Skip to main content

Documentation Index

Fetch the complete documentation index at: https://docs.pixeltable.com/llms.txt

Use this file to discover all available pages before exploring further.

​
Overview

Build and share multimodal AI datasets without managing infrastructure. Work with your images, videos, audio, and documents through a unified Python API - process them with AI models, create embeddings, and publish your results for team collaboration or public research.

​
Quick Start

Requirements: Pixeltable >= 0.4.24 Replicate a dataset: 
import pixeltable as pxt

coco_copy = pxt.replicate(
    remote_uri='pxt://pixeltable:fiftyone/coco_mini_2017',
    local_path='coco-copy'
)
Replicas are read-only locally, but you can query them, perform similarity searches, update them with pull(), or create independent copies. Publish your datasets (requires account and API key from pixeltable.com): 
pxt.publish(
    source='my-table',
    destination_uri='pxt://username/my-dataset'
)
After publishing, use push() to update the cloud replica with local changes. Access defaults to private; add access='public' to make it publicly accessible. Learn more in the Data Sharing Guide.

​
Resources

Discord

Get real-time help from our community

GitHub

Report issues and contribute code

Docs

Browse our documentation

Office Hours

Schedule time with our team
Last modified on May 1, 2026