// Schema for the {{projectName}} AI backend.
//
// Tables are auto-discovered: every exported `table(...)` in this file
// (or any `*.entity.ts` / `*.schema.ts` file) is registered by
// `voltro dev` — no manual barrel. `actors` + `tenants` are the
// framework's core tables: the built-in `audit()` / `tenant()` /
// `softDelete()` mixins reference them, so they must be declared (the
// CLI wires them into the mixin registry once it finds them).
//
// The agent thread tables (`agent_threads`, `agent_messages`) are
// auto-provided + auto-migrated by the framework because this app ships
// an `*.agent.tsx` — you do NOT declare them here.

import {
  databaseHandle,
  id,
  table,
  text,
  vectorEmbedding,
  type InferRow,
} from '@voltro/database'

// ---------- Core tables (required by the audit / tenant mixins) ----------

export const actors = table('actors', {
  id:          id(),
  kind:        text().oneOf(['user', 'serviceAccount', 'apiKey', 'system']),
  displayName: text().nullable(),
})

export const tenants = table('tenants', {
  id:   id(),
  name: text(),
})

// ---------- Knowledge base ----------
//
// `vectorEmbedding({ from: 'body', ... })` adds an `embedding` vector
// column + an HNSW index over it, and registers a re-embed hook that
// calls `@voltro/ai`'s `embed` on every insert/update of `body` — so a
// plain `ctx.store.insert('docs', { title, body })` auto-embeds, no app
// code. Query it with `database.docs.nearestNeighbours(queryString, k)`
// (the string overload is valid because this table carries the mixin —
// the runtime embeds the query string before searching).
//
// `dimensions` MUST match the model's output width. 1536 =
// text-embedding-3-small (OpenAI). If you point AI_MODEL at a different
// embedding model, change this to match (e.g. 768 / 3072) or the vector
// width won't line up.
export const docs = table('docs', {
  id:    id({ prefix: 'doc' }),
  title: text(),
  body:  text(),
})
  .with(
    vectorEmbedding({
      from:       'body',
      model:      'text-embedding-3-small',
      dimensions: 1536,
    }),
  )

export type Doc = InferRow<typeof docs>

export const database = databaseHandle({ actors, tenants, docs })