Modelfile

A Modelfile describes a derived model: a base model plus the questions it should always ask, an optional refit calibration and a license. Build it with ollaya create, then run it by name with just a state.

ollaya create triage -f Modelfile
ollaya run triage "I was charged twice for my subscription this month."

Example

# Modelfile
FROM laya:en

QUESTIONS """
{
  "department": {
    "type": "choice",
    "instructions": "Which team should handle this?",
    "criteria": {
      "billing": "Payments, invoices and refunds",
      "technical": "Bugs, errors and outages",
      "account": "Login, profile and settings"
    }
  },
  "urgency": {
    "type": "score",
    "instructions": "How urgent is this?",
    "criteria": ["Not urgent", "Normal", "Urgent"]
  },
  "refund": {
    "type": "noul",
    "instructions": "Is the customer asking for a refund?"
  }
}
"""

CALIBRATION ./calibration.json

LICENSE """
Apache License, Version 2.0
"""

Instructions

Instruction	Required	Description
`FROM`	yes	The base model, e.g. `laya:en` or `laya:multilingual`
`QUESTIONS`	no	The question schema — the same object as `questions` in the API
`CALIBRATION`	no	Calibration temperatures that replace the base model's
`PARAMETER`	no	A runtime parameter for the model
`LICENSE`	no	License text for the derived model

Instructions are written in upper case. Multi-line values are wrapped in """.

FROM

The model to build on. Any local or pullable model works:

FROM laya:multilingual

QUESTIONS

The questions the model asks when you call it without any. It takes a JSON object, inline between """ or as a path to a .json file:

QUESTIONS ./questions.json

CALIBRATION

Decision models report probabilities, and those probabilities are only useful if they are calibrated. Ollaya calibrates with temperature scaling. CALIBRATION points to a JSON file with temperatures refit on your own labelled data, which replaces the base model's calibration:

{
  "temperature_by_options": {
    "choice:2": 1.9,
    "choice:3-5": 1.8,
    "score:3-5": 1.3,
    "noul:2": 2.0
  }
}

Keys are question type and option count; values are the temperatures to divide logits by. Refitting on data from your own workflow is the most reliable way to make thresholds like "escalate when P > 0.9" behave.

PARAMETER

Sets a runtime parameter for the model:

PARAMETER <name> <value>

The list of supported parameters will be documented here before the first release.

LICENSE

The license text shipped with the model and shown by ollaya show. When you build on an Apache-2.0 model such as Laya, keep its license and attribution.