> ## Documentation Index
> Fetch the complete documentation index at: https://docs.mirage.strukto.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# LanceDB

> Set up a LanceDB connection for the LanceDB resource.

LanceDB mounts a 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.

## Connection

### Local / embedded

Point `uri` at a directory. LanceDB stores the table there, no server needed.

```bash theme={null}
# .env.development
LANCEDB_URI=/data/fashion.lancedb
```

### Object storage

`uri` also accepts `s3://`, `gs://`, and `az://` prefixes for tables backed by
object storage.

### Cloud and Enterprise

`db://` URIs connect to LanceDB Cloud (`api_key` + `region`) or Enterprise
(`api_key` + `host_override`):

```bash theme={null}
# .env.development
LANCEDB_URI=db://my-database
LANCEDB_API_KEY=sk_...
LANCEDB_REGION=us-east-1
# Enterprise only
LANCEDB_HOST_OVERRIDE=https://my-database.us-east-1.api.lancedb.com
```

## Search

Search is the `search "<query>" <path>` command. It returns ranked rows as their
canonical `<id>.md` file paths plus a score, so results compose with `cat`, `wc`,
and pipes (`grep`/`rg` stay lexical). It requires a table built with an embedding
function on a source field, so `tbl.search(text)` auto-embeds the query.

## Limits

The resource is read-only and bounds how much an agent can pull:

* `search_limit` (10): default top-k returned by `search`.
* `max_rows` (1,000): hard ceiling on rows listed per folder.

See the [Python](/python/resource/lancedb) and [TypeScript](/typescript/setup/lancedb)
resource pages for full config.