Tier 1: chat quality — fuzzy aliases, reply templates, dedup, rewriter

Foco: matar repetición y adaptar respuestas. Los handlers tenían ~30 strings
hardcodeadas (3-7 lugares cada una). Aliases hacían substring exacto.

- pg_trgm + GIN indexes en product_aliases / alias_product_mappings.
  Captura plurales, diminutivos, typos sin reglas. catalogRetrieval re-busca
  el snapshot con normalized_alias cuando el query original no rinde
  (vasio→vacio→Vacío).
- reply_templates table + replyTemplates.js. 20 keys, 2-3 variantes c/u
  con DEFAULTS hardcodeados como fallback. pickVariant excluye las usadas
  en context.recent_replies (FIFO cap 8). Wired en idle/cart/cartHelpers/
  shipping/payment/waiting.
- failed_searches counter en context. count>=3 escala via humanFallback.
  Reset en cada add_to_cart exitoso.
- storeContext.js: vars derivadas de getStoreConfig (delivery_zones, hours,
  zonas) listas para inyectar en templates cuando los datos se carguen.
- replyRewriter.js: LLM call opcional (REPLY_REWRITER=1) que adapta el
  template al hilo conversacional. 1.5s timeout, fallback al template puro.
  Sólo activo en 8 slots semánticamente importantes.
- 12 unit tests para replyTemplates (rotation, recency, FIFO, vars).
  208 tests totales pasando.

Plan completo: ~/.claude/plans/ok-creo-que-tiene-humming-sutton.md

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
Lucas Tettamanti
2026-05-01 19:29:02 -03:00
parent 525679cf8b
commit f784ddd62d
17 changed files with 1347 additions and 308 deletions

View File

@@ -535,32 +535,57 @@ export async function getDecryptedTenantEcommerceConfig({
return rows[0] || null;
}
export async function searchProductAliases({ tenant_id, q = "", limit = 20 }) {
export async function searchProductAliases({ tenant_id, q = "", limit = 20, threshold = 0.3 }) {
const lim = Math.max(1, Math.min(200, parseInt(limit, 10) || 20));
const query = String(q || "").trim();
if (!query) return [];
const normalized = query.toLowerCase();
const like = `%${query}%`;
const nlike = `%${normalized}%`;
const sql = `
select tenant_id, alias, normalized_alias, woo_product_id, category_hint, boost, metadata, updated_at
select tenant_id, alias, normalized_alias, woo_product_id, category_hint, boost, metadata, updated_at,
greatest(similarity(alias, $2), similarity(normalized_alias, $3)) as sim
from product_aliases
where tenant_id=$1
and (alias ilike $2 or normalized_alias ilike $3)
order by boost desc, updated_at desc
where tenant_id = $1
and (alias % $2 or normalized_alias % $3)
order by sim desc, boost desc, updated_at desc
limit $4
`;
const { rows } = await pool.query(sql, [tenant_id, like, nlike, lim]);
return rows.map((r) => ({
tenant_id: r.tenant_id,
alias: r.alias,
normalized_alias: r.normalized_alias,
woo_product_id: r.woo_product_id,
category_hint: r.category_hint,
boost: r.boost,
metadata: r.metadata,
updated_at: r.updated_at,
}));
const { rows } = await pool.query(sql, [tenant_id, query, normalized, lim]);
return rows
.filter((r) => Number(r.sim) >= threshold)
.map((r) => ({
tenant_id: r.tenant_id,
alias: r.alias,
normalized_alias: r.normalized_alias,
woo_product_id: r.woo_product_id,
category_hint: r.category_hint,
boost: r.boost,
metadata: r.metadata,
updated_at: r.updated_at,
similarity: Number(r.sim),
}));
}
export async function searchAliasProductMappings({ tenant_id, q = "", limit = 50, threshold = 0.3 }) {
const lim = Math.max(1, Math.min(200, parseInt(limit, 10) || 50));
const query = String(q || "").trim();
if (!query) return [];
const normalized = query.toLowerCase();
const sql = `
select alias, woo_product_id, score, similarity(alias, $2) as sim
from alias_product_mappings
where tenant_id = $1 and alias % $2
order by sim desc, score desc
limit $3
`;
const { rows } = await pool.query(sql, [tenant_id, normalized, lim]);
return rows
.filter((r) => Number(r.sim) >= threshold)
.map((r) => ({
alias: r.alias,
woo_product_id: Number(r.woo_product_id),
score: Number(r.score || 1),
similarity: Number(r.sim),
}));
}
export async function getRecoRules({ tenant_id }) {