`generateText()`

Generates text and calls tools for a given prompt using a language model.

It is ideal for non-interactive use cases such as automation tasks where you need to write text (e.g. drafting email or summarizing web pages) and for agents that use tools.

import { openai } from '@ai-sdk/openai';
import { generateText } from 'ai';

const { text } = await generateText({
  model: openai('gpt-4-turbo'),
  prompt: 'Invent a new holiday and describe its traditions.',
});

console.log(text);

To see generateText in action, check out these examples.

Import

import { generateText } from "ai"

API Signature

model:

LanguageModel

The language model to use. Example: openai('gpt-4-turbo')

system:

string

The system prompt to use that specifies the behavior of the model.

prompt:

string

The input prompt to generate the text from.

messages:

Array<CoreSystemMessage | CoreUserMessage | CoreAssistantMessage | CoreToolMessage> | Array<UIMessage>

A list of messages that represent a conversation. Automatically converts UI messages from the useChat hook.

CoreSystemMessage

role:

'system'

The role for the system message.

content:

string

The content of the message.

CoreUserMessage

role:

'user'

The role for the user message.

content:

string | Array<TextPart | ImagePart | FilePart>

The content of the message.

TextPart

type:

'text'

The type of the message part.

text:

string

The text content of the message part.

ImagePart

type:

'image'

The type of the message part.

image:

string | Uint8Array | Buffer | ArrayBuffer | URL

The image content of the message part. String are either base64 encoded content, base64 data URLs, or http(s) URLs.

mimeType?:

string

The mime type of the image. Optional.

FilePart

type:

'file'

The type of the message part.

data:

string | Uint8Array | Buffer | ArrayBuffer | URL

The file content of the message part. String are either base64 encoded content, base64 data URLs, or http(s) URLs.

mimeType:

string

The mime type of the file.

CoreAssistantMessage

role:

'assistant'

The role for the assistant message.

content:

string | Array<TextPart | ToolCallPart>

The content of the message.

TextPart

type:

'text'

The type of the message part.

text:

string

The text content of the message part.

ToolCallPart

type:

'tool-call'

The type of the message part.

toolCallId:

string

The id of the tool call.

toolName:

string

The name of the tool, which typically would be the name of the function.

args:

object based on zod schema

Parameters generated by the model to be used by the tool.

CoreToolMessage

role:

'tool'

The role for the assistant message.

content:

Array<ToolResultPart>

The content of the message.

ToolResultPart

type:

'tool-result'

The type of the message part.

toolCallId:

string

The id of the tool call the result corresponds to.

toolName:

string

The name of the tool the result corresponds to.

result:

unknown

The result returned by the tool after execution.

isError?:

boolean

Whether the result is an error or an error message.

tools:

Record<string, CoreTool>

Tools that are accessible to and can be called by the model. The model needs to support calling tools.

CoreTool

description?:

string

Information about the purpose of the tool including details on how and when it can be used by the model.

parameters:

Zod Schema | JSON Schema

The schema of the input that the tool expects. The language model will use this to generate the input. It is also used to validate the output of the language model. Use descriptions to make the input understandable for the language model. You can either pass in a Zod schema or a JSON schema (using the `jsonSchema` function).

execute?:

async (parameters: T, options: ToolExecutionOptions) => RESULT

An async function that is called with the arguments from the tool call and produces a result. If not provided, the tool will not be executed automatically.

ToolExecutionOptions

toolCallId:

string

The ID of the tool call. You can use it e.g. when sending tool-call related information with stream data.

messages:

CoreMessage[]

Messages that were sent to the language model to initiate the response that contained the tool call. The messages do not include the system prompt nor the assistant response that contained the tool call.

abortSignal:

AbortSignal

An optional abort signal that indicates that the overall operation should be aborted.

toolChoice?:

"auto" | "none" | "required" | { "type": "tool", "toolName": string }

The tool choice setting. It specifies how tools are selected for execution. The default is "auto". "none" disables tool execution. "required" requires tools to be executed. { "type": "tool", "toolName": string } specifies a specific tool to execute.

maxTokens?:

number

Maximum number of tokens to generate.

temperature?:

number

Temperature setting. The value is passed through to the provider. The range depends on the provider and model. It is recommended to set either `temperature` or `topP`, but not both.

topP?:

number

Nucleus sampling. The value is passed through to the provider. The range depends on the provider and model. It is recommended to set either `temperature` or `topP`, but not both.

topK?:

number

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?:

number

Presence penalty setting. It 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.

frequencyPenalty?:

number

Frequency penalty setting. It 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.

stopSequences?:

string[]

Sequences that will stop the generation of the text. If the model generates any of these sequences, it will stop generating further text.

seed?:

number

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

maxRetries?:

number

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

abortSignal?:

AbortSignal

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

headers?:

Record<string, string>

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

maxSteps?:

number

Maximum number of sequential LLM calls (steps), e.g. when you use tool calls. A maximum number is required to prevent infinite loops in the case of misconfigured tools. By default, it is set to 1.

experimental_continueSteps?:

boolean

Enable or disable continue steps. Disabled by default.

experimental_telemetry?:

TelemetrySettings

Telemetry configuration. Experimental feature.

TelemetrySettings

isEnabled?:

boolean

Enable or disable telemetry. Disabled by default while experimental.

recordInputs?:

boolean

Enable or disable input recording. Enabled by default.

recordOutputs?:

boolean

Enable or disable output recording. Enabled by default.

functionId?:

string

Identifier for this function. Used to group telemetry data by function.

metadata?:

Additional information to include in the telemetry data.

experimental_providerMetadata?:

Record<string,Record<string,JSONValue>> | undefined

Optional metadata from the provider. The outer key is the provider name. The inner values are the metadata. Details depend on the provider.

experimental_activeTools?:

Array<TOOLNAME> | undefined

The tools that are currently active. All tools are active by default.

experimental_repairToolCall?:

(options: ToolCallRepairOptions) => Promise<LanguageModelV1FunctionToolCall | null>

A function that attempts to repair a tool call that failed to parse. Return either a repaired tool call or null if the tool call cannot be repaired.

ToolCallRepairOptions

system:

string | undefined

The system prompt.

messages:

CoreMessage[]

The messages in the current generation step.

toolCall:

LanguageModelV1FunctionToolCall

The tool call that failed to parse.

tools:

TOOLS

The tools that are available.

parameterSchema:

(options: { toolName: string }) => JSONSchema7

A function that returns the JSON Schema for a tool.

error:

NoSuchToolError | InvalidToolArgumentsError

The error that occurred while parsing the tool call.

experimental_output?:

Output

Experimental setting for generating structured outputs.

Output

Output.text():

Output

Forward text output.

Output.object():

Output

Generate a JSON object of type OBJECT.

Options

schema:

Schema<OBJECT>

The schema of the JSON object to generate.

onStepFinish?:

(result: onStepFinishResult) => Promise<void> | void

Callback that is called when a step is finished.

onStepFinishResult

stepType:

"initial" | "continue" | "tool-result"

The type of step. The first step is always an "initial" step, and subsequent steps are either "continue" steps or "tool-result" steps.

finishReason:

The reason the model finished generating the text for the step.

usage:

TokenUsage

The token usage of the step.

TokenUsage

promptTokens:

number

The total number of tokens in the prompt.

completionTokens:

number

The total number of tokens in the completion.

totalTokens:

number

The total number of tokens generated.

text:

string

The full text that has been generated.

toolCalls:

ToolCall[]

The tool calls that have been executed.

toolResults:

ToolResult[]

The tool results that have been generated.

warnings:

Warning[] | undefined

Warnings from the model provider (e.g. unsupported settings).

response?:

Response

Response metadata.

Response

id:

string

The response identifier. The AI SDK uses the ID from the provider response when available, and generates an ID otherwise.

model:

string

The model that was used to generate the response. The AI SDK uses the response model from the provider response when available, and the model from the function call otherwise.

timestamp:

Date

The timestamp of the response. The AI SDK uses the response timestamp from the provider response when available, and creates a timestamp otherwise.

headers?:

Record<string, string>

Optional response headers.

isContinued:

boolean

True when there will be a continuation step with a continuation text.

experimental_providerMetadata?:

Record<string,Record<string,JSONValue>> | undefined

Optional metadata from the provider. The outer key is the provider name. The inner values are the metadata. Details depend on the provider.

Returns

text:

string

The generated text by the model.

toolCalls:

array

A list of tool calls made by the model.

toolResults:

array

A list of tool results returned as responses to earlier tool calls.

finishReason:

The reason the model finished generating the text.

usage:

CompletionTokenUsage

The token usage of the generated text.

CompletionTokenUsage

promptTokens:

number

The total number of tokens in the prompt.

completionTokens:

number

The total number of tokens in the completion.

totalTokens:

number

The total number of tokens generated.

request?:

RequestMetadata

Request metadata.

RequestMetadata

body:

string

Raw request HTTP body that was sent to the provider API as a string (JSON should be stringified).

response?:

ResponseMetadata

Response metadata.

ResponseMetadata

id:

string

The response identifier. The AI SDK uses the ID from the provider response when available, and generates an ID otherwise.

model:

string

The model that was used to generate the response. The AI SDK uses the response model from the provider response when available, and the model from the function call otherwise.

timestamp:

Date

The timestamp of the response. The AI SDK uses the response timestamp from the provider response when available, and creates a timestamp otherwise.

headers?:

Record<string, string>

Optional response headers.

messages:

Array<CoreAssistantMessage | CoreToolMessage>

The response messages that were generated during the call. It consists of an assistant message, potentially containing tool calls. When there are tool results, there is an additional tool message with the tool results that are available. If there are tools that do not have execute functions, they are not included in the tool results and need to be added separately.

warnings:

Warning[] | undefined

Warnings from the model provider (e.g. unsupported settings).

experimental_providerMetadata:

Record<string,Record<string,JSONValue>> | undefined

Optional metadata from the provider. The outer key is the provider name. The inner values are the metadata. Details depend on the provider.

steps:

Array<StepResult>

Response information for every step. You can use this to get information about intermediate steps, such as the tool calls or the response headers.

StepResult

stepType:

"initial" | "continue" | "tool-result"

The type of step. The first step is always an "initial" step, and subsequent steps are either "continue" steps or "tool-result" steps.

text:

string

The generated text by the model.

toolCalls:

array

A list of tool calls made by the model.

toolResults:

array

A list of tool results returned as responses to earlier tool calls.

finishReason:

The reason the model finished generating the text.

usage:

CompletionTokenUsage

The token usage of the generated text.

CompletionTokenUsage

promptTokens:

number

The total number of tokens in the prompt.

completionTokens:

number

The total number of tokens in the completion.

totalTokens:

number

The total number of tokens generated.

request?:

RequestMetadata

Request metadata.

RequestMetadata

body:

string

Raw request HTTP body that was sent to the provider API as a string (JSON should be stringified).

response?:

ResponseMetadata

Response metadata.

ResponseMetadata

id:

string

The response identifier. The AI SDK uses the ID from the provider response when available, and generates an ID otherwise.

model:

string

The model that was used to generate the response. The AI SDK uses the response model from the provider response when available, and the model from the function call otherwise.