Production-readiness cycle. Classifier was excessively conservative (real Run A: ACTIONABLE_NOW/UNASSIGNED_ACTIONABLE both 0) and made concrete semantic mistakes on real tickets: - #34419: technician "Rafael Brito" (internal) classified as WAITING_VENDOR waiting_for -- an internal technician is not a vendor. - #37389: ticket had concrete open tasks ("Realizar um inventário das máquinas", "Alinhar o dia...") but was classified INSUFFICIENT_CONTEXT. - Generic next_action ("Revisar chamado") repeated across unrelated tickets, proving nothing about real actionability. Rewrote the system prompt (n8n/nodes/prepare-ai-prompt.node.js) with: practical actionability definition ("suporte consegue fazer algo util agora", explicit inclusion list); contatar-vs-aguardar distinction with examples; WAITING_* requires positive evidence (action already taken AND external dependency still open); technician-vs-vendor distinction citing the TECNICO context field; STATUS Planejado alone != blocked/scheduled; SCHEDULED requires an explicit date/window; mandatory chronological interpretation (most recent apontamento wins over a superseded old blocker); next_action must be concrete, with explicit accepted/rejected examples; INSUFFICIENT_CONTEXT bar raised (ask "is there a diagnostic step available even without full info" first). n8n/nodes/prepare-ai-prompt.node.test.js: 10 new tests asserting each rule's text is still present in the prompt (deterministic proxy -- behavioral proof comes from the real DEV run, inspected manually). logic/classification.js: added AI_CLASSIFIER_VERSION=3 (stamped on every valid classification); added a deterministic safety net (not just a prompt hope) -- isWaitingForInternalTechnician() rejects WAITING_VENDOR when waiting_for matches the ticket's own TECNICO field, routing to a new fallback_reason 'ai_semantic_conflict' instead of accepting a known-wrong semantic classification; added next_action genericness rejection (isGenericNextAction) for ACTIONABLE_NOW/UNASSIGNED_ACTIONABLE only. n8n/nodes/validate-ai-response.node.js: now passes the ticket into validateAiClassification() so the technician guard has the facts it needs. logic/cache.js: added buildCacheKey(contextHash, classifierVersion) -> "<hash>:v<version>", stored in the same last_context_hash column (no schema migration) -- bumping AI_CLASSIFIER_VERSION now forces a cache miss on every ticket without manually clearing the Data Table. n8n/nodes/decide-needs-ai.node.js / prepare-memoria-analise-record.node.js updated to compute/persist the composite key. logic/config.js: AI_MAX_CANDIDATES default raised 30->60 (now equals CANDIDATE_POOL_SIZE) -- no candidate should go unanalyzed by an artificial cap now that Run B already proved the cache makes repeat runs cheap; AI_FALLBACK stays reserved for real provider failures. Also added SEND_ENABLED (default false) and ENVIRONMENT config fields for the real Slack send gate (used by logic/slack.js, next commit). Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
118 lines
5.2 KiB
JavaScript
118 lines
5.2 KiB
JavaScript
const VALID_CLASSIFICATIONS = [
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'ACTIONABLE_NOW', 'UNASSIGNED_ACTIONABLE', 'WAITING_REQUESTER', 'WAITING_VENDOR',
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'WAITING_APPROVAL', 'SCHEDULED', 'DEPENDENCY_BLOCKED', 'NEEDS_COORDINATION',
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'PROJECT_LONG_TERM', 'DUPLICATE_OR_OBSOLETE', 'INSUFFICIENT_CONTEXT',
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];
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// Versao do prompt/classificador. Bump manual sempre que o system prompt ou as regras de
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// validacao mudarem de forma que mudaria o julgamento da IA -- forca cache miss em TODO
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// chamado (ver logic/cache.js -> buildCacheKey), sem precisar apagar a Data Table na mao.
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const AI_CLASSIFIER_VERSION = 3;
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// O modelo, apesar do schema permitir null de verdade em blocker_type/waiting_for, as vezes
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// devolve a STRING "null" (ou variantes equivalentes) em vez do valor JSON null. Normaliza
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// aqui, na camada de validacao -- unico lugar que toca a resposta crua da IA.
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const NULL_LIKE_STRINGS = new Set(['null', 'none', 'n/a', 'na', '']);
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function normalizeNullableString(value) {
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if (value === null || value === undefined) return null;
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const trimmed = String(value).trim();
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if (NULL_LIKE_STRINGS.has(trimmed.toLowerCase())) return null;
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return trimmed;
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}
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// next_action generico nao prova acionabilidade nenhuma -- ver missao "finalizacao para
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// producao", secao 9. So se aplica a ACTIONABLE_NOW/UNASSIGNED_ACTIONABLE: nessas duas
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// classes o next_action E a evidencia de que existe um proximo passo concreto sob controle
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// do suporte; nas demais classes o campo descreve o que se espera de terceiros, entao uma
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// frase curta ("aguardar resposta") e legitima ali.
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const ACTIONABLE_CLASSES_REQUIRING_CONCRETE_NEXT_ACTION = new Set(['ACTIONABLE_NOW', 'UNASSIGNED_ACTIONABLE']);
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const GENERIC_NEXT_ACTION_PHRASES = new Set([
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'revisar chamado', 'revisar o chamado', 'dar andamento', 'dar andamento no chamado',
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'analisar situacao', 'analisar a situacao', 'verificar chamado', 'verificar o chamado',
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'acompanhar', 'acompanhar chamado', 'acompanhar o chamado',
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]);
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function normalizeForComparison(text) {
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return String(text || '')
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.trim()
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.toLowerCase()
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.normalize('NFD')
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.replace(/[̀-ͯ]/g, '') // remove acentos (combining marks) p/ comparar "situação" == "situacao"
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.replace(/[.!]+$/g, '');
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}
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function isGenericNextAction(nextAction) {
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return GENERIC_NEXT_ACTION_PHRASES.has(normalizeForComparison(nextAction));
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}
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// Guarda deterministica: tecnico interno (aparece no campo TECNICO do proprio chamado) nunca
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// pode ser tratado como fornecedor externo (WAITING_VENDOR). Ver missao "finalizacao para
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// producao", secao 6. Isso nao depende do prompt se comportar bem -- e verificado aqui.
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function isWaitingForInternalTechnician(waitingFor, ticket) {
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if (!waitingFor || !ticket || !ticket.tecnico_atribuido) return false;
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const tecnico = normalizeForComparison(ticket.tecnico_atribuido);
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const alvo = normalizeForComparison(waitingFor);
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if (!alvo || tecnico === 'sem tecnico atribuido') return false;
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return tecnico.includes(alvo);
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}
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function validateAiClassification(raw, ticket) {
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const errors = [];
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if (!raw || typeof raw !== 'object') {
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return { valid: false, data: null, errors: ['resposta nao e um objeto JSON'] };
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}
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if (!VALID_CLASSIFICATIONS.includes(raw.classification)) {
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errors.push(`classification invalida: ${raw.classification}`);
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}
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if (typeof raw.actionable_today !== 'boolean') errors.push('actionable_today deve ser boolean');
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const confidence = Number(raw.confidence);
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if (!Number.isFinite(confidence) || confidence < 0 || confidence > 1) errors.push('confidence deve estar entre 0 e 1');
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if (typeof raw.next_action !== 'string' || raw.next_action.trim().length === 0 || raw.next_action.length > 200) {
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errors.push('next_action invalido (vazio ou muito longo)');
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} else if (
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ACTIONABLE_CLASSES_REQUIRING_CONCRETE_NEXT_ACTION.has(raw.classification)
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&& isGenericNextAction(raw.next_action)
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) {
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errors.push(`next_action generico demais para ${raw.classification}: "${raw.next_action}"`);
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}
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if (raw.evidence != null && !Array.isArray(raw.evidence)) errors.push('evidence deve ser array');
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if (typeof raw.reason !== 'string') errors.push('reason deve ser string');
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const waitingFor = normalizeNullableString(raw.waiting_for);
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if (raw.classification === 'WAITING_VENDOR' && isWaitingForInternalTechnician(waitingFor, ticket)) {
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errors.push(`waiting_for ("${waitingFor}") corresponde a tecnico interno do chamado, nao pode ser WAITING_VENDOR`);
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}
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if (errors.length) return { valid: false, data: null, errors };
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return {
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valid: true,
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errors: [],
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data: {
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classification: raw.classification,
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actionable_today: raw.actionable_today,
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confidence,
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blocker_type: normalizeNullableString(raw.blocker_type),
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waiting_for: waitingFor,
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next_action: raw.next_action,
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suggested_action_type: raw.suggested_action_type ?? 'technical_action',
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business_risk: raw.business_risk ?? 'medium',
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reason: raw.reason,
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evidence: Array.isArray(raw.evidence) ? raw.evidence.slice(0, 5) : [],
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is_fallback: false,
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fallback_reason: null,
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classifier_version: AI_CLASSIFIER_VERSION,
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},
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};
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}
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module.exports = {
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VALID_CLASSIFICATIONS,
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AI_CLASSIFIER_VERSION,
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validateAiClassification,
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normalizeNullableString,
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isGenericNextAction,
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isWaitingForInternalTechnician,
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};
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