Llamatik exposes a small set of runtime generation parameters through updateGenerateParams(...).

LlamaBridge.updateGenerateParams(
    temperature = 0.7f,
    maxTokens = 256,
    topP = 0.95f,
    topK = 40,
    repeatPenalty = 1.1f,
)

What each parameter does#

Temperature#

Controls randomness.

• lower values: more deterministic
• higher values: more varied and creative

maxTokens#

Sets the maximum number of tokens the model may generate. Use this to control response length and latency.

topP#

Nucleus sampling threshold. The model samples from the smallest set of likely tokens whose cumulative probability reaches topP.

topK#

Limits sampling to the K most likely next tokens.

repeatPenalty#

Discourages repeated phrases and loops. This is often useful for chat, summaries, and structured outputs.

Tuning advice#

• Start from moderate values and test on a fixed prompt set.
• Change one parameter at a time.
• For extraction or JSON, lean toward lower temperature.
• For brainstorming or creative tasks, slightly higher temperature can help.