Quand le catalogue seede ne couvre pas un ingredient, l'utilisateur pouvait etre bloque (creation manuelle) ou perdre silencieusement la ligne (import). Une ligne de recette accepte desormais `placeholderName` (texte libre) au lieu de `ingredientId` : l'API cree une ligne `Ingredient` `isPlaceholder` (cle `placeholder:<uuid>`, `displayName`, `createdById`) dans la transaction de la recette, et emet `ingredient.placeholder_created`. Ces lignes sont exclues de `GET /reference/ingredients` et de `ingredient-matcher`. Front : bouton "Ajouter << ... >>" dans l'etat vide de `IngredientPicker` (formulaire + import), badge "a completer" sur la ligne, helper `ingredientLabel` applique partout ou un libelle d'ingredient est rendu. Admin : `/admin/catalog/*` (+ page `apps/admin-web`) liste les placeholders regroupes par nom normalise, "marquer traite" (`reviewedAt`) et purge des orphelins. La promotion en vraie entree catalogue reste manuelle. Migration `ingredient_placeholder` ecrite a la main (Postgres indisponible). Suites Mocha DB-backed ecrites, non executees en session ; test pur `normalizePlaceholderName` + Cypress admin-web/web verts. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
130 lines
6.2 KiB
TypeScript
130 lines
6.2 KiB
TypeScript
import { z } from "zod";
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// Shared between apps/api (server-side validation, source of truth) and
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// apps/admin-web (client-side validation for instant feedback). Same
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// rationale as schemas/auth.ts — one set of rules, French messages surfaced
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// as-is in the admin login form.
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/**
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* Payload accepted by `POST /admin/auth/login`. Deliberately its own schema
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* (not a re-export of `loginSchema`): the admin surface is a separate
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* contract from the end-user one even though the shape currently matches.
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*/
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export const adminLoginSchema = z.object({
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email: z.string().trim().toLowerCase().email("Email invalide"),
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password: z.string().min(1, "Le mot de passe est requis"),
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});
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/** Inferred TS type for {@link adminLoginSchema}'s validated output. */
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export type AdminLoginInput = z.infer<typeof adminLoginSchema>;
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/**
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* Query params for `GET /admin/metrics` — `?days=` bounds how far back the
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* time-series go (and how many daily buckets they carry). Coerced from the
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* query string; clamped to a sane window so a huge value can't make the
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* dashboard scan the whole history.
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*/
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export const getMetricsSchema = z.object({
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days: z.coerce.number().int().min(7).max(365).default(30),
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});
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/** Inferred TS type for {@link getMetricsSchema}'s validated output. */
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export type GetMetricsInput = z.infer<typeof getMetricsSchema>;
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/**
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* Payload of `POST /internal/tech-steps/heartbeat` — `services/tech-step-llm-worker`
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* (which has no inbound HTTP of its own) reporting that it's alive. Sent on
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* `boot`, on every scheduler `tick`, and after each `job` (with that job's
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* name, outcome and counts). The worker key is fixed server-side (only one
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* worker exists), so it isn't in the payload.
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*/
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export const workerHeartbeatSchema = z.object({
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event: z.enum(["boot", "tick", "job"]),
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/** The job that just ran — present only when `event === "job"`. */
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job: z.string().max(100).optional(),
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/** Whether that job succeeded — present only when `event === "job"`. */
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ok: z.boolean().optional(),
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/** Small `{ label: number }` summary of that job (e.g. `{ suggestions: 3 }`). */
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counts: z.record(z.string(), z.number()).optional(),
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});
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/** Inferred TS type for {@link workerHeartbeatSchema}'s validated output. */
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export type WorkerHeartbeatInput = z.infer<typeof workerHeartbeatSchema>;
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/** Statuses a `TechStepTrainingSuggestion` can be filtered by / set to. */
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export const TRAINING_SUGGESTION_STATUSES = ["pending", "applied", "rejected"] as const;
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/** One of {@link TRAINING_SUGGESTION_STATUSES}. */
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export type TrainingSuggestionStatus = (typeof TRAINING_SUGGESTION_STATUSES)[number];
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/** Query params for `GET /admin/tech-steps/suggestions` — every filter optional. */
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export const listSuggestionsQuerySchema = z.object({
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status: z.enum(TRAINING_SUGGESTION_STATUSES).optional(),
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sourceType: z.enum(["correction", "llm_audit"]).optional(),
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techStepKey: z.string().min(1).optional(),
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locale: z.string().min(1).optional(),
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});
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/** Inferred TS type for {@link listSuggestionsQuerySchema}. */
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export type ListSuggestionsQuery = z.infer<typeof listSuggestionsQuerySchema>;
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/** Query params for `GET /admin/tech-steps/corrections`. `consumed`/`hasCorrectedTechStep` are tri-state (omitted = no filter). */
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export const listCorrectionsQuerySchema = z.object({
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consumed: z.enum(["true", "false"]).optional(),
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hasCorrectedTechStep: z.enum(["true", "false"]).optional(),
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});
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/** Inferred TS type for {@link listCorrectionsQuerySchema}. */
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export type ListCorrectionsQuery = z.infer<typeof listCorrectionsQuerySchema>;
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/**
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* Body of `PATCH /admin/tech-steps/suggestions/:id` — curate a suggestion
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* before it feeds a `training_data.py` edit. Every field optional; at least
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* one must be present (enforced service-side).
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*/
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export const updateTrainingSuggestionSchema = z.object({
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status: z.enum(TRAINING_SUGGESTION_STATUSES).optional(),
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suggestedSynonyms: z.array(z.string().min(1)).max(200).optional(),
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suggestedUtterances: z.array(z.string().min(1)).max(200).optional(),
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});
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/** Inferred TS type for {@link updateTrainingSuggestionSchema}. */
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export type UpdateTrainingSuggestionInput = z.infer<typeof updateTrainingSuggestionSchema>;
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/**
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* Body of `POST /admin/tech-steps/retrain` — runs the F1 regression gate
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* then, if it passes, backfills every step and marks the given suggestion
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* ids. Both id lists optional (an empty run just re-gates + backfills).
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*/
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export const retrainRequestSchema = z.object({
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appliedIds: z.array(z.number().int().positive()).max(500).optional(),
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rejectedIds: z.array(z.number().int().positive()).max(500).optional(),
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});
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/** Inferred TS type for {@link retrainRequestSchema}. */
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export type RetrainRequestInput = z.infer<typeof retrainRequestSchema>;
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/** Query params for `GET /admin/tech-steps/training-data-snippet`. */
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export const trainingDataSnippetQuerySchema = z.object({
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techStepKey: z.string().min(1),
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locale: z.string().min(1).default("fr"),
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status: z.enum(TRAINING_SUGGESTION_STATUSES).default("applied"),
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});
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/** Inferred TS type for {@link trainingDataSnippetQuerySchema}. */
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export type TrainingDataSnippetQuery = z.infer<typeof trainingDataSnippetQuerySchema>;
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/**
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* Query params for `GET /admin/catalog/placeholders` — the off-catalog
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* ingredient review. `reviewed` is tri-state: omitted / `"false"` hides
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* groups every row of which has already been triaged (the default working
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* view), `"true"` shows only fully-triaged groups.
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*/
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export const listPlaceholdersQuerySchema = z.object({
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reviewed: z.enum(["true", "false"]).optional(),
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});
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/** Inferred TS type for {@link listPlaceholdersQuerySchema}. */
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export type ListPlaceholdersQuery = z.infer<typeof listPlaceholdersQuerySchema>;
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/**
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* Body of `PATCH /admin/catalog/placeholders/mark-reviewed` — stamps
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* `reviewedAt` on the given placeholder `Ingredient` ids (a maintainer has
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* seen this catalog gap and, if warranted, added the real entry by hand).
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* Bounded so one call can't sweep an unbounded set.
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*/
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export const markPlaceholdersReviewedSchema = z.object({
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ingredientIds: z.array(z.number().int().positive()).min(1).max(500),
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});
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/** Inferred TS type for {@link markPlaceholdersReviewedSchema}. */
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export type MarkPlaceholdersReviewedInput = z.infer<typeof markPlaceholdersReviewedSchema>;
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