import { createClient } from 'embedbase-js'
const embedbase = createClient('https://api.embedbase.xyz', '<grab me here https://app.embedbase.xyz/>')
const ads = [
    'Discover Harem Pants! Unique, stylish bohemian vibes with a dropped crotch & loose legs. Comfy meets chic - elevate your wardrobe. Limited stock - shop now!.',
    'Introducing our fabulous Fringe Skirt! Step out in style with eye-catching fringe detailing that adds flair and movement. Perfect for any occasion, create unforgettable memories with this chic piece.',
    'Introducing the Gingham Dress: Timeless & Chic! 💕 Step into summer with this must-have, two-toned checkered dress. From picnics to parties, it\'s your go-to look. Shop now for unbeatable style!',
]
const datasetId = 'product-ads'
const data = await embedbase.dataset(datasetId).batchAdd(ads.map((data) => ({ data })))
console.log(data)

[
  {
    id: '9ced909f95e08e71a08bf6729be33dedc6793258c011989d5da9dd67b257509e',
    status: 'success'
  },
  {
    id: '2fd991008424b2eb0354b040cd65ca1b8dc4deae941ec3c0abe6987ab6b2c7d1',
    status: 'success'
  },
  {
    id: '4dcba3c9311b76cf90b9cc4bf68e1524802e7345e6ec20de73941b86f53a5e33',
    status: 'success'
  }
]

import { Configuration, OpenAIApi } from 'openai'
const question = 'im looking for a nice pant that is comfortable and i can both use for work and for climbing'
const context = await embedbase.dataset(datasetId).createContext(question)
const prompt = 
    `Based on the following context:\n${context}\nAnswer the user's question: ${question}`
const configuration = new Configuration({
  apiKey: process.env.OPENAI_API_KEY,
})
const openai = new OpenAIApi(configuration);
const completion = await openai.createChatCompletion({
    model: 'gpt-3.5-turbo',
    messages: [{ role: 'user', content: prompt }],
})
console.log(completion.data.choices[0].message?.content)

You might want to try our Harem Pants! They have a dropped crotch and loose legs for comfort,
and their unique bohemian style can elevate your wardrobe for work.
However, please note that they may not be the most suitable for climbing.

npm i embedbase-js