Artificial Intelligence Tools for Knowledge-Intensive Tasks (AIKIT)
################################################################################ Author: Darrell O. Ricke, Ph.D. (mailto: Darrell.Ricke@ll.mit.edu) Copyright: Copyright (c) 2024 Massachusetts Institute of Technology License: GNU GPL license (http://www.gnu.org/licenses/gpl.html)
RAMS request ID 1028310
DISTRIBUTION STATEMENT A. Approved for public release. Distribution is unlimited. This material is based upon work supported by the Department of the Air Force under Air Force Contract No. FA8702-15-D-0001. Any opinions, findings, conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the Department of the Air Force.
© 2024 Massachusetts Institute of Technology.
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Summary
This is the Artificial Intelligence Tools for Knoledge-Intensive Tasks (AIKIT) system. AIKIT is packaged as both Docker and Singularity containers. AIKIT includes Large Language Models (LLM), LangChain, Jupyter notebooks, Retrieval-Augmented Generation (RAG), and Ruby-on-Rails web interface.
Singularity
To build:
Update the AIKIT_UI/Gemfile for the 3.0.2 version of Ruby by commenting out the Docker version and uncommenting the 3.0.2 version.
tar -cf AIKIT_UI.tar AIKIT_UI
singularity build aikit.sif aikit.def
-or-
apptainer build aikit.sif aikit.def
Singularity AIKIT Rails interface example:
Place LLM models in io/hub
singularity run --nv -B io/:/io/ aikit.sif "rails s -b 0.0.0.0"
-or-
apptainer run --nv -B io/:/io/ aikit.sif "rails s -b 0.0.0.0"
AIKIT web interface on port 3000 on hosting server
Docker
To build:
docker build . -t aikit:latest
To run:
Place LLM models in io/hub
./docker_up.cmds
AIKIT web interface on port 3000 on hosting server