d64b1132b9dfb906f27dc7bd883d24b787df3e41
8
Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
  GustavoandClaude Sonnet 5
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abc690ddb7 |
feat(v2): real Slack send pipeline (guard, idempotency, success/failure registration)
Implements the actual send branch: Selecionar Top N -> Montar Mensagem ->
Guard de Envio -> Slack real -> registrar resultado (only after
confirmed success/failure) -- previously simulated/absent.
logic/slack.js (new): shouldSendByConfig (SEND_ENABLED gate, defaults
false), computeMessageHash (djb2Hash of the exact message text, reused
from logic/hash.js), alreadySentSuccessfully (idempotency check: only a
prior status='success' record for the same report_date+run_type+
message_hash blocks a resend -- a prior 'failed' record does not, so
retries after a real failure aren't stuck), evaluateSendGuard (single
auditable decision combining both), buildEnvioDigestRecord.
logic/slack.test.js: 13 tests covering all of the above, explicitly
labeled against the mission's required tests #13-#16.
New node drivers:
- guard-envio-slack.node.js: reads the digest + recent envio records
(fetched by report_date), computes the send decision.
- Slack node itself (n8n-nodes-base.slack, native, not a raw webhook):
reuses the real "Slack account" credential (slackApi) and
$vars.SLACK_CHANNEL_TECNICO channel variable already used by this
org's own "Notificacao de Erros Globais" workflow on the same n8n
instance -- V1's own Slack webhook URL was never actually deployed
(its Config value is literally "SEU/WEBHOOK/AQUI", same class of
placeholder as the old GLPI URL from the prior cycle), so this reuses
the one REAL, credentialed Slack mechanism that exists in this
environment rather than inventing a new destination. onError:
continueErrorOutput splits success/failure into two branches.
- registrar-envio-sucesso.node.js / registrar-envio-falha.node.js: build
the success/failure record; only the success path continues to the
existing per-ticket send-counter logic (rewired below).
- lancar-erro-envio.node.js: after the failure record is written,
explicitly throws so the n8n execution shows status=error (never
silently swallow a send failure).
- pular-envio.node.js: terminal no-op for the "should not send" branch
(SEND_ENABLED=false or already sent today), for observability only.
n8n/nodes/prepare-envio-record.node.js: rewired to read the Top10
selection by name ($('Code - Selecionar Top 10').all()) instead of
$input, since it now runs downstream of the Slack-success registration,
not directly off Selecionar Top10 -- registering per-ticket send counts
before Slack ever confirmed anything was the exact "don't register
before confirmation" bug the mission called out.
logic/message.test.js: added a full-Top10 message-length regression test
(mission requirement: message stays short, no leaked JSON/score/evidence).
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
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GustavoandClaude Sonnet 5
|
482b7ef48e |
fix(v2): redefine AI actionability semantics + version the classifier (AI_CLASSIFIER_VERSION)
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> |
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GustavoandClaude Sonnet 5
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edecd271b9 |
fix(v2): fix missing transitive dependency (normalize.js) in 3 node drivers
Found while syncing this cycle's fixes to the live DEV workflow and
preparing Run A: tools/build-workflow.js's readLogicSource() only inlines
whatever a node's own `@requires` header lists -- it does not resolve
transitive dependencies. context.js started doing `require('./normalize')`
earlier this cycle, but the three node drivers that need normalizeTicket/
buildAiContextText (which call normalizeGlpiText internally) still only
declared `@requires context.js`, never `normalize.js` itself.
The result compiles fine (new Function(...) syntax-checks pass -- a
ReferenceError is a runtime error, not a syntax error) but would throw
"normalizeGlpiText is not defined" the moment any of these three nodes
actually ran:
- Code - Mesclar Contexto e Calcular Hash (merge-context-hash.node.js)
- Code - Normalizar Candidatos Base (normalize-candidates.node.js)
- Code - Preparar Prompt IA (prepare-ai-prompt.node.js)
This never surfaced in Run 1 (prior session) because normalize.js/the
descricao field didn't exist yet at that point, and it didn't surface in
this cycle's local test suite because node--test only exercises the pure
logic/*.js modules directly (with real requires), never the inlined,
concatenated jsCode a node actually runs in n8n.
Fixed by adding normalize.js explicitly to each of the three headers,
matching the codebase's existing convention for multi-file deps (e.g.
compute-score.node.js already lists `@requires cooldown.js score.js`
together instead of relying on any transitive resolution).
Added a regression test that scans every generated Code node for calls to
normalizeGlpiText/normalizeTicket/buildAiContextText and asserts the
normalizeGlpiText function definition is actually present in that same
inlined source -- would have caught this before it ever reached DEV.
102/102 tests passing (was 101/101 -- +1 new regression test).
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
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GustavoandClaude Sonnet 5
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3c87ab55e1 |
fix(v2): fix cache is_fallback bug, wire observability + data quality, drop debug webhook, fix GLPI URL
- Real bug found by code review while implementing this cycle: "Code - Reusar Classificacao em Cache" always hardcoded is_fallback: false when reconstructing a classification from memory, even when the cached classification was itself AI_FALLBACK. On a cache hit for a previously fallback-classified ticket, this would have let it skip applyFallbackPolicy's exclusion entirely (the policy checks aiClassification.is_fallback first). Fixed to derive is_fallback from the cached ai_classification value. - select-top10.node.js now carries `resolucao` (ia | cache | fallback_cap) through to the scored item, previously dropped -- needed to tell cache hits apart from real AI calls in observability. - Code - Comparar Legacy x V2 now computes the full observability summary (candidate_count, cache_hits/misses, ai_requested/success/errors, ai_fallback_count and by-reason breakdown, classification_counts, insufficient_context_count, actionable_real_count, critical_override_count, top10_count, blocked_count, coordination_count) and the data-quality review (buildDataQualityReview over INSUFFICIENT_CONTEXT tickets), both stored in the shadow_runs `summary` JSON column -- no new Data Table needed. - Removed the debug webhook entirely (Debug - Ver Painel, Data Table - Buscar Shadow Runs Recentes debug branch, Code - Montar Painel Debug, Debug - Responder) and the now-unused debug-panel.node.js driver. Workflow went from 37 to 33 nodes. Debugging goes through n8n execution data, the Data Tables, and the shadow diff instead, as requested. - Fixed glpi_base_url: was still V1's own placeholder (https://glpi.suaempresa.com.br, never a real value, not report anonymization) -- confirmed the real domain (https://glpi.gtigrupo.com.br) from the live, active GLPI x WhatsApp workflow's own GLPI API config in the same n8n instance. SQL still only ever receives it through {GLPI_BASE_URL} substitution from the Config node, never hardcoded. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com> |
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GustavoandClaude Sonnet 5
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00a42db269 |
fix(v2): AI_FALLBACK replaces the ACTIONABLE_NOW-with-confidence-0 lie, normalize null-like strings
Fallback (ai_disabled, ai_error, invalid_json, ai_max_candidates_cap -- any candidate the AI never actually analyzed) now produces classification 'AI_FALLBACK', an explicit technical state that is never part of the 11-class enum sent to OpenAI (the AI itself can never legitimately return it). Previously it silently claimed ACTIONABLE_NOW with confidence 0, which made unanalyzed tickets indistinguishable from genuinely confirmed ones at the classification-label level. Also normalizes blocker_type/waiting_for when the model returns the literal string "null"/"none"/"n/a"/"" instead of JSON null -- done once, in the validation layer (logic/classification.js), not scattered around the workflow. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com> |
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GustavoandClaude Sonnet 5
|
ea105d525c |
fix(v2): three real bugs found by an actual end-to-end run against production GLPI data
Ran the deployed workflow for real (temporary webhook trigger, briefly
activated, immediately deactivated and removed after each attempt) against
the real GLPI MySQL database and a real OpenAI credential. Found and fixed:
1. $env access is blocked on this n8n instance (N8N_BLOCK_ENV_ACCESS_IN_NODE).
parseConfig($env) threw "access to env vars denied" on the very first
Code node. Config now comes from the "Config - Coordenador GLPI v2" Set
node instead (same pattern the V1 workflow already used) -- expanded
that node with all 13 tunable parameters, and pointed the 3 affected
node drivers (build-sql-candidatos, decide-needs-ai, select-top10) at
it instead of $env.
2. Data Table "upsert" operation requires both `columns` (values) and a
separate `filters` (match condition) -- I had only set columns with
matchingColumns, which isn't enough; n8n refused to activate the
workflow ("Missing or invalid required parameters: filters"). Added
filters.conditions matching on ticket_id to both memory-writing Data
Table nodes.
3. Real architecture bug: "Data Table - Buscar Memoria" sat inline in the
41-candidate chain (Mesclar Contexto -> Buscar Memoria -> Decidir
Necessidade de IA). A bulk "get all rows" Data Table node run with 41
input items produced 41 identical fetches and its OWN output (the empty
memory table on a first run) replaced the 41 candidates entirely --
"Decidir Necessidade de IA" received 0 items and the whole main branch
silently skipped. Moved the memory fetch to a parallel branch off
Config (fires once) and added a real Merge node ("Merge - Aguardar
Memoria") to guarantee both the candidates and the memory rows have
executed before "Decidir Necessidade de IA" runs -- same synchronization
pattern already used for context and for the shadow comparison.
Also fixed a cosmetic bug found in the real message output: buildTopMessage
produced a quadruple newline between the header and the first ticket block
([header, '', ...blocks].join('\n\n') double-counts the blank line already
inserted by the '\n\n' join). Added a regression test.
Verified with a real execution (id 13599, 24/08/2026 19:25 UTC) against the
live GLPI database: 41 real candidates, 30 sent to OpenAI (capped), 11
fallback-capped, memory table populated with 41 real rows including
genuine WAITING_VENDOR/WAITING_REQUESTER classifications with real
blocker_type/waiting_for fields extracted from real ticket task content,
and a real shadow_runs row comparing Legacy x V2 (4 tickets removed by V2:
2 for INSUFFICIENT_CONTEXT, 1 WAITING_REQUESTER, 1 WAITING_VENDOR; 4 added).
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
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GustavoandClaude Sonnet 5
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a99a25cb1a |
feat(v2): complete n8n workflow template (36 nodes) covering full V2 pipeline + shadow branch
- 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>
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GustavoandClaude Sonnet 5
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00bb89f4f4 |
feat(v2): candidate pool SQL (admin exclusion preserved, no hard LIMIT 10) + verbatim legacy SQL for shadow mode
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com> |