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lancedb-gatefixer[bot]
2deccf21cf
## Summary - normalize Python snake_case and TypeScript camelCase embedding metadata - use the normalized metadata for schema validation and embedding lookup - cover appending through `Table.add()` with a Python-authored schema fixture ## Root cause Python writes embedding source and vector column names as `source_column` and `vector_column`, but the TypeScript SDK only read `sourceColumn` and `vectorColumn`. The missing source name reached the add path as `undefined`, preventing JavaScript rows from being embedded and appended. ## Validation - `pnpm lint` - `pnpm test __test__/embedding.test.ts __test__/arrow.test.ts __test__/registry.test.ts --runInBand` (201 passed, 1 skipped) - `pnpm build` - `pnpm run docs` Fixes #1289 <!-- lance-gatekeeper-fix:v1 agent=b71c18a5e33d26f4d138972e91d34e66 generation=1 --> --------- Co-authored-by: Gatefixer <313497061+lancedb-gatefixer[bot]@users.noreply.github.com> Co-authored-by: Xuanwo <github@xuanwo.io>
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.