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`nprobes(0)` bypassed the validation used by the minimum and maximum probe setters, allowing zero into query requests and producing inconsistent local and remote results. Sync Python could additionally interpret the zero maximum as an unbounded search. Reject zero in the Rust vector-query builder and propagate its input error through the Python vector/hybrid and Node bindings. Validate nonpositive counts in the sync Python vector and hybrid builders so every SDK and backend reports `nprobes must be greater than 0` before execution. Update the Rust examples and document the positive-count requirement. Regression tests cover local and remote vector/hybrid builders, rejection before remote query requests, promised TypeScript query vectors, and positive counts replacing both probe bounds. Validation: - Rust probe regression tests: 2 passed. - Focused Python query, remote, hybrid, and serialization tests: 22 passed. The four sync regression cases fail with the original setters. - Focused TypeScript indexed local and mocked remote tests: 2 passed. - Workspace `cargo check --features remote --tests --examples` and Clippy passed. - Rust formatting, Python formatting/lint, and TypeScript build/lint/docs passed. Repository-wide `ruff check .` reports 29 existing errors in unchanged CI scripts; `ruff check python` passes. Fixes #4388 BREAKING CHANGE: Rust `VectorQuery::nprobes` now returns `Result<Self>` instead of `Self`; callers must handle the result, as with the existing minimum/maximum probe setters. <!-- lance-gatekeeper-fix:v1 agent=e92fda5a212c7f9e80fa55e7b4e4634d generation=1 --> Co-authored-by: Gatefixer <313497061+lancedb-gatefixer[bot]@users.noreply.github.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 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.