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8373318e89
Adds an FM-Index — a scalar index over string and binary columns that
accelerates substring search (`contains(col, 'needle')`), distinct from
the tokenized `FTS` index — across the Rust core and the Python and
TypeScript bindings.
## Rust
- `Index::Fm(FmIndexBuilder)` and `IndexType::Fm`.
- `make_index_params` maps `Index::Fm` to Lance's
`ScalarIndexParams::for_builtin(BuiltinIndexType::Fm)`.
- `supported_fm_data_type` validates
`Utf8`/`LargeUtf8`/`Binary`/`LargeBinary` columns.
- `list_indices` round-trips the type (`"Fm"` → `IndexType::Fm`); the
remote wire type is `"FM"`.
## Python
Adds `lancedb.index.Fm`, accepted by `create_index`:
```python
from lancedb.index import Fm
await tbl.create_index("text", config=Fm())
```
## TypeScript
Adds the `Index.fm()` factory:
```ts
await tbl.createIndex("text", { config: Index.fm() });
```
LanceDB JavaScript SDK
A JavaScript library for LanceDB.
Installation
npm install @lancedb/lancedb
This will download the appropriate native library for your platform. We currently support:
- Linux (x86_64 and aarch64 on glibc and musl)
- MacOS (Intel and ARM/M1/M2)
- Windows (x86_64 and aarch64)
Usage
Basic Example
import * as lancedb from "@lancedb/lancedb";
const db = await lancedb.connect("data/sample-lancedb");
const table = await db.createTable("my_table", [
{ id: 1, vector: [0.1, 1.0], item: "foo", price: 10.0 },
{ id: 2, vector: [3.9, 0.5], item: "bar", price: 20.0 },
]);
const results = await table.vectorSearch([0.1, 0.3]).limit(20).toArray();
console.log(results);
The quickstart contains more complete examples.
Development
See CONTRIBUTING.md for information on how to contribute to LanceDB.