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Will JonesandClaude Opus 5
65e9a4b873
An embedder can extend the SQL dialect with its own statements, but has had nowhere to say what a statement *is*: its grammar, the label it reports to an audit log, and the access it needs are three separate facts, and describing them separately means a host ends up with parallel downcast chains that must be kept in step by hand. Adding a statement to only two of the three is a silent gap rather than a compile error. `lancedb::sql` gains the seam that keeps them together: - `CustomSqlHandler` contributes a grammar; `route_custom_sql` picks the one that owns a statement and leaves the rest to DataFusion. - `SqlStatement` pairs a planned node with its audit label and the `AccessRequirement`s it needs. The vocabulary names what is reached for -- read, write, own, create, database, namespace, system -- rather than a privilege, so no access-control model has to live in the dialect. - `StatementRegistry` holds both, with the consultation order it is given. Registration is front-insertion so an extension can get ahead of a catch-all that would otherwise swallow its keyword. - `WriteObserver` reports a committed write without the statement knowing how its host represents that. - `DmlResult` carries what a DML statement did as a one-row batch. The feature adds no dependency that is not already required, so it is on by default; the flag is there so an embedder that does not want the surface can opt out. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.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.