#3838th of 60 in Data and scraping for AIFor data and documents, documents and ocr, science, health and research, research and papers

grobid

Extracts structured TEI/XML from scientific PDFs, including metadata and references

Stars
5.2k
License
Apache-2.0
Last commit
Nov 2026
Last release
Aug 2026
Language
Java
Stars, last 29 weeks+456
22 Apr 2026: 4,771 stars29 Apr 2026: 4,789 stars6 May 2026: 4,809 stars13 May 2026: 4,824 stars20 May 2026: 4,852 stars27 May 2026: 4,872 stars3 Jun 2026: 4,886 stars10 Jun 2026: 4,905 stars17 Jun 2026: 4,917 stars24 Jun 2026: 4,927 stars1 Jul 2026: 4,941 stars8 Jul 2026: 4,955 stars15 Jul 2026: 4,971 stars22 Jul 2026: 4,990 stars29 Jul 2026: 5,009 stars5 Aug 2026: 5,022 stars12 Aug 2026: 5,047 stars19 Aug 2026: 5,072 stars26 Aug 2026: 5,089 stars2 Sept 2026: 5,100 stars9 Sept 2026: 5,106 stars16 Sept 2026: 5,117 stars23 Sept 2026: 5,127 stars30 Sept 2026: 5,138 stars7 Oct 2026: 5,154 stars14 Oct 2026: 5,169 stars21 Oct 2026: 5,183 stars28 Oct 2026: 5,200 stars4 Nov 2026: 5,218 stars11 Nov 2026: 5,227 stars

4,771 on 22 Apr 20265,227 on 11 Nov 2026

From GitHub's daily star counts.

Checked on GitHub.

Overview

GROBID parses scientific and technical PDFs into structured XML/TEI using a cascade of sequence-labelling models. CRF models are the default, and DeLFT deep learning models can be enabled via JEP. It extracts headers, references, citation contexts, full-text structure, funders and PDF coordinates, and exposes them through a web service, batch commands and a Java API.

Who it is for: Developers and researchers extracting metadata and text from scholarly PDFs

Strengths

  • Reference parsing around .87 F1 on a PubMed Central set with the deep learning model
  • Returns PDF bounding-box coordinates for extracted structures
  • Reported 10.6 PDF/s full-text on one 16-CPU, 32 GB machine with the Node.js client
  • Default CRF models run on commodity CPUs without a GPU

Weaknesses

  • Deep learning models are off by default and need Python/JEP, ideally a GPU
  • Windows is not currently supported
  • Aimed at scholarly PDFs, not general document-to-markdown conversion
  • Batch command lines are single-threaded; clients are needed for scale

What it needs

  • GPU optional
  • Docker
  • Needs OpenJDK 21 (source builds), Python 3.10-3.11 with JEP (deep learning models), DeLFT, pdfalto, biblio-glutton or CrossRef API (optional consolidation)
  • Models: CRF, RNN, transformers (via DeLFT)
  • port 8080

What changed

  1. 0.9.1 ↗ (opens in a new tab)Security fix

    GHSA-MGXF-7MG7-QPMF, GHSA-G2R5-4C8R-C84F, GHSA-47QP-HQVX-6R3F, GHSA-2R2C-CX56-8933, CVE-2026-54513. “Prevent command injection through crafted PDF file names in the non-server pdfalto path: the command is no longer interpolated into a bash -c string but passed as positional parameters and exec'd via…”

  2. 0.9.0 ↗ (opens in a new tab)Security fix

    “Updated Dropwizard to address Trivy vulnerability in Docker image”

  3. 0.8.2 ↗ (opens in a new tab)Security fix

    “Fixed various security vulnerabilities #1125 #1123 #1205”

From the release notes. No flag means the note does not say so, not that the upgrade is safe.

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