paperai
tika-python
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paperai | tika-python | |
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19 | 4 | |
1,194 | 1,411 | |
3.1% | - | |
5.9 | 2.2 | |
5 months ago | 11 days ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
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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.
paperai
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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.
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Build Personal ChatGPT Using Your Data
https://github.com/neuml/paperai
Disclaimer: I am the author of both
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[P] Parse research papers into structured data
paperai | paperetl
- Show HN: Semantic search and workflows for medical/scientific papers
- Semantic search and workflows for medical/scientific papers
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# Run txtai in native code
action: translate input: txtai executes machine-learning workflows to transform data and build AI-powered semantic search applications. output: txtai exécute des workflows d'apprentissage automatique pour transformer les données et construire des applications de recherche sémantique alimentées par l'IA. action: translate input: Traditional search systems use keywords to find data output: Les systèmes de recherche traditionnels utilisent des mots-clés pour trouver des données action: summary input: https://github.com/neuml/txtai output: txtai executes machine-learning workflows to transform data and build AI-powered semantic search applications. Semantic search applications have an understanding of natural language and identify results that have the same meaning, not necessarily the same keywords. API bindings for JavaScript, Java, Rust and Go. Cloud-native architecture scales out with container orchestration systems (e. g. Kubernetes) action: summary input: https://github.com/neuml/paperai output: paperai is an AI-powered literature discovery and review engine for medical/scientific papers. Paperai was used to analyze the COVID-19 Open Research Dataset (CORD-19) paperai and NeuML have been recognized in the following articles: Cord-19 Kaggle Challenge Awards Machine-Learning Experts Delve Into 47,000 Papers on Coronavirus Family. real 0m22.478s user 0m13.776s sys 0m3.218s
tika-python
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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.
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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!
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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.
What are some alternatives?
txtai - đź’ˇ All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows
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
sentence-transformers - Multilingual Sentence & Image Embeddings with BERT
layout-parser - A Unified Toolkit for Deep Learning Based Document Image Analysis
faiss - A library for efficient similarity search and clustering of dense vectors.
py-pdf-parser - A Python tool to help extracting information from structured PDFs.
scibert - A BERT model for scientific text.
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.
science-parse - Science Parse parses scientific papers (in PDF form) and returns them in structured form.
paperetl - 📄 ⚙️ ETL processes for medical and scientific papers