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How to route requests with NeoHorse-Jev structured decisions with Neo Horse

Use NeoHorse-Jev-4B to pick an action, check a condition, or assign a rating from app state.

Who it is forAn application engineer whose workflow must choose between tools, branches, or request routes based on current state.

The problemHand-written routing rules become hard to maintain when the choice depends on free-form context.

The outcomeYour app gets a structured decision with probabilities from Choice, Noul, or Score and uses it to route requests or select tools.

What you need first

  • A machine with enough GPU memory for the 4B or 9B BF16 weights, or a quantized GGUF or MLX build for smaller hardware
  • Python with pip available
  • Disk space for the downloaded checkpoint from Hugging Face or ModelScope

Steps

  1. Download the complete NeoHorse-Jev-4B model bundle from Hugging Face or ModelScope, not only the weights.
  2. Open jev/README.md in the repo and read the Deployment section.
  3. Pick vLLM, SGLang, or the native Python runtime as described in that guide.
  4. Write your questions and possible answers for Choice, Noul, or Score, and map each answer to a route or tool.
  5. Run a few sample application states through the model and confirm the returned decision matches the route you expect.

Prompt for your agent

In the TokenRhythm/NeoHorse repo, read the NeoHorse-Jev deployment guide in jev/README.md and set up the model bundle at <model-directory>. Send the application state <sample-state> with the Choice question <question> and report the selected answer and its probability. Verify that the probabilities for the listed answers sum to a value you can explain.

Caveat. The README says the decision model needs its complete bundle and a matching runtime or backend adapter, and the deployment steps are in a separate jev/README.md that is not shown here.

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