paperai
science-parse
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paperai | science-parse | |
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19 | 1 | |
1,196 | 570 | |
3.3% | 2.1% | |
5.9 | 0.0 | |
5 months ago | 9 months ago | |
Python | Java | |
Apache License 2.0 | Apache License 2.0 |
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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
science-parse
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Seeking Advice: How to extract Abstract from scientific journals (.pdfs) 10k+.
Just use science-parse or GROBID. They have been designed for that exact reason.
What are some alternatives?
txtai - đź’ˇ All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows
grobid - A machine learning software for extracting information from scholarly documents
tika-python - Tika-Python is a Python binding to the Apache Tika™ REST services allowing Tika to be called natively in the Python community.
paperetl - 📄 ⚙️ ETL processes for medical and scientific papers
SciencePlots - Matplotlib styles for scientific plotting
sentence-transformers - Multilingual Sentence & Image Embeddings with BERT
faiss - A library for efficient similarity search and clustering of dense vectors.
scibert - A BERT model for scientific text.
covasim - COVID-19 Agent-based Simulator (Covasim): a model for exploring coronavirus dynamics and interventions
tldrstory - đź“Š Semantic search for headlines and story text