// The search service of a deployment whose vectors backend has no vector store (no Qdrant linked,
// no explicit pgvector choice). It is not a fake: it is the honest answer of such a deployment.
// Readiness says `unavailable` with the reason a person can act on; an index job fails its row with
// the stable `vector_store_unavailable` code instead of retrying forever; a search or a removal is
// refused with a typed problem. Nothing is written anywhere, so choosing a store later (enabling
// document AI links a managed Qdrant) starts from a clean state.

import { AppError } from "@conusai-kit/core"
import type { KnowledgeSearchService } from "../core/ports.js"

function unavailable(reason: string): AppError {
  return new AppError({
    type: "/problems/runtime_unavailable",
    title: "The knowledge search service is unavailable",
    status: 503,
    code: "runtime_unavailable",
    detail: reason,
  })
}

export function unavailableKnowledgeSearch(reason: string): KnowledgeSearchService {
  return {
    async readiness() {
      return { state: "unavailable", reasons: [reason] }
    },

    async index() {
      // A permanent failure: the row records why, and a retry of the same job cannot succeed until
      // the deployment binds a store (a new deployment, which re-runs the job).
      throw Object.assign(new Error(reason), { permanent: "vector_store_unavailable" })
    },

    async search() {
      throw unavailable(reason)
    },

    async remove() {
      throw unavailable(reason)
    },
  }
}