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LanceDBResource exposes a LanceDB table as a read-only filesystem: group-by columns become nested folders, each row is a card plus an optional blob file, and semantic search is the search command. The TypeScript backend mirrors the Python one and returns identical results.

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Node

pnpm add @struktoai/mirage-node @lancedb/lancedb

import { LanceDBResource, MountMode, Workspace } from '@struktoai/mirage-node'

const fashion = new LanceDBResource({
  config: {
    uri: '/data/fashion.lancedb', // or s3://, gs://, db:// (LanceDB Cloud)
    table: 'fashion',
    groupBy: ['gender', 'articleType', 'baseColour'],
    idColumn: 'id',
    titleColumn: 'productDisplayName',
    blobColumn: 'image_bytes',
    blobExt: 'jpg',
    vectorColumn: 'vector', // presence enables the search command
    searchLimit: 5,
  },
})

const ws = new Workspace({ '/fashion/': fashion }, { mode: MountMode.READ })

await ws.execute('ls /fashion/Men/Shoes/White')
await ws.execute('search "red running shoes" /fashion') // ranked paths + score + card

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Filesystem layout

/fashion/<gender>/<articleType>/<baseColour>/<id>.md   # row card
/fashion/<gender>/<articleType>/<baseColour>/<id>.jpg  # raw blob bytes
Semantic search is the search command, not a path: it returns ranked rows as the canonical <id>.md paths above, annotated with the vector distance.

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Cloud and Enterprise

db:// URIs connect to LanceDB Cloud (apiKey + region) or Enterprise (apiKey + hostOverride): 
const fashion = new LanceDBResource({
  config: {
    uri: 'db://my-database',
    apiKey: process.env.LANCEDB_API_KEY,
    region: 'us-east-1',
    hostOverride: 'https://my-database.us-east-1.api.lancedb.com', // Enterprise only
    table: 'fashion',
    groupBy: ['gender'],
    idColumn: 'id',
    vectorColumn: 'vector',
  },
})

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Supported commands

ls, cd, tree, cat, stat, find, wc, and search. grep/rg stay lexical; search "<query>" <path> is the semantic command, returning ranked rows as canonical <id>.md paths plus a score, so results compose with cat, wc, and pipes. Flags: --top-k, --threshold, --method semantic. Search requires a table built with an embedding function on a source field, so tbl.search(text) auto-embeds the query. The Node example under examples/typescript/lancedb/ builds such a table and produces the same output as the Python example, including identical similarity scores (0.2679).