Re:WARC-GPT: An Open-Source Tool for Exploring Web Archives ...
by Cedricgc on Sunday June 09, 2024 @04:52PM
(#40627532)
Looking into this, could be very useful for working with personal Zotero archives of webpages
[ Parent
| on HN ]
Re:WARC-GPT: An Open-Source Tool for Exploring Web Archives ...
by jszymborski on Sunday June 09, 2024 @05:57PM
(#40627956)
As previously seen on HN:
Re:WARC-GPT: An Open-Source Tool for Exploring Web Archives ...
by szvsw on Monday June 10, 2024 @09:08AM
(#40633210)
There’s also ARIA [1]. I actually think the one linked above seems more interesting. At the same time, doesn’t seem all that different from just rolling your own solution.
Re:WARC-GPT: An Open-Source Tool for Exploring Web Archives ...
by westurner on Saturday June 15, 2024 @06:05AM
(#40688712)
paper-qa:
https://github.com/whitead/paper-qa :
> LLM Chain querying documents with citations [e.g. a scientific Zotero library]
> This is a minimal package for doing question and answering from PDFs or text files (which can be raw HTML). It strives to give very good answers, with no hallucinations, by grounding responses with in-text citations.
pip install paper-qa
> If you use Zotero to organize your personal bibliography, you can use the paperqa.contrib.ZoteroDB to query papers from your library, which relies on pyzotero. Install pyzotero to use this feature: pip install pyzotero
> If you want to use [ paperqa with pyzotero ] in an jupyter notebook or colab, you need to run the following command: import nest_asyncio
nest_asyncio.apply()
... there is also neuml/paper-ai w/ paperetl; https://news.ycombinator.com/item?id=39363115 : gh topic: pdfgpt, chatpdf,neuml/paperai has a YAML report definition schema: https://github.com/neuml/paperai :
> Semantic search and workflows for medical/scientific paper
python -m paperai.report report.yml 50 md <path to model directory>
> The following [columns and answers] report [output] formats are supported: [Markdown, CSV], Annotation - Columns and answers are extracted from articles with the results annotated over the original PDF files. Requires passing in a path with the original PDF files.