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How to route tickets on an open LLM with no training or labels with Any Jev

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

Who it is forA developer with an open LLM already downloaded who needs a routing or classification step and has no labeled data to train on.

The problemRaw label logits change when the options are reordered and carry the model's bias toward some labels, so the probabilities are not trustworthy.

The outcomeA Decision with a distribution over the options and a level value of L0, which downstream code can require before acting.

What you need first

  • 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

Steps

  1. Run pip install anyjev in a Python environment with the backend you need. (inferred, check the README)
  2. Create the backend with HFBackend("Qwen/Qwen3-8B") and build a Decider with Decider(backend).
  3. Define a choice question with Question.choice("Which team should handle this?", ["billing", "technical", "sales", "other"], name="route"). (inferred, check the README)
  4. Call d.decide(<ticket text>, [route])["route"] and read r.distribution and r.level. (inferred, check the README)
  5. Optionally enable the rotation budget with Decider(backend, adaptive_shifts=True, canonical_order=True) and calibrate it on a few hundred unlabelled tickets using calibrate_adaptive.

Prompt for your agent

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.

Caveat. The README's accuracy and automation figures come from BANKING77 with Qwen3-8B, so measure on your own tickets before trusting the threshold.

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