const fs = require('fs');
const _ = require('lodash')
const Typesense = require('typesense')

const { load, cut } = require('@node-rs/jieba');
const { log } = require('console');

load()

const txt = fs.readFileSync('./5.txt', 'utf8')

const databaseName123 = 'okaytest123'

const client = new Typesense.Client({
  'nodes': [{
    'host': 'localhost',
    'port': '8108',
    'protocol': 'http'
  }],
  'apiKey': 'xyz',
  'connectionTimeoutSeconds': 300
})

const schema = {
  'name': databaseName123,
  'fields': [
    { name: 'title', type: 'string', locale: 'zh' },
    { name: 'text', type: 'string' },

    {
      name: 'embedding',
      type: 'float[]',
      embed: {
        from: [
          'title',
        ],
        model_config: {
          model_name: 'ts/all-MiniLM-L12-v2'
        }
      }
    }
  ]
}

;(async function () {
  try {
    await client.collections(databaseName123).delete()
  } catch {

  }

  try {
    await client.collections().create(schema)
  } catch (ex) {
    console.log(ex)
  }

  const text = cut(txt).join(' ')

  fs.writeFileSync('./cut.txt', text)

  try {
    await client.collections(databaseName123).documents().import([
      { id: '1', title: txt, text },
    ])
  } catch (ex) {
    console.log(ex)
  }

  const resp = await client.collections(databaseName123).documents().search({
    q: `孔明`,
    // query_by: 'embedding,title',
    query_by: 'text',
    // query_by: 'title',
    pre_segmented_query: true,
    // drop_tokens_threshold: 0, typo_tokens_threshold: 0, prefix: false
    // sort_by: '_vector_distance:desc'
  }).catch(console.log)

  // const result = _.map(resp.hits, (item) => {
  //   console.log(JSON.stringify(item.highlights, null, 2))
  //   // return {
  //   //   title: item.document.title,
  //   //   tags: item.document.tags,
  //   //   distance: item.vector_distance,
  //   // }
  // })

  console.log(JSON.stringify(resp, null, 2))
  // console.log(JSON.stringify(resp, null, 2))

  // console.log(await client.collections().retrieve())
} ())