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
• [X] 3 - build placeholder UI
• [-] 3.5 - integrate FahamuAI API into placeholder
• [-] 4 - create UI for Q&A window that fits into current GN framework
• [ ] 5 - create CI/CD tests for new module
• [ ] 6 - 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.