cost calculation
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// (same reason as ListRuntimeUsageByAgent above). Hours with zero activity
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// are omitted; the client fills the 24-bucket axis.
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func (q *Queries) GetRuntimeUsageByHour(ctx context.Context, arg GetRuntimeUsageByHourParams) ([]GetRuntimeUsageByHourRow, error) {
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rows, err := q.db.Query(ctx, getRuntimeUsageByHour, arg.RuntimeID, arg.Since)
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if err != nil {
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return nil, err
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}
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defer rows.Close()
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items := []GetRuntimeUsageByHourRow{}
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for rows.Next() {
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var i GetRuntimeUsageByHourRow
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if err := rows.Scan(
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&i.Hour,
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&i.Model,
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&i.InputTokens,
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&i.OutputTokens,
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&i.CacheReadTokens,
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&i.CacheWriteTokens,
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&i.TaskCount,
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); err != nil {
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return nil, err
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}
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items = append(items, i)
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}
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if err := rows.Err(); err != nil {
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return nil, err
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}
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return items, nil
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}
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const listRuntimeUsage = `-- name: ListRuntimeUsage :many
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SELECT
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DATE(tu.created_at) AS date,
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tu.provider,
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tu.model,
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SUM(tu.input_tokens)::bigint AS input_tokens,
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SUM(tu.output_tokens)::bigint AS output_tokens,
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SUM(tu.cache_read_tokens)::bigint AS cache_read_tokens,
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SUM(tu.cache_write_tokens)::bigint AS cache_write_tokens
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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.runtime_id = $1
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AND tu.created_at >= DATE_TRUNC('day', $2::timestamptz)
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GROUP BY DATE(tu.created_at), tu.provider, tu.model
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ORDER BY DATE(tu.created_at) DESC, tu.provider, tu.model
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`
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type ListRuntimeUsageParams struct {
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RuntimeID pgtype.UUID `json:"runtime_id"`
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Since pgtype.Timestamptz `json:"since"`
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}
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type ListRuntimeUsageRow struct {
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Date pgtype.Date `json:"date"`
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Provider string `json:"provider"`
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Model string `json:"model"`
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InputTokens int64 `json:"input_tokens"`
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OutputTokens int64 `json:"output_tokens"`
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CacheReadTokens int64 `json:"cache_read_tokens"`
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CacheWriteTokens int64 `json:"cache_write_tokens"`
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}
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// Bucket by tu.created_at (usage report time, ~= task completion time), not
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// atq.created_at (task enqueue time), so tasks that queue one day and execute
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// the next are attributed to the day tokens were actually produced. The since
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// cutoff is truncated to start-of-day so `days=N` yields full calendar days.
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func (q *Queries) ListRuntimeUsage(ctx context.Context, arg ListRuntimeUsageParams) ([]ListRuntimeUsageRow, error) {
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rows, err := q.db.Query(ctx, listRuntimeUsage, arg.RuntimeID, arg.Since)
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if err != nil {
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return nil, err
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}
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defer rows.Close()
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items := []ListRuntimeUsageRow{}
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for rows.Next() {
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var i ListRuntimeUsageRow
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if err := rows.Scan(
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&i.Date,
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&i.Provider,
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&i.Model,
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&i.InputTokens,
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&i.OutputTokens,
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&i.CacheReadTokens,
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&i.CacheWriteTokens,
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); err != nil {
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return nil, err
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}
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items = append(items, i)
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}
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if err := rows.Err(); err != nil {
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return nil, err
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}
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return items, nil
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}
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const listRuntimeUsageByAgent = `-- name: ListRuntimeUsageByAgent :many
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SELECT
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atq.agent_id,
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tu.model,
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SUM(tu.input_tokens)::bigint AS input_tokens,
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SUM(tu.output_tokens)::bigint AS output_tokens,
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SUM(tu.cache_read_tokens)::bigint AS cache_read_tokens,
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SUM(tu.cache_write_tokens)::bigint AS 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.runtime_id = $1
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AND tu.created_at >= DATE_TRUNC('day', $2::timestamptz)
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GROUP BY atq.agent_id, tu.model
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ORDER BY atq.agent_id, tu.model
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`
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type ListRuntimeUsageByAgentParams struct {
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RuntimeID pgtype.UUID `json:"runtime_id"`
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Since pgtype.Timestamptz `json:"since"`
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}
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type ListRuntimeUsageByAgentRow struct {
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AgentID pgtype.UUID `json:"agent_id"`
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Model string `json:"model"`
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InputTokens int64 `json:"input_tokens"`
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OutputTokens int64 `json:"output_tokens"`
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CacheReadTokens int64 `json:"cache_read_tokens"`
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CacheWriteTokens int64 `json:"cache_write_tokens"`
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TaskCount int32 `json:"task_count"`
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}
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// Per-(agent, model) token aggregates for a runtime since a cutoff. Powers
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// the runtime-detail "Cost by agent" tab. task_usage only carries task_id,
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// so we join the queue to expose agent_id. The model dimension is kept on
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// purpose: cost is computed client-side from a per-model pricing table, so
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// collapsing models server-side would erase the information needed to do
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// that arithmetic. The client groups by agent_id and sums cost per agent.
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func (q *Queries) ListRuntimeUsageByAgent(ctx context.Context, arg ListRuntimeUsageByAgentParams) ([]ListRuntimeUsageByAgentRow, error) {
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rows, err := q.db.Query(ctx, listRuntimeUsageByAgent, arg.RuntimeID, arg.Since)
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if err != nil {
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return nil, err
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}
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defer rows.Close()
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items := []ListRuntimeUsageByAgentRow{}
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for rows.Next() {
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var i ListRuntimeUsageByAgentRow
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if err := rows.Scan(
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&i.AgentID,
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&i.Model,
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&i.InputTokens,
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&i.OutputTokens,
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&i.CacheReadTokens,
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&i.CacheWriteTokens,
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&i.TaskCount,
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); err != nil {
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return nil, err
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}
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items = append(items, i)
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}
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if err := rows.Err(); err != nil {
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return nil, err
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}
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return items, nil
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}
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