Skip to main content

Retab official python library

Project description

Retab

Retab Logo

The AI Automation Platform

Made with love by the team at Retab 🤍.

Our Website | Documentation | Discord | Twitter


What is Retab?

Retab solves all the major challenges in document processing with Large Language Models:

  1. Universal Document Preprocessing: Convert any file type (PDFs, Excel, emails, etc.) into LLM-ready format without writing custom parsers
  2. Structured, Schema-driven Extraction: Get consistent, reliable outputs using schema-based prompt engineering
  3. Processors: Publish a live, stable, shareable document processor.
  4. Automations: Create document processing workflows that can be triggered by events (mailbox, upload link, endpoint, outlook plugin).
  5. Projects: Evaluate the performance of models against annotated datasets
  6. Optimizations: Identify the most used processors and help you finetune models to reduce costs and improve performance

We are offering you all the software-defined primitives to build your own document processing solutions. We see it as Stripe for document processing.

Our goal is to make the process of analyzing documents and unstructured data as easy and transparent as possible.

A new, lighter paradigm Large Language Models collapse entire layers of legacy OCR pipelines into a single, elegant abstraction. When a model can read, reason, and structure text natively, we no longer need brittle heuristics, handcrafted parsers, or heavyweight ETL jobs. Instead, we can expose a small, principled API: "give me the document, tell me the schema, and get back structured truth." Complexity evaporates, reliability rises, speed follows, and costs fall—because every component you remove is one that can no longer break. LLM‑first design lets us focus less on plumbing and more on the questions we actually want answered.

Many people haven't yet realized how powerful LLMs have become at document processing tasks - we're here to help unlock these capabilities.


Go further


Code examples

You can check our Github repository to see code examples: python examples and jupyter notebooks.

Community

Let's create the future of document processing together!

Join our discord community to share tips, discuss best practices, and showcase what you build. Or just tweet at us.

We can't wait to see how you'll use Retab.


Roadmap

We share our roadmap publicly on Github

Among the features we're working on:

  • Node.js SDK
  • Schema optimization autopilot
  • Sources API

Project details


Release history Release notifications | RSS feed

Download files

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

Source Distribution

retab-0.0.119.tar.gz (114.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

retab-0.0.119-py3-none-any.whl (127.1 kB view details)

Uploaded Python 3

File details

Details for the file retab-0.0.119.tar.gz.

File metadata

  • Download URL: retab-0.0.119.tar.gz
  • Upload date:
  • Size: 114.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.7

File hashes

Hashes for retab-0.0.119.tar.gz
Algorithm Hash digest
SHA256 72e46bb3db315e4cfc0a69897e33684f20543ae0f9b559b7c9396e1370a9d39c
MD5 25bad8bc5c36f02cf8b9384f72ef4c5d
BLAKE2b-256 7154c679a0f97fa164936c6da098138f6d7c4254d0bb5921b80aa8369b9a3d54

See more details on using hashes here.

File details

Details for the file retab-0.0.119-py3-none-any.whl.

File metadata

  • Download URL: retab-0.0.119-py3-none-any.whl
  • Upload date:
  • Size: 127.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.7

File hashes

Hashes for retab-0.0.119-py3-none-any.whl
Algorithm Hash digest
SHA256 6edd9cb23db09adbd9e59e365849ed40e91c447877a24a877817d9aa2a4c1724
MD5 44b326588094363b6289d866432b29f6
BLAKE2b-256 67390f3c2f4690ca55ef7c86ed3f3cfba2d62480cad2e8ae7136e908a23b016d

See more details on using hashes here.

Supported by

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