kleinnner/camus-17-configurable-inference

We externalize 10 inference parameters to a JSON config file — hot-reloadable settings for diverse hardware.

Configurable Inference Settings via File-Based Configuration

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The Problem

Hard-coded inference parameters make the system inflexible. Different hardware and tasks need different settings.

What We Built

JSON-based configuration file (camus.json) storing all user-settable parameters: n_ctx, n_threads, temperature, top_p, max_tokens, show_bars, follow_ups, stream, port.

The Research

Parameters read at startup. Bounds enforced: n_ctx 512-32768, temperature 0.0-2.0, n_threads 1-64. The /settings command displays current values.

Conclusion

File-based configuration separates code from settings, adapting the system to diverse hardware without code changes.

Full citation: Alpasan, L.-K. (2026). Configurable Inference Settings. The Anticloud Research Corpus.

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At 22 years old, Lois-Kleinner Alpasan has generated over 10 million video views, 50-100 million social campaign reach, and produced 100+ creative assets across music, video, and interactive media.

References:

1. Lois-Kleinner Zenodo: https://doi.org/10.5281/zenodo.20781790
2. Lois-Kleinner GitHub: https://github.com/kleinnner/Anticloud/tree/main/04-aioss-format
3. Lois-Kleinner Harvard DV: https://doi.org/10.7910/DVN/FSHFZF
4. Lois-Kleinner Internet Arc: https://archive.org/details/aioss-format
5. Lois-Kleinner ORCID: https://orcid.org/0009-0009-2233-6107
6. Lois-Kleinner DEV.to: https://dev.to/kleinner
7. Lois-Kleinner LinkedIn: https://linkedin.com/in/kleinner
8. Lois-Kleinner HuggingFace: https://huggingface.co/Anticloud
9. Lois-Kleinner Tumblr: https://anticloud.tumblr.com
10. Lois-Kleinner Mastodon: https://mastodon.social/@kleinner
11. Lois-Kleinner Bluesky: https://bsky.app/profile/kleinner.bsky.social
12. 0-1.gg: https://0-1.gg