Rizzo-AI-Academy/rizzo-flow

The open, local take on Jev: typed decisions from an LLM, without generating a single token

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Unstructured state in → typed, probabilistic decisions out. On your own machine. 🌐 Website · A project by Rizzo AI Academy · 🇮🇹 Documentazione dettagliata in italiano Rizzo Flow is an open-source, local-first implementation of the idea behind Jev, TypeSafe's "System One" model: a function call with judgment that takes unstructured state and returns typed decisions with probabilities — a yes/no, a choice among options, a score on a rubric, a number — instead of text you then have to parse. Jev is a closed, hosted service. Rizzo Flow gives you the same programming model on your own hardware, with open weights, and with the same HTTP interface, so code written against the TypeSafe API can point at localhost by changing one URL. It runs on llama.cpp, so the hardware can be an Apple, NVIDIA, AMD or Intel GPU, or no GPU at all. New: fine-tuned weights. Since 25 September…

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Inside the original README — Document outline
  1. Rizzo Flow
  2. The open, local take on Jev: typed decisions from an LLM, without generating a single token
  3. Quickstart
  4. Which hardware, and what we have actually run
  5. Models and options
  6. Training and calibration
  7. Fine-tuning
  8. Results on typed-decisions
  9. Calibration
  10. Why "System One"
  11. Primitives
  12. Native API — POST /v1/decisions

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Documentation belongs to its respective authors. Reported project/model license: Apache-2.0. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.

What this repository does

The open, local take on Jev: typed decisions from an LLM, without generating a single token

Repository facts

Owner
Rizzo-AI-Academy
Primary language
Python
Stars
721
Forks
43
Open issues + pull requests
10
License
Apache-2.0
Archived
No
Default branch
main
Created
2026-09-21T00:00:02.000Z
Last push
2026-09-25T21:15:27.000Z

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