Skip to content
Merged
Show file tree
Hide file tree
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
1 change: 1 addition & 0 deletions README.md
Original file line number Diff line number Diff line change
Expand Up @@ -192,6 +192,7 @@ The [independent model research](community/projects/tools/README.md#independent-
- [agy-jevgate](https://github.com/catpotd/agy-jevgate) - Fail-closed Antigravity `PreToolUse` hook for shell commands using TypeSafe Jev risk scores. [Project guide](community/projects/tools/agy-jevgate.md).
- [AlphaOptimizer](https://github.com/alpha-tales/alphaoptimizer) - Compact large Codex/tool outputs locally; optional TypeSafe Jev ranks relevant chunks (BYOK). [Project guide](community/projects/tools/alphaoptimizer.md).
- [agent-desktop](https://github.com/lahfir/agent-desktop) - Rust macOS accessibility CLI for desktop computer use; optional jev-desktop skill/scripts use TypeSafe Jev for target/command choice without putting the a11y tree in agent context (BYOK). [Project guide](community/projects/tools/agent-desktop.md).
- [AnyJev (Nokia Applied Research)](https://github.com/nokia-applied-research/AnyJev) - Turn open LLMs into Jev-style typed decisions with probabilities (L0–L2); independent of official Jev / TypeSafe hosted API. [Project guide](community/projects/tools/nokia-anyjev.md).
- [feelings](https://github.com/BoundaryML/feelings) - BAML `.feels()` / `.how()` / `.matches<T>()` typed AI-if methods powered by TypeSafe Jev; upstream licensing unspecified. [Project guide](community/projects/tools/feelings.md).
- [jev-feels](https://github.com/Qew7/jev-feels) - Ruby gem for TypeSafe Jev as `feels?` / `decide` / `score` and Rails validations (distinct from BAML feelings and ruby_decision_model). [Project guide](community/projects/tools/jev-feels.md).
- [jev-foundation-models](https://github.com/peterfriese/jev-foundation-models) - Swift 6 bridge: TypeSafe Jev as an Apple Foundation Models `LanguageModel` for `@Generable` decisions (distinct from TypeSafe Swift client). [Project guide](community/projects/tools/jev-foundation-models.md).
Expand Down
1 change: 1 addition & 0 deletions community/projects/tools/README.md
Original file line number Diff line number Diff line change
Expand Up @@ -286,6 +286,7 @@ These projects study related typed-decision patterns using other models. They ar

| Project | What you can do | Stack / format |
| --- | --- | --- |
| [AnyJev (Nokia Applied Research)](nokia-anyjev.md) | Turn an open LLM into Jev-style typed decisions with probabilities (L0–L2); independent of official Jev. | Python · PyPI (`anyjev` 0.1.0, Apache-2.0) |
| [Jev-Omni](jev-omni.md) | Run an open multimodal System One–style classifier (text/image/audio/video → option probabilities) on Gemma 4 12B IT; independent of official Jev. | Python / PyTorch · HF weights (CUDA, ~50 GB FP32) |
| [Jevlike](jevlike.md) | Train a small option-attention scorer with synthetic data and optional frozen encoders; independent of official Jev. | Python / PyTorch · research starter |
| [NanoJev](nanojev.md) | Study independent Qwen-based typed decision heads, local serving, and game controllers with recorded comparisons. | Python / PyTorch · model research and replay |
Expand Down
49 changes: 49 additions & 0 deletions community/projects/tools/nokia-anyjev.md
Original file line number Diff line number Diff line change
@@ -0,0 +1,49 @@
# AnyJev (Nokia Applied Research)

[All projects](../README.md) · [Independent model research](README.md#independent-model-research)

Turn an open LLM into a Jev-style typed decision model (Choice/Noul/Score with probabilities) via position-debiasing and optional calibration/heads—no TypeSafe hosted Jev and no fine-tune required for L0. Distinct from any MorrisZJ/AnyJev fork; independent of official Jev weights.

| At a glance | Details |
| --- | --- |
| Source | [Source](https://github.com/nokia-applied-research/AnyJev) |
| Maintainer | [nokia-applied-research](https://github.com/nokia-applied-research) (authors: Jiamu Zhang, Tianze Yang, Yucheng Shi, Liang Wu). Independently curated; this entry is not an upstream submission or endorsement. Not affiliated with TypeSafe AI. |
| Format | Python package **`anyjev` 0.1.0** (PyPI; `pip install "anyjev[hf]"`). Transformers backend today; vLLM/SGLang on roadmap. |
| Requirements | Python ≥ 3.10; Hugging Face model weights for live LLM readout (`torch`/`transformers` extras). Offline `demo` with `--backend fake` needs no download. |
| License | [Apache-2.0](https://github.com/nokia-applied-research/AnyJev/blob/3cd8c6fcd9e90fc04214575ade6779da1e3f3704/LICENSE). |
| Disclosure | AI-assisted catalog review; no affiliation. Listing is not an endorsement. Source inspected (README, LICENSE, pyproject, package layout). Live model downloads and reported BANKING77 numbers were **not** reproduced on the review host. Upstream benchmarks are author-reported. |

## When to use

Use it to study or deploy Jev-shaped decisions on your own open models with L0 (training-free), L1 (temperature), or L2 (closed-form early-exit heads). Prefer hosted [TypeSafe Jev](https://docs.typesafe.ai) when you want the official System One API; prefer [Open Alternative to Jev](open-alternative-jev.md) for other open-model comparison labs.

## How it works

`Decider` + backend read next-token distributions for typed questions. L0 averages cyclic option rotations and divides out a label prior; L1 adds temperature; L2 fits a small head on hidden states (~⅔ depth) from a few hundred labels. Every `Decision` carries its `level` for downstream gating.

## Get started

```sh
pip install "anyjev[hf]"
# or from source:
git clone https://github.com/nokia-applied-research/AnyJev.git
cd AnyJev
git checkout 3cd8c6fcd9e90fc04214575ade6779da1e3f3704
python -m demo.jev_mode --backend fake # no download
```

## Examples and demos

- README usage with `Question.choice` / `noul` / `score`.
- `demo/` lifecycle scripts; shipped heads under `anyjev-heads/`.
- Bench docs: `docs/results_bench.md` (author-reported).

## Limits and data handling

Local inference sends prompts only to your chosen backend—not to TypeSafe. Not a drop-in replacement for official Jev behavior or pricing. Pre-Alpha classifiers. This listing did not download Qwen weights or re-run benches.

## Review and maintenance

Reviewed on **2026-09-23** at [commit 3cd8c6f](https://github.com/nokia-applied-research/AnyJev/tree/3cd8c6fcd9e90fc04214575ade6779da1e3f3704) (**0.1.0**, Apache-2.0). AI-assisted source review of README, LICENSE, pyproject. No live model spend.

Related: [Open Alternative to Jev](open-alternative-jev.md), [Jev-Omni](jev-omni.md), [SemIf](semif.md).
Loading