Work In Progress: Codex Ideas

and Beethoven as the ultimate token predictor

Dear fellow book-lovers,

Today I am going to share two items.

Beethoven, Master of Latent Space

First, a video interview with Leonard Bernstein where he explains that the true essence of Beethoven’s unique greatness was remarkably reminiscent of the modern art of generative modeling. In the section before the jump point, Bernstein explains that Beethoven was only average (LLM-level?) in so many aspects of musical creation. But when it came to figuring out the next token …

Codexes-Ideas: A Look Under the Hood

I have been reorganizing my Python book publishing libraries from giant monorepos to more focused individual repositories. Here is the README for the one that I use in the “ideation” phase.

Overview

A comprehensive tool for generating, managing, and evaluating book ideas using AI models.

Codexes Ideas is a powerful framework for:

• Generating creative book ideas using various AI models

• Running idea tournaments to identify the most promising concepts

• Creating continuous streams of fresh book ideas

• Expanding initial ideas into more developed concepts

• Building oral histories and other complex book projects

Installation

Prerequisites

• Python 3.8 or higher

• uv for Python environment management

• Local LLM server such as Ollama (optional but recommended for faster performance)

Setup

1. Clone the repository:

git clone https://github.com/yourusername/codexes-ideas.git
   cd codexes-ideas

2. Create and activate a virtual environment:

uv venv
   source .venv/bin/activate  # On Windows: .venv\Scripts\activate

3. Install dependencies:

uv pip install -r requirements.txt

4. (Optional) Install Ollama for local AI model access:

   • Follow instructions at ollama.ai

   • Pull recommended models:

ollama pull mistral
     ollama pull deepseek-r1:latest

Usage

The Codexes Ideas tool provides several commands through the IdeaGeneratingMachine.py script: