Skip to main content

Tool to extract and store sentence embeddings to a fast and scalable vector db

Project description

sentence_store

A tool to extract and store sentence embeddings to a fast and scalable vector db

Install:

pip3 install sentence_store

Usage:

from sentence_store.main import Embedder
 e = Embedder(cache_name='embedder_test')
    sents = [
        "The dog barks to the moon",
        "The cat sits on the mat",
        "The phone rings",
        "The rocket explodes",
        "The cat and the dog sleep"
    ]
    e.store(sents)
    q = 'Who sleeps on the mat?'
    rs = e(q, 2)
    for r in rs: print(r)

    print('TIMES:', e.times)
    return True

Enjoy, Paul Tarau

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

sentence_store-0.4.2.tar.gz (4.7 kB view details)

Uploaded Source

File details

Details for the file sentence_store-0.4.2.tar.gz.

File metadata

  • Download URL: sentence_store-0.4.2.tar.gz
  • Upload date:
  • Size: 4.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.6

File hashes

Hashes for sentence_store-0.4.2.tar.gz
Algorithm Hash digest
SHA256 96480802322b905de4fa21e1094a952023d4c10ce5f0871821a920b2843b019d
MD5 3a6bae35e35b34818559adacdb2cbcd3
BLAKE2b-256 429ec380f22d603b6e67d8642392518e0849b251202ead8b68ff849fe6f1845e

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page