paperai
paper-qa
paperai | paper-qa | |
---|---|---|
19 | 10 | |
1,198 | 3,616 | |
1.3% | - | |
5.9 | 8.7 | |
5 months ago | 4 days ago | |
Python | Python | |
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
paper-qa
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Oracle of Zotero: LLM QA of Your Research Library
Why does this post link to a renamed fork of Paper-QA (https://github.com/whitead/paper-qa) which has made zero changes and is 19 commits behind the original?
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[P] A Large Language Model for Healthcare | NHS-LLM and OpenGPT
To be honest, I'm not too sure about this part, and think that it is probably not the best approach to have the model itself generate references. I prefer the approach used in e.g. paperqa, but wanted to explore both options.
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Looking for a paper summarizer
I’ve come across Paper QA (github page) and as a graduate student I loved the idea that when I do literature review and find tons of papers I can just ask the AI to find the info I’m looking for in the paper. However, this service requires OpenAI API key, which I’ve acquired but turns out it’s a paid service. Free key doesn’t get me anything. Is there a service/software like this that is free? Or something that I can host on my PC instead of using people’s servers so it’s cheaper/free?
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ChatPDF – Chat with Any PDF
I tried it [1] a lot, but I must say it confuses me most of the time and I need to read the original text to check if it makes sense. Lots of times it doesn't.
[1] https://github.com/whitead/paper-qa
- Alternatives to Pinecone? (Vector databases) [D]
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DIY natural language processing - How to start, techniques guidance
Have a look at this: https://github.com/whitead/paper-qa
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Show HN: Document Q&A with GPT: web, .pdf, .docx, etc.
1: We are finding out. Someone else mentioned: https://github.com/whitead/paper-qa We're hoping to keep our service be accessible and easy to use, and add features. Such as from your other questions...
2: We are thinking of the website integration. Do you think OpenAI may release this too? Questions received by email is a new idea that sounds interesting!
3: Thanks for the suggestion – we will look into it.
- GitHub - whitead/paper-qa: LLM Chain for answering questions from documents with citations
- Paper QA: LLM Chain for answering questions from documents with citations
What are some alternatives?
txtai - 💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows
vault-ai - OP Vault ChatGPT: Give ChatGPT long-term memory using the OP Stack (OpenAI + Pinecone Vector Database). Upload your own custom knowledge base files (PDF, txt, epub, etc) using a simple React frontend.
tika-python - Tika-Python is a Python binding to the Apache Tikaâ„¢ REST services allowing Tika to be called natively in the Python community.
simple-llm-finetuner - Simple UI for LLM Model Finetuning
SciencePlots - Matplotlib styles for scientific plotting
gpt4-pdf-chatbot-langchain - GPT4 & LangChain Chatbot for large PDF docs
sentence-transformers - Multilingual Sentence & Image Embeddings with BERT
langchain - âš¡ Building applications with LLMs through composability âš¡ [Moved to: https://github.com/langchain-ai/langchain]
faiss - A library for efficient similarity search and clustering of dense vectors.
google-research - Google Research
scibert - A BERT model for scientific text.
OpenGPT - A framework for creating grounded instruction based datasets and training conversational domain expert Large Language Models (LLMs).