iframe-proxy | Sunbelt Computer Software

History

44 lines (37 loc) · 1.36 KB

Raw

import { CohereClient } from 'cohere-ai';

import pg from 'pg';

import pgvector from 'pgvector/pg';

const client = new pg.Client({database: 'pgvector_example'});

await client.connect();

await client.query('CREATE EXTENSION IF NOT EXISTS vector');

await pgvector.registerTypes(client);

await client.query('DROP TABLE IF EXISTS documents');

await client.query('CREATE TABLE documents (id bigserial PRIMARY KEY, content text, embedding bit(1536))');

async function embed(texts, inputType) {

const cohere = new CohereClient();

const response = await cohere.embed({

texts: texts,

model: 'embed-v4.0',

inputType: inputType,

embeddingTypes: ['ubinary']

});

return response.embeddings.ubinary.map((e) => {

return e.map((v) => v.toString(2).padStart(8, '0')).join('')

});

}

const input = [

'The dog is barking',

'The cat is purring',

'The bear is growling'

];

const embeddings = await embed(input, 'search_document');

for (let [i, content] of input.entries()) {

await client.query('INSERT INTO documents (content, embedding) VALUES ($1, $2)', [content, embeddings[i]]);

}

const query = 'forest';

const queryEmbedding = (await embed([query], 'search_query'))[0];

const { rows } = await client.query('SELECT content FROM documents ORDER BY embedding <~> $1 LIMIT 5', [queryEmbedding]);

for (let row of rows) {

console.log(row.content);

}

await client.end();

Sunbelt Computer Software

PL/B Language Development and Support

Navigation Menu

Uh oh!

Sunbelt Computer Software

PL/B Language Development and Support

Uh oh!

FilesExpand file tree

example.js

Latest commit

History

example.js

File metadata and controls