Files
lancedb/docs/src/basic_legacy.ts
2024-07-22 10:26:49 -07:00

127 lines
3.1 KiB
TypeScript

// --8<-- [start:import]
import * as lancedb from "vectordb";
import {
Schema,
Field,
Float32,
FixedSizeList,
Int32,
Float16,
} from "apache-arrow";
import * as arrow from "apache-arrow";
// --8<-- [end:import]
import * as fs from "fs";
import { Table as ArrowTable, Utf8 } from "apache-arrow";
const example = async () => {
fs.rmSync("data/sample-lancedb", { recursive: true, force: true });
// --8<-- [start:open_db]
const lancedb = require("vectordb");
const uri = "data/sample-lancedb";
const db = await lancedb.connect(uri);
// --8<-- [end:open_db]
// --8<-- [start:create_table]
const tbl = await db.createTable(
"myTable",
[
{ vector: [3.1, 4.1], item: "foo", price: 10.0 },
{ vector: [5.9, 26.5], item: "bar", price: 20.0 },
],
{ writeMode: lancedb.WriteMode.Overwrite },
);
// --8<-- [end:create_table]
{
// --8<-- [start:create_table_with_schema]
const schema = new arrow.Schema([
new arrow.Field(
"vector",
new arrow.FixedSizeList(
2,
new arrow.Field("item", new arrow.Float32(), true),
),
),
new arrow.Field("item", new arrow.Utf8(), true),
new arrow.Field("price", new arrow.Float32(), true),
]);
const data = [
{ vector: [3.1, 4.1], item: "foo", price: 10.0 },
{ vector: [5.9, 26.5], item: "bar", price: 20.0 },
];
const tbl = await db.createTable({
name: "myTableWithSchema",
data,
schema,
});
// --8<-- [end:create_table_with_schema]
}
// --8<-- [start:add]
const newData = Array.from({ length: 500 }, (_, i) => ({
vector: [i, i + 1],
item: "fizz",
price: i * 0.1,
}));
await tbl.add(newData);
// --8<-- [end:add]
// --8<-- [start:create_index]
await tbl.createIndex({
type: "ivf_pq",
num_partitions: 2,
num_sub_vectors: 2,
});
// --8<-- [end:create_index]
// --8<-- [start:create_empty_table]
const schema = new arrow.Schema([
new arrow.Field("id", new arrow.Int32()),
new arrow.Field("name", new arrow.Utf8()),
]);
const empty_tbl = await db.createTable({ name: "empty_table", schema });
// --8<-- [end:create_empty_table]
{
// --8<-- [start:create_f16_table]
const dim = 16;
const total = 10;
const schema = new Schema([
new Field("id", new Int32()),
new Field(
"vector",
new FixedSizeList(dim, new Field("item", new Float16(), true)),
false,
),
]);
const data = lancedb.makeArrowTable(
Array.from(Array(total), (_, i) => ({
id: i,
vector: Array.from(Array(dim), Math.random),
})),
{ schema },
);
const table = await db.createTable("f16_tbl", data);
// --8<-- [end:create_f16_table]
}
// --8<-- [start:search]
const query = await tbl.search([100, 100]).limit(2).execute();
// --8<-- [end:search]
console.log(query);
// --8<-- [start:delete]
await tbl.delete('item = "fizz"');
// --8<-- [end:delete]
// --8<-- [start:drop_table]
await db.dropTable("myTable");
// --8<-- [end:drop_table]
};
async function main() {
await example();
console.log("Basic example: done");
}
main();