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# Large Language Models (LLMs) & Metadata
* assigned: soloshelby, priscilla
* contact: bonfacem
* keywords: gnsoc, LLMs, metadata
## Integrate an LLM Q&A system into gn.genenetwork.org
This development will be done in stages:
* [X] 1 - get API access to FahamuAI GeneNetwork Q&A system
* [X] 2 - create local python Flask sandbox
* [-] 3 - create UI for Q&A window that fits into current GN framework
* [ ] 4 - create CI/CD tests for new module
* [ ] 5 - integrate new functionality into GN1 & GN2
## Add GN metadata
* [ ] export GN RDF triples
* [ ] convert data of triples into plain English sentences
* [ ] submit triples-based sentences to Q&A LLM
* [ ] submit RDF metadata to an Oracle to support Q&A system truthfulness
## Set up system update protocol
These are all living systems that must be kept up-to-date.
GN is consistently being used for research and we are improving its design and functionality to make this statement perpetually true.
In order to keep the Q&A system up-to-date we must:
* [ ] create protocol to get new publications
* [ ] query web for new publications utilizing GN
* [ ] pull links to the newly found documents
* [ ] acquire the documents
* [ ] process documents for LLM
The National Library of Medicine's PubMed is a National Institute of Health system that is one of the most widely used resources for researchers found
PubMed is consistently updated by the NIH, so we must build a script to:
* [ ] poll its API on a regular basis
* [ ] download new citations,
* [ ] parse citations and metadata for input into LLM
* [ ] upload new data into LLM
By ensuring up-to-date information about the main information sources for the GeneNetwork Q&A system, the system grows with the knowledgebase.
Add functionality that allows someone to submit documentation to the system, which is added after being reviewed by a specialist.
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