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home-assistant-typesafe

allenporter/home-assistant-typesafe

Home Assistant conversation integration using Jev for fast intent routing.

Automated README summary

Automatically summarized from the README on 21 Sept 2026; not a run by jevbooks. Run instructions and author-reported outcomes still need verification.

What it is

A Home Assistant custom conversation integration for Assist. It classifies natural language utterances and binds device targets for voice and text commands, using cloud-accelerated TypeSafe System One decision routing with no local GPU/CPU overhead.

How it uses Jev

Jev answers structured TypeSafe System One questions (Choice and Noul primitives) covering intent selection, target type (entity vs. area), entity/area candidates, and compound command detection in a single unified payload. The integration queries the TypeSafe System One API (jev-latest) in one network roundtrip, obtaining calibrated probabilities used for confidence gating and target binding.

Primitives:choicenoul

Technique worth stealing

5-stage speculative pipeline: tokenization, candidate retrieval, hierarchical hydration, engine scoring, and target binding.

Try it

Install into custom_components/typesafe and add via Settings > Devices & Services > Add Integration > TypeSafe.

View on GitHub

Start using Jev: API key and your first request →

Model judgments from README excerpts

Project signals use repository metadata, an existing summary and the first 700 README characters, not the full project. “Not found” means not detected in that material; it does not establish absence. These are the original judgments with recorded models and dates, not source audits or run results.

Models & evaluation dates

Inclusion gate
jev-1.13.0
Project signals
jev-1.13.0
Category
jev-1.13.0
Pattern tags
jev-1.13.0

Evidence

These signals use repository metadata, an existing summary and at most 700 cleaned README characters. ≥ 0.60 means reported in that excerpt; ≤ 0.40 means not found there. The middle band is inconclusive. None is a source-code audit or a test result. The runnable-tool question excludes research experiments; the recommendation question asks for a learning shortlist, not a quality verdict.

  • Jev is core to the projectFound in material0.80
  • Shows a System One patternnot found in the excerpt0.21
  • Describes handling uncertaintynot found in the excerpt0.05
  • Reports measured numbersnot found in the excerpt0.04
  • Is a runnable toolFound in material0.94
  • Top-10 learning shortlist signalnot found in the excerpt0.23
  • Is a replica of the modelnot found in the excerpt0.05
  • Solves a common problem (0–2)score on a 0–2 scale1.02 / 2
  • About JevFound in material0.97
Signals
Jev is core to the project0.80Shows a System One pattern0.21Describes handling uncertainty0.05Reports measured numbers0.04Is a runnable tool0.94Top-10 learning shortlist signal0.23Is a replica of the model0.0500.51Solves a common problem (0–2)1.02 / 2012

no-judgment band (0.40–0.60)

Design patterns
Traffic light0.94Funnel0.92Questionnaire0.89Prefetch0.6500.51

no-judgment band (0.40–0.60)

The Jev model and date for each judgment stage are listed above. Card written by DeepSeek V4.1 Flash from the README on 21 Sept 2026.