DEDUPED Hot AI repos, turned into use cases Get 5 a day

What you can do with Any Jev

AnyJev is a Python library that turns an LLM into a decision model: you give it a state and a typed question, and it returns an answer with a probability over the options, read from the model's next-token distribution.

Trended earlier

nokia-applied-research/AnyJev on GitHub

Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk.

What do you want to do?

3 use cases

  • Route support tickets to one option with a probability

    Send a customer message to one of several queues and get the probability for each queue in one call.

    View prompt
    Using the repo AnyJev (nokia-applied-research/AnyJev), load morriszjm/Tacit-9B with Tacit.from_pretrained and call decide on <customer message> with the options <queue list>. Expected output: the chosen option, a probability per option, and the route value. Verify that the probabilities sum to about 1 before routing the ticket.

  • Route tickets on an open LLM with no training or labels

    Use the Decider at level L0 to get stable option probabilities from any open causal LM.

    View prompt
    Using the repo AnyJev (nokia-applied-research/AnyJev), build a Decider on Qwen/Qwen3-8B with HFBackend and route the ticket <ticket text> using a choice question over <option list>. Expected output: a distribution over the options and the level L0. Verify that the distribution is returned for every option and that the level is L0 before acting on the result.

  • Share one decision endpoint with a capped reasoning budget

    Run a local HTTP gateway so several clients get decisions and share one cap on reasoning escalations.

    View prompt
    Using the repo AnyJev (nokia-applied-research/AnyJev), start the vLLM server for morriszjm/Tacit-9B and the anyjev.serve gateway on port 8100, then POST the decision <state text> with options <option list> to /v1/decide. Expected output: a JSON decision with answer, probs and route fields. Verify that GET /v1/stats returns an escalation share at or below the configured cap.

How to use Any Jev

  1. Check you have what it needs: Python with pip; A GPU or a vLLM server for the 9B-class models, or a smaller open causal LM for the training-free path; Access to the Hugging Face model you choose, for example morriszjm/Tacit-9B or Qwen/Qwen3-8B.
  2. Open nokia-applied-research/AnyJev on GitHub and read the README and license.
  3. Create a Python environment and run pip install "anyjev[hf]". (inferred, check the README)
  4. Load the model in Python with Tacit.from_pretrained("morriszjm/Tacit-9B").
  5. Call tacit.decide(state=<customer message>, question="What does the customer want?", options=[<your queue names>]) on one message. (inferred, check the README)
  6. Read d["answer"], d["probs"] and d["route"] from the returned result.

These steps come from our top use case, Route support tickets to one option with a probability, which also has a copy-paste agent prompt.

Any Jev alternatives · Best AI repos for Work and operations

About this repo

  • Who it is forBuilt for engineers and ML teams who need an LLM to make routine classification or triage decisions with calibrated probabilities, either from a training-free setup or from the Tacit checkpoints.
  • Why it is hot
  • LanguagePython
  • Sourcegithub.com/nokia-applied-research/AnyJev · Back to Hot repos

Requirements

  • Python with pip
  • A GPU or a vLLM server for the 9B-class models, or a smaller open causal LM for the training-free path
  • Access to the Hugging Face model you choose, for example morriszjm/Tacit-9B or Qwen/Qwen3-8B
Maintain Any Jev? Add the Featured on Deduped badge

Paste this into your README:

[![Featured on Deduped](https://dedupedai.com/badge/nokia-applied-research-anyjev.svg)](https://dedupedai.com/use-cases/nokia-applied-research-anyjev/?ref=badge)

More badge styles and HTML

Questions about Any Jev

What is Any Jev?

AnyJev is a Python library that turns an LLM into a decision model: you give it a state and a typed question, and it returns an answer with a probability over the options, read from the model's next-token distribution. It is an open-source project on GitHub: https://github.com/nokia-applied-research/AnyJev.

Who is Any Jev for?

Built for engineers and ML teams who need an LLM to make routine classification or triage decisions with calibrated probabilities, either from a training-free setup or from the Tacit checkpoints.

What can I do with Any Jev?

3 use cases so far, for example: Route support tickets to one option with a probability; Route tickets on an open LLM with no training or labels; Share one decision endpoint with a capped reasoning budget. Each has steps and a copy-paste agent prompt.

What do I need to run Any Jev?

Python with pip; A GPU or a vLLM server for the 9B-class models, or a smaller open causal LM for the training-free path; Access to the Hugging Face model you choose, for example morriszjm/Tacit-9B or Qwen/Qwen3-8B.

What are alternatives to Any Jev?

Other hot AI repos in Work and operations: AI Job Search, Solidcraft, Fastbrowse, Awesome AI Agent Platforms, Nautilo.

Is Any Jev safe to run?

Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.