- 14 new Code node drivers implementing the pipeline stages: normalize
candidates, build context SQL, merge context + hash, decide AI need,
prepare AI prompt, validate AI response, AI-disabled fallback, reuse
cached classification, compute score, select top 10, prepare memory/
envio records, build message/digest, compare legacy x V2, debug panel.
- Consolidated the two context queries (followups/tasks) into a single
UNION ALL query tagged by tipo, and added a "Merge - Unir Shadow"
synchronization node before comparing legacy x V2: n8n does not
guarantee relative execution order between sibling branches that only
share an early common ancestor, so cross-branch data was only safe to
read by name once a real Merge node forced both to complete first.
- Reordered score calculation before the memory upsert (score is needed
in the persisted row) and turned both Data Table writes into
side-effect branches that fan out from the main path instead of
gating it, so the Data Table node's own output shape never needs to
carry the full pipeline state forward.
- Fixed a duplicate-identifier bug in the build script: score.js's
require('./cooldown') survived inlining and collided with
cooldown.js's own computeCooldown function in the same Code node
scope. build-workflow.js now strips inter-module requires when
inlining, and a new test syntax-checks every generated jsCode string
plus asserts no leftover require() calls.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
29 lines
1.1 KiB
JavaScript
29 lines
1.1 KiB
JavaScript
// @requires context.js hash.js
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const candidatosBase = $('Code - Normalizar Candidatos Base').all().map((item) => item.json);
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const contextRows = $input.all().map((item) => item.json);
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function groupBy(rows, key) {
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const map = {};
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for (const row of rows) {
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const k = String(row[key]);
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if (!map[k]) map[k] = [];
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map[k].push(row);
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}
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return map;
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}
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const followupRows = contextRows.filter((row) => row.tipo === 'followup');
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const taskRows = contextRows.filter((row) => row.tipo === 'task');
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const followupsByTicket = groupBy(followupRows, 'tickets_id');
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const tasksByTicket = groupBy(taskRows, 'tickets_id');
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return candidatosBase.map((base) => {
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const idKey = String(base.id);
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const followups = (followupsByTicket[idKey] || []).map((f) => ({ id: f.id, date: f.date, texto: f.texto }));
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const tasks = (tasksByTicket[idKey] || []).map((t) => ({ id: t.id, date: t.date, status: t.status, texto: t.texto }));
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const ticket = normalizeTicket(base, { followups, tasks });
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const contextHash = buildContextFingerprint(ticket);
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return { json: { ticket, contextHash } };
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});
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