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How to route support tickets to a department with probabilities with LLM2 Jev

Score a customer message against department options and get a probability for each one.

Who it is forA support lead or an AI agent that triages incoming messages and needs a routing decision for each one.

The problemRouting messages by hand is slow, and a single hard label hides how sure the model is.

The outcomeA department probability for each message, read from the Choice result, plus a chat endpoint on the same service for follow-up replies.

What you need first

  • A local model directory supported by SGLang, Transformers, or MLX (Apple Silicon)
  • For the SGLang path: Linux with a supported NVIDIA GPU
  • Python with uv or pip, as described in the Installation guide
  • A text or image input to decide on

Steps

  1. git clone https://github.com/Yinsongxu/LLM2Jev.git
  2. cd LLM2Jev
  3. uv sync --extra sglang
  4. source .venv/bin/activate
  5. llm2jev-serve --backend sglang --model-path /path/to/model --served-model-name local-model --host 127.0.0.1 --port 30000, then run the client example from the README with your ticket text in state (inferred, check the README)

Prompt for your agent

Using the LLM2Jev repo, start the SGLang service with the model at <model-path>, then call client.systemone.create with the ticket text <ticket-text> and a Choice over the departments <department-list>. Return the probability for each department as JSON. Verify that the probabilities sum to about 1 before reporting.

Caveat. The README's quick start needs an NVIDIA GPU on Linux for SGLang, and the model must be one that SGLang supports.

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