Files
markitect-main/examples/infospace-with-history
tegwick 41773f1320 feat(llm): add OpenAI adapter, entity archive policy, process chapters 5-7
Add OpenAIAdapter for the OpenAI chat completions API (apikey-chatgpt.txt
or OPENAI_API_KEY). Set default model to arcee-ai/trinity-large-preview:free
for the infospace pipeline and increase max_tokens from 4096 to 8192.

Reprocess chapter 05 with Trinity Large (was Gemini: 1 truncated entity,
now 19 complete entities). Process chapters 06 (Aurora Alpha, 10 entities)
and 07 (Trinity Large, 15 entities including regenerated violent-policy.md).
Canonical set now at 85 unique entities.

Add entity archive policy: entities are never silently deleted. Retired
entities move to output/entities/archive/ with a dated reason header.
New CLI option: --archive-entity <slug> --reason "...". The --list
output shows the archive count alongside the canonical set.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-11 23:39:44 +01:00
..

This example provides a tutorial and reference experiment for how to set up a viable infospace with history using markitect.

The task is to capture the knowledge from Adam Smith's The Wealth of Nations available digitally in the public domain as a transcript of the original text and transform and extend it to a collection of concepts and entities from a systems theoretical point of view based on Stafford Beer's Viable System Model that is consistent and complete.

The tutorial should explain how to use the concept of schemas to provide a scaffolding for how to structure the necessary information entities and define a set of prompts and instructions using the prompt dependency resolution infrastructure to incrementally inject chapters of the book.

The information space should utilize the option of keeping changes as git history. And define metrics for completeness and consistency.

While running the experiment no changes must be made to the markitect infrastructure.

If demand for optimization or fixing errors occurs, a list of corresponding tasks should be generated. It will be used to optimize the markitect infrastructure to then rerun the experiment to optimize tooling and infospace over time and again.

--worsch, 10th Feb. 2026