# Inference Parameters

Set inference-time parameters such as `temperature`, `maxTokens`, `topP` and more.

```lms_code_snippet
  variants:
    ".respond()":
      language: python
      code: |
        result = model.respond(chat, config={
            "temperature": 0.6,
            "maxTokens": 50,
        })

    ".complete()":
      language: python
      code: |
        result = model.complete(chat, config={
            "temperature": 0.6,
            "maxTokens": 50,
            "stopStrings": ["\n\n"],
          })

```

See [`LLMPredictionConfigInput`](./../../typescript/api-reference/llm-prediction-config-input) in the
Typescript SDK documentation for all configurable fields.

Note that while `structured` can be set to a JSON schema definition as an inference-time configuration parameter
(Zod schemas are not supported in the Python SDK), the preferred approach is to instead set the
[dedicated `response_format` parameter](<(./structured-responses)>), which allows you to more rigorously
enforce the structure of the output using a JSON or class based schema definition.