# Bootslop: A Sourceless ColorForth Derivative

This repository contains the curation materials and prototype implementation for building a zero-overhead, sourceless ColorForth-derivative for x86-64, specifically modeled after the architectures of Timothy Lottes and Onat Türkçüoğlu.

## Project Goal

The objective is to *learn* how to build this architecture from scratch, with the AI acting as a highly contextualized mentor.

## Current State

The `attempt_1/` directory contains a working C prototype that successfully implements the core architectural pillars:
*   A "sourceless" editor that manipulates a 32-bit token array (`Tape Drive`) and a parallel 64-bit annotation array.
*   A modal, interactive GUI built with raw Win32 GDI calls.
*   A handmade Just-In-Time (JIT) compiler that translates tokens into executable x86-64 machine code on every keypress.
*   An execution model based on Onat's 2-register stack (`RAX`/`RDX`) and a global memory tape.

## Helper Scripts

This repository contains several Python scripts used during the initial curation and content-gathering phase:

*   `process_visuals.py`: Downloads videos from YouTube, extracts frames based on transcript timestamps, performs OCR on the frames, and uses color analysis to generate semantically-tagged markdown logs of the visual content. It also crops out relevant code blocks and diagrams.
*   `fetch_blog.py`: Parses `TimothyLottesBlog.csv` and scrapes the HTML content of each blog post, converting it to clean markdown for local archival.
*   `fetch_notes.py`: Parses `FORTH_NOTES.csv`, filters out irrelevant or already-processed links, and scrapes the remaining pages into markdown files.
*   `estimate_context.py`: A utility to scan the `references/` directory and provide a rough estimate of the total token count to ensure it fits within the AI model's context window.
*   `ocr_interaction.py`: A small utility to perform OCR on single image files.
