Settings

Large language models (LLMs) typically provide settings to augment their output.

All AI SDK functions support the following common settings in addition to the model, the prompt, and additional provider-specific settings:

const result = await generateText({
model: yourModel,
maxTokens: 512,
temperature: 0.3,
maxRetries: 5,
prompt: 'Invent a new holiday and describe its traditions.',
});

Some providers do not support all common settings. If you use a setting with a provider that does not support it, a warning will be generated. You can check the warnings property in the result object to see if any warnings were generated.

maxTokens

Maximum number of tokens to generate.

temperature

Temperature setting.

The value is passed through to the provider. The range depends on the provider and model. For most providers, 0 means almost deterministic results, and higher values mean more randomness.

It is recommended to set either temperature or topP, but not both.

topP

Nucleus sampling.

The value is passed through to the provider. The range depends on the provider and model. For most providers, nucleus sampling is a number between 0 and 1. E.g. 0.1 would mean that only tokens with the top 10% probability mass are considered.

It is recommended to set either temperature or topP, but not both.

topK

Only sample from the top K options for each subsequent token.

Used to remove "long tail" low probability responses. Recommended for advanced use cases only. You usually only need to use temperature.

presencePenalty

The presence penalty affects the likelihood of the model to repeat information that is already in the prompt.

The value is passed through to the provider. The range depends on the provider and model. For most providers, 0 means no penalty.

frequencyPenalty

The frequency penalty affects the likelihood of the model to repeatedly use the same words or phrases.

The value is passed through to the provider. The range depends on the provider and model. For most providers, 0 means no penalty.

stopSequences

The stop sequences to use for stopping the text generation.

If set, the model will stop generating text when one of the stop sequences is generated. Providers may have limits on the number of stop sequences.

seed

It is the seed (integer) to use for random sampling. If set and supported by the model, calls will generate deterministic results.

maxRetries

Maximum number of retries. Set to 0 to disable retries. Default: 2.

abortSignal

An optional abort signal that can be used to cancel the call.

The abort signal can e.g. be forwarded from a user interface to cancel the call, or to define a timeout.

Example: Timeout

const result = await generateText({
model: openai('gpt-4o'),
prompt: 'Invent a new holiday and describe its traditions.',
abortSignal: AbortSignal.timeout(5000), // 5 seconds
});

headers

Additional HTTP headers to be sent with the request. Only applicable for HTTP-based providers.

You can use the request headers to provide additional information to the provider, depending on what the provider supports. For example, some observability providers support headers such as Prompt-Id.

import { generateText } from 'ai';
import { openai } from '@ai-sdk/openai';
const result = await generateText({
model: openai('gpt-4o'),
prompt: 'Invent a new holiday and describe its traditions.',
headers: {
'Prompt-Id': 'my-prompt-id',
},
});

The headers setting is for request-specific headers. You can also set headers in the provider configuration. These headers will be sent with every request made by the provider.