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f9d5fa88a1
Lance now supports FTS, so add it into lancedb Python, TypeScript and Rust SDKs. For Python, we still use tantivy based FTS by default because the lance FTS index now misses some features of tantivy. For Python: - Support to create lance based FTS index - Support to specify columns for full text search (only available for lance based FTS index) For TypeScript: - Change the search method so that it can accept both string and vector - Support full text search For Rust - Support full text search The others: - Update the FTS doc BREAKING CHANGE: - for Python, this renames the attached score column of FTS from "score" to "_score", this could be a breaking change for users that rely the scores --------- Signed-off-by: BubbleCal <bubble-cal@outlook.com>
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)
- MacOS (Intel and ARM/M1/M2)
- Windows (x86_64 only)
We do not yet support musl-based Linux (such as Alpine Linux) or aarch64 Windows.
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 a more complete example.
Development
npm run build
npm run test
Running lint / format
LanceDb uses biome for linting and formatting. if you are using VSCode you will need to install the official Biome extension. To manually lint your code you can run:
npm run lint
to automatically fix all fixable issues:
npm run lint-fix
If you do not have your workspace root set to the nodejs directory, unfortunately the extension will not work. You can still run the linting and formatting commands manually.
Generating docs
npm run docs
cd ../docs
# Asssume the virtual environment was created
# python3 -m venv venv
# pip install -r requirements.txt
. ./venv/bin/activate
mkdocs build