Can typesafe.ai Jev model talk? – they said no
say-hi Can a model that only picks from a list learn to talk? Repository: https://github.com/huemorgan2/say-hi JEV (TypeSafe's jev-1.13.0) isn't a text generator. It's a chooser: you send it a situation (state) and a question with a set of options (criteria), and it picks one, with a confidence and a probability for every option. say-hi tries to get it to talk anyway, by giving it a keyboard.
- ▪say-hi Can a model that only picks from a list learn to talk?
- ▪Repository: https://github.com/huemorgan2/say-hi JEV (TypeSafe's jev-1.13.0) isn't a text generator.
- ▪It's a chooser: you send it a situation (state) and a question with a set of options (criteria), and it picks one, with a confidence and a probability for every option. say-hi tries to get it to talk anyway, by giving it a keyboard.
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | GitHub |
| Canonical URL | https://github.com/huemorgan2/say-hi |
| Publication time | Thu, 01 Oct 2026 18:25:38 +0000 |
| Retrieval time | 2026-10-01T18:37:31.853Z |
| Last seen | 2026-10-01T18:37:31.853Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | IGcWxrXS8RwD · 1 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
say-hi Can a model that only picks from a list learn to talk? Repository: https://github.com/huemorgan2/say-hi JEV (TypeSafe's jev-1.13.0) isn't a text generator. It's a chooser: you send it a situation (state) and a question with a set of options (criteria), and it picks one, with a confidence and a probability for every option. say-hi tries to get it to talk anyway, by giving it a keyboard. Every reply is typed one key per JEV request: letters, digits, punctuation, space, backspace, return and a SEND key. It's a fun experiment with Jev, and a starting point for simple chatbots with canned responses: replace the keyboard (or the answer list) with your own canned replies, and Jev picks the best one for each message.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.
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