Suriyakumarvijayanayagam
72907dae74
POST /v1/mob/scan/lookup label + customer → catalogue match, sizes, and
every registered store that sells it with live
stock, in-stock first / nearest first, one
recommended
POST /v1/mob/scan/confirm chosen store + size + qty → re-read the ledger;
ok, or the next-nearest store with enough of the
same product
GET /v1/mob/scan/stores registered stores nearest first
Recognition is pgvector cosine search over every brand_* table (each
with its own index, merged) plus a word match that settles near-ties
and works alone when no model is configured. The embedder is chosen by
EMBEDDING_PROVIDER (OpenAI-compatible or Gemini) and must be the model
that indexed the catalogue: verified 2026-09-15 as all-MiniLM-L6-v2 over
search_query, served by the cluster's Ollama as `all-minilm`; the first
search refuses a width mismatch by name.
Customer, stores and catalogue are read concurrently under a 5 s cap; a
slow model degrades to a text answer. Vectors and ranked hits are cached
in Redis and in-process; live stock never is. Availability uses the same
rules as the customer catalogue (approve, publishedat, ledger balance,
outlet price else retail). No stock reservation: confirm re-reads.
scratch/cataloguedims reports the catalogue's embedding width and fill.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
18 lines
471 B
Go
18 lines
471 B
Go
package routes
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import (
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"nearle/facade"
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"github.com/gofiber/fiber/v2"
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)
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// Scan-to-order, customer app only. See controllers/scanController.go for
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// the three calls and services/scanService.go for the pipeline behind them.
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func RegisterScanRoutes(api fiber.Router, f *facade.Facade) {
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scan := api.Group("/v1/mob/scan")
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scan.Post("/lookup", f.ScanController.Lookup)
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scan.Post("/confirm", f.ScanController.Confirm)
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scan.Get("/stores", f.ScanController.Stores)
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}
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