tika-python
paperetl
tika-python | paperetl | |
---|---|---|
4 | 12 | |
1,420 | 316 | |
- | 4.4% | |
2.2 | 6.3 | |
26 days ago | 5 months ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
tika-python
-
Document Parsing - an unsolved problem?
At my previous job we had the same problem which we solved by using Tika. We called it on the server along with other stuff, but there is also a Python binding.
-
Extract text from PDF
Tika is from Apache so yes its original code base is Java but it has bindings in other languages. Checkout Tika-Python!
-
Extract text from documents
The Textractor instance is the main entrypoint for extracting text. This method is backed by Apache Tika, a robust text extraction library written in Java. Apache Tika has support for a large number of file formats: PDF, Word, Excel, HTML and others. The Python Tika package automatically installs Tika and starts a local REST API instance used to read extracted data.
paperetl
- Show HN: Open-source Rule-based PDF parser for RAG
-
Oracle of Zotero: LLM QA of Your Research Library
Nice project!
I've spent quite a lot of time in the medical/scientific literature space. With regards to LLMs, specifically RAG, how the data is chunked is quite important. With that, I have a couple projects that might be beneficial additions.
paperetl (https://github.com/neuml/paperetl) - supports parsing arXiv, PubMed and integrates with GROBID to handle parsing metadata and text from arbitrary papers.
paperai (https://github.com/neuml/paperai) - builds embeddings databases of medical/scientific papers. Supports LLM prompting, semantic workflows and vector search. Built with txtai (https://github.com/neuml/txtai).
While arbitrary chunking/splitting can work, I've found that integrating parsing that has knowledge of medical/scientific paper structure increases the overall accuracy and experience of downstream applications.
-
[P] Parse research papers into structured data
paperai | paperetl
- Parse research papers into a structured dataset
- ETL for medical and scientific papers
- Show HN: ETL for Medical and Scientific Papers
-
Seeking Advice: How to extract Abstract from scientific journals (.pdfs) 10k+.
paperai and paperetl are a set of projects to consider for this task.
- paperetl: ETL processes for medical and scientific papers
What are some alternatives?
EasyOCR - Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.
SciencePlots - Matplotlib styles for scientific plotting
txtai - π‘ All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows
ciscoconfparse - Parse, Audit, Query, Build, and Modify Cisco IOS-style configurations.
layout-parser - A Unified Toolkit for Deep Learning Based Document Image Analysis
paperai - π π€ Semantic search and workflows for medical/scientific papers
py-pdf-parser - A Python tool to help extracting information from structured PDFs.
rdm - Our regulatory documentation manager. Streamlines 62304, 14971, and 510(k) documentation for software projects.
contextualized-topic-models - A python package to run contextualized topic modeling. CTMs combine contextualized embeddings (e.g., BERT) with topic models to get coherent topics. Published at EACL and ACL 2021.
dagster - An orchestration platform for the development, production, and observation of data assets.
science-parse - Science Parse parses scientific papers (in PDF form) and returns them in structured form.