mirror of
https://github.com/lancedb/lancedb.git
synced 2026-08-15 02:28:38 +00:00
Yang Cen
9dc5ec03aa
## What changed - add `block_size` to Python FTS configuration and the deprecated local/remote helpers - add `blockSize` to the TypeScript FTS options and propagate it through the NAPI binding - serialize the value as `block_size` for remote index creation - document the existing Rust builder API and generate the TypeScript API reference - add local, remote, metadata, search, and invalid-value regression coverage ## Why Lance supports configuring the number of documents per compressed FTS posting block, but LanceDB's Python and TypeScript APIs did not expose the setting. This made the experimental FTS V3 layout unavailable through those clients and allowed the value to be dropped before index creation. ## How it works The default remains `128`. Supported values are `128` and `256`; selecting `256` uses the experimental FTS V3 format. Invalid values are rejected by the Lance builder and surfaced as Python or JavaScript errors. ## Validation - `cargo check --quiet --features remote --tests --examples` - `cargo +1.94.0 clippy --quiet --features remote --tests --examples -- -D warnings` - targeted Rust local and remote index tests - Rust doctests: 34 passed - Python Ruff checks, doctest, and targeted local/remote tests: 5 passed - TypeScript build, Biome lint, generated docs, and targeted Jest tests: 9 passed - `git diff --check` ## Limitations The Java client remains unchanged because its external remote REST model does not currently expose `block_size`. Co-authored-by: Yang Cen <yangcen@Yangs-Mac-mini.local>
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.