Eight sub-phases per docs/ticket-analyzer-phase2-spec.md:
2.1 Schema (migration 070): analyzer_stage_executions table; source_snapshot,
aggregate_fingerprint, fingerprint_generated_at columns on analyzer_analyses.
model_traces marked LEGACY (kept for back-compat).
2.2 Every pipeline stage records a row to analyzer_stage_executions, success
or failure. Worker persists a status='failed' analyzer_analyses row when
the pipeline throws so partial stage records have a parent. Pipeline
exposes raw triage/sonnet/opus responses for downstream stages.
2.3 Stage 3 prompt updated with markdown formatting rules + banned filler
phrases. Added react-markdown + remark-gfm + @tailwindcss/typography.
New <AnalysisMarkdown> component replaces <ProseText>; coerces stray
headers to bold paragraphs.
2.4 Stage 6 fingerprint (Haiku) runs after persistence, failure-tolerant.
scripts/backfill-fingerprints.ts reconstructs Stage 6 input from the
legacy model_traces blob.
2.5 Browse UI rebuild at /analyzer/tickets: multi-select for client/issue/
queue/status/priority/assignee, sticky filter bar, active-filter chips,
bulk selection persisted via localStorage, "Analyze N selected" +
"Generate aggregate report" actions. New <MultiSelect> primitive.
Staleness uses last_activity_date > completed_at heuristic per spec C.1.
2.6 Aggregate reports (migration 071): runner is fire-and-forget, persists
SQL distributions immediately so UI shows partial state during the
Sonnet reduce call. Three endpoints, three pages (/analyzer/reports[/new
/:id]). IT Glue context fetcher capped at 200 doc titles.
2.7 Cost guards (migration 072): per-request $5 confirmation, soft-warn at
$20/day, hard-block at $50/day with ANALYZER_DAILY_COST_OVERRIDE_USERS
override. Every gating decision audited.
2.8 Runbook + build notes updated.
128 vitest tests passing, tsc clean. Migrations 070/071/072 idempotent
(IF NOT EXISTS). model_traces double-write retained — drop in a future
migration once aggregate reports have soaked.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
258 lines
8.7 KiB
TypeScript
258 lines
8.7 KiB
TypeScript
/**
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* Analyzer job worker.
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*
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* Polls `analyzer_jobs` for queued rows, runs the full pipeline, persists the
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* result, and updates the job's status / result_analysis_id throughout.
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*
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* Concurrency model: a single in-process polling loop. Multiple Next.js
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* workers will all import this module, but `claimQueuedJob()` uses
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* `FOR UPDATE SKIP LOCKED` so they cooperate at the row level — each job is
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* processed exactly once.
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*
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* Auto-start: the worker self-initializes on first server-side import in
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* production. In dev / tests, set ANALYZER_WORKER_AUTOSTART=1 to opt in.
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*/
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import {
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bulkInsertStageExecutions,
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claimQueuedJob,
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completeJob,
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failJob,
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insertAnalysis,
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insertFailedAnalysis,
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updateAnalysisFingerprint,
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updateJobStatus,
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} from './persistence';
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import { loadTicketBundle, TicketNotFoundError } from './data-access';
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import { runPipeline, type PipelineResult } from './pipeline';
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import { runFingerprintStage } from './stages/stage6-fingerprint';
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import { HAIKU } from '@/lib/services/llm/models';
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import type {
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PreprocessedTicket,
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StageExecutionRecord,
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} from '@/lib/types/analyzer';
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const POLL_INTERVAL_MS = 2_000;
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class AnalyzerWorker {
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private timer: NodeJS.Timeout | null = null;
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private running = false;
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private inFlight = false;
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async start(): Promise<void> {
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if (this.running) return;
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this.running = true;
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console.log('[ANALYZER-WORKER] starting; polling every 2s');
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this.scheduleNextPoll(0);
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}
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async stop(): Promise<void> {
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this.running = false;
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if (this.timer) {
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clearTimeout(this.timer);
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this.timer = null;
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}
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}
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private scheduleNextPoll(delay: number): void {
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if (!this.running) return;
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this.timer = setTimeout(() => {
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void this.poll();
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}, delay);
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}
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private async poll(): Promise<void> {
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if (!this.running) return;
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if (this.inFlight) {
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// Avoid overlap if a previous poll is still running.
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this.scheduleNextPoll(POLL_INTERVAL_MS);
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return;
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}
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this.inFlight = true;
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try {
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const claimed = await claimQueuedJob();
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if (claimed) {
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await this.runJob(claimed.id, claimed.ticket_number, claimed.queued_by_user_id);
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}
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} catch (err) {
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console.error('[ANALYZER-WORKER] poll error:', err);
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} finally {
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this.inFlight = false;
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this.scheduleNextPoll(POLL_INTERVAL_MS);
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}
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}
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/**
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* Process a single job end-to-end. Public so tests + manual triggers can
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* call it directly without going through the poll loop.
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*/
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async runJob(
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jobId: string,
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ticketNumber: string,
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triggeredByUserId: string | null
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): Promise<{ analysis_id: string | null; outcome: PipelineResult['outcome'] | 'failed' }> {
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// Phase 2: collect per-stage records as the pipeline runs, plus the
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// preprocessed bundle, so we can persist a failed analyzer_analyses row
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// (with source_snapshot) when a stage throws.
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const stageRecords: StageExecutionRecord[] = [];
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let capturedPre: PreprocessedTicket | null = null;
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try {
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const bundle = await loadTicketBundle(ticketNumber);
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const result = await runPipeline(
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{ bundle, force: false },
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{},
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{
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onStage: (stage) => updateJobStatus(jobId, stage),
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onStageRecord: (rec) => {
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stageRecords.push(rec);
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},
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onPreprocessed: (pre) => {
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capturedPre = pre;
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},
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}
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);
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if (result.outcome === 'idempotent_short_circuit') {
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// Point the job at the existing analysis so the UI can navigate to it.
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await completeJob(jobId, result.existing_analysis_id);
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return {
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analysis_id: result.existing_analysis_id,
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outcome: 'idempotent_short_circuit',
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};
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}
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const inserted = await insertAnalysis({
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ticket_number: result.pre.header.ticket_number,
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autotask_ticket_id: result.pre.header.autotask_ticket_id,
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content_hash: result.pre.content_hash,
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triggered_by_user_id: triggeredByUserId,
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status: 'complete',
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haiku_used: result.meta.haiku_used,
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sonnet_used: result.meta.sonnet_used,
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opus_used: result.meta.opus_used,
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total_input_tokens: result.meta.total_input_tokens,
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total_output_tokens: result.meta.total_output_tokens,
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estimated_cost_usd: result.meta.estimated_cost_usd,
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analysis: result.analysis,
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filtered_noise_count: result.filtered_noise_count,
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model_traces: result.model_traces,
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source_snapshot: result.pre.events,
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});
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// Stage 6 — fingerprint. Failure-tolerant: log and continue.
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const fpStart = new Date();
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let fpInputTokens: number | null = null;
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let fpOutputTokens: number | null = null;
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let fpOutput: unknown = {};
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let fpErr: Error | null = null;
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try {
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const fp = await runFingerprintStage({
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triage: result.triage_response,
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sonnet: result.sonnet_response,
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opus: result.opus_response,
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});
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fpInputTokens = fp.usage.input_tokens;
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fpOutputTokens = fp.usage.output_tokens;
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fpOutput = fp.data;
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await updateAnalysisFingerprint(inserted.id, fp.data);
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} catch (err) {
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fpErr = err instanceof Error ? err : new Error(String(err));
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console.warn(
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`[ANALYZER-WORKER] fingerprint failed for analysis ${inserted.id}: ${fpErr.message}`
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);
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}
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const fpEnd = new Date();
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stageRecords.push({
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stage: 'fingerprint',
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stage_order: 6,
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model_id: HAIKU,
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input_payload: {
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triage_category: result.triage_response.category,
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ticket_number: result.pre.header.ticket_number,
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opus_used: result.opus_response !== null,
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},
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output_payload: fpErr ? {} : fpOutput,
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input_tokens: fpInputTokens,
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output_tokens: fpOutputTokens,
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latency_ms: fpEnd.getTime() - fpStart.getTime(),
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started_at: fpStart,
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completed_at: fpEnd,
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error_message: fpErr ? fpErr.message : null,
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});
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await bulkInsertStageExecutions(inserted.id, stageRecords);
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await completeJob(jobId, inserted.id);
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return { analysis_id: inserted.id, outcome: 'complete' };
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} catch (err) {
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const message = err instanceof Error ? err.message : String(err);
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console.error(
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`[ANALYZER-WORKER] job ${jobId} (${ticketNumber}) failed:`,
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message
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);
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const reason =
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err instanceof TicketNotFoundError
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? `Ticket ${ticketNumber} not found in local mirror — confirm sync is current.`
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: message;
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// Phase 2: when we have a preprocessed bundle, persist a 'failed'
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// analyzer_analyses row with source_snapshot + accumulated stage rows.
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// Best-effort — if this fails we still fail the job below.
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if (capturedPre !== null) {
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const pre: PreprocessedTicket = capturedPre;
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try {
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const failedAnalysis = await insertFailedAnalysis({
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ticket_number: pre.header.ticket_number,
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autotask_ticket_id: pre.header.autotask_ticket_id,
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content_hash: pre.content_hash,
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triggered_by_user_id: triggeredByUserId,
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source_snapshot: pre.events,
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filtered_noise_count: pre.counts.filtered_noise,
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error_message: reason,
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partial_input_tokens: 0,
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partial_output_tokens: 0,
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partial_cost_usd: 0,
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haiku_used: stageRecords.some((r) => r.stage === 'triage'),
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sonnet_used: stageRecords.some((r) => r.stage === 'analyze'),
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opus_used: stageRecords.some((r) => r.stage === 'deep_review'),
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});
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await bulkInsertStageExecutions(failedAnalysis.id, stageRecords);
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} catch (persistErr) {
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console.error(
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`[ANALYZER-WORKER] failed to persist failed-analysis row for job ${jobId}:`,
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persistErr
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);
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}
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}
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await failJob(jobId, reason);
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return { analysis_id: null, outcome: 'failed' };
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}
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}
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}
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export const analyzerWorker = new AnalyzerWorker();
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/**
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* Should we auto-start the worker on import?
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* - Skip in browsers (typeof window check).
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* - Skip during vitest.
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* - Auto-start in production by default.
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* - Otherwise opt in via ANALYZER_WORKER_AUTOSTART=1.
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*/
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function shouldAutoStart(): boolean {
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if (typeof window !== 'undefined') return false;
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if (process.env.VITEST === 'true') return false;
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if (process.env.NODE_ENV === 'production') return true;
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return process.env.ANALYZER_WORKER_AUTOSTART === '1';
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}
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if (shouldAutoStart()) {
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analyzerWorker.start().catch((err) => {
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console.error('[ANALYZER-WORKER] failed to auto-start:', err);
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});
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}
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export const _WORKER_INTERNALS = { POLL_INTERVAL_MS };
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