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-0.0.93.tar.gz (84.2 kB view details)

Uploaded Source

Built Distribution

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

retab-0.0.93-py3-none-any.whl (97.5 kB view details)

Uploaded Python 3

File details

Details for the file retab-0.0.93.tar.gz.

File metadata

  • Download URL: retab-0.0.93.tar.gz
  • Upload date:
  • Size: 84.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.7

File hashes

Hashes for retab-0.0.93.tar.gz
Algorithm Hash digest
SHA256 d29dcc795a4e3d3f48158d32b497a9f5938693f0512f448784460a050ef63551
MD5 f0edc6ccb43153a7819fce8295c9e244
BLAKE2b-256 df9afee8373656a874b6f4431ee7acb73abd716ac26c1cc52e61abde1d9c5ccc

See more details on using hashes here.

File details

Details for the file retab-0.0.93-py3-none-any.whl.

File metadata

  • Download URL: retab-0.0.93-py3-none-any.whl
  • Upload date:
  • Size: 97.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.7

File hashes

Hashes for retab-0.0.93-py3-none-any.whl
Algorithm Hash digest
SHA256 4e8e62d357cb4813aae0b20e4bf6407fddf3c6291106182d69794371567a9848
MD5 666c20147c8182be5ea28dccf19e6227
BLAKE2b-256 c4174f3316b52cbe223b598c4c2c069dce58322fc0c3b6eeb5000669461cf132

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