Installing the new Go-based Fabric LLM cli

Fabric’s installation instructions from its website make it appear that installing this new version rewritten in the Go language should be easier than it was with the original Python implementation.

Although pipx made things relatively easy before, I ran into trouble when my installed version of Go did not meet the requirements of the newer Fabric package.

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# Old Python-based implementation
# git clone https://github.com/danielmiessler/fabric.git && # Clone Fabric to your computer
# 	pushd fabric &&
# 	pipx install . &&
# 	exec zsh && fabric --help

# New go version
# Install Fabric directly from the repo

go install github.com/daniel/miessler/fabric@latest

My solution was to try out PKGX which was something that I had been looking for an excuse to try.

Run Large Language Models Locally With *ollama.ai's* Docker Image

ollama is an open-source framework for self-hosting large language models (LLM) similar to ChatGPT or Google’s Bard. The official Docker image makes it painless to host any number of the supported models.

Shell script to get an Ollama model running #

The example “run_ollama_container.sh” script(s) below take the LLM model name as an argument (assigned to $LLMMODEL), but the pull and run docker exec commands can be called additional times to start other models as well within the same running container.

*Magic-Wormhole* file transfer

Warp is a Rust software package that makes sending content between computers super easy using entryption and simple one-time word-based or QR-code authentication keys. Because of the underlying protocol, transfers will occur over local LAN or internet depending on where the machines involved are located. The software allows users to send and recieve files between Linux, OSX, Windows and smart phones.

I was interested in using Warp on the command line for simple low-setup file transfers in and out of my office, but it turns out that the underlying protocol that Warp leverages is also an open-source project and it already includes a CLI (magic-wormhole).

*ugrid* ADCIRC vectors in QGIS with MDAL

use nco cli to make compliant files

An Update To Apptainer Use On TACC HPC

The University of Texas’ newest supercomputer Frontera currently requires the following modules loaded for Apptainer images/containers based on the mvapich infiniband (ib) base images–particularly for any containerized programs that intend to use MPI.

Researchers moving their Apptainer images between TACC HPC systems, or building container images specifically for individual systems, may need to adapt their sbatch scripts to accommodate differences between default environments and infrastructures on the various available clusters.

Oilspill Visualizaton

Found another set of animations of particle model output from some past work. The image below is a snapshot during the early part of the output of a simulation of the Deepwater Horizon oilspill, animations of which were ultimately used in parts of the court cases.

Python’s visvis library used to render the results of an oilspill simulation:

SWAN Wave Model Container with MPI

Coinciding with the Containers at TACC training taking place today via webinar, here is a method I have used successfully to build our version of SWAN v41.10 spectral wave model in order to run with MPI on the University of Texas’ Stampede2 cluster.

Build SWAN with Docker #

The following Dockerfile will build the parallel mpi implementation of SWAN, the single-core serial SWAN model, and the SWAN hcat concatenation utility. The containerized model should be able to be used for 2D non-stationary, 1D or stationary simulations.

Another Example Visualization of LarvaMap Output

Found another old animation sample that was uploaded to YouTube. Again, Python’s visvis library used to render LarvaMap model output.

While visvis is not longer being actively developed, it is still an incredibly powerful and efficient opengl toolkit for Python.

Example 3D Visualization of Lagrangian Particle Behavior

Found an old animation while cleaning up my computer. Python’s visvis library used to render LarvaMap model output.

sci-wms

https://slides.com/alexandercrosby/sci-wms

ugrid

Conventions Documentation #

The conventions can be found here:

https://ugrid-conventions.github.io/ugrid-conventions/

Which is maintained though the following git repository:

https://github.com/ugrid-conventions/ugrid-conventions

Check Compliance #

pyugrid can be used to parse and validate CF-UGRID metadata. Its documentation is located here:

https://pyugrid.github.io/pyugrid/

LarvaMap

LarvaMap is a distributed parallel lagrangian transport model for larvae that includes customizable biological behavior.

The idea behind LarvaMap was to make it easy for researchers everywhere to use sophisticated larval transport models to explore and test hypotheses about the early life of marine organisms.

LarvaMap integrates four components: an ocean circulation model, a larval behavior library, a python Lagrangian particle model, and a web-system for running the transport models.