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lancedb-gatefixer[bot]
c18aa7b033
Renaming or dropping an embedding source or vector column leaves schema metadata pointing at missing fields, causing later `add()` calls to fail. Reject these operations in local schema evolution before committing any changes. The guard reads Python/Node embedding column metadata and native Rust `lancedb::column_definitions` without loading embedding models. It supports explicit and default Rust vector-column names and respects quoted column paths. Unrelated column changes and nullability updates remain supported. The restriction is documented in the Python, Rust, and TypeScript APIs. Regression coverage includes both SDK metadata formats, native Rust definitions with explicit and default destinations, atomic rejection of batched changes, and continued embedding generation after reopening. Fixes #4763 Validation at the exact PR head and GitHub test-merge: - Hosted macOS Python wheel suite: 3061 passed, 162 skipped, 70 deselected, including all 8 sync and 4 async embedding schema-evolution cases. - Hosted Windows Rust suite: 1900 library tests passed, 8 embedding integration tests passed, and 107 doctests passed, including the native explicit/default destination and binding guard cases. - Hosted Linux Python 3.10 rerun: 3084 passed, 159 skipped, 50 deselected; the previously observed remote-fork timeout passed on the replacement job. - All 10 applicable exact-head workflow runs completed successfully. The existing main-only Windows ARM job was skipped by its workflow condition.
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.