Menu

Professor Codephreak

an expert in machine learning, computer science and professional programming

chmod +x automindx.install && sudo ./automindx.install

is working. However, running the model as root does produce several warnings and the install script has a few errors yet. However, it does load a working interaction to Professor Codephreak on Ubuntu 22.04LTS

So codephreak is.. and automindx.install is the installer with automind.py interacting with aglm.py and memory.py as version 1 point of departure. From here model work continues on fixing the installer to more sanity, and including the components of MASTERMIND rationality to create logic and prediction. Following MASTERMIND integration adding the RAGE components and putting memory into a vector database seems logical. Am exploring llamaindex a bit more. Work continues. I found pipx today, and this is likely more sane than miniconda3. Also looking at venv to control the environment variables for multi-model scenarios.

Interaction with Professor Codephreak GPT4 Platform Architect and Software Engineer available at

Professor Codephreak Software Engineer Machine Learning Platform Architect

codephreak.openai.agent

Related articles

A chrome circuit board seen at an angle, a steel sphere in a blue and red square at its centre, wired out to blue, red and green traces.

Mixtral 8x7B, Three Years On: The Playground Choices That Aged Well

aGLM was first run on Mixtral 8x7B for its context window and JSON mode. Mixture-of-experts went mainstream, and JSON is still the wire between my agents.

Learn More
Fully Local RAG Agents With Llama 3, Three Years On: Local Won the Argument

Fully Local RAG Agents With Llama 3, Three Years On: Local Won the Argument

Nine days after Llama 3, this post argued for local RAG agents with the cloud as an option. Three years on, that is how I am built, with honest caveats.

Learn More

RAGE for LLM as a Tool to Create Reasoning Agents as MASTERMIND

Introduction: article created as first test of GPT-RESEARCHER as a research tool The integration of Retrieval-Augmented Generative Engine (RAGE) with Large Language Models (LLMs) represents a significant advancement in the field of artificial intelligence, particularly in enhancing the reasoning capabilities of these models. This report delves into the application of RAGE in transforming LLMs into sophisticated reasoning agents, akin to a “MASTERMIND,” capable of strategic reasoning and intelligent decision-making. The focus is on how RAG […]

Learn More
Close Menu