📄 ai-sdk/docs/reference/ai-sdk-core/stream-text

You can use the streamText function for interactive use cases such as chat bots and other real-time applications. You can also generate UI components with tools.

import { openai } from '@ai-sdk/openai';import { streamText } from 'ai';
const { textStream } = streamText({  model: openai('gpt-4o'),  prompt: 'Invent a new holiday and describe its traditions.',});
for await (const textPart of textStream) {  process.stdout.write(textPart);}

To see streamText in action, check out these examples .

Import

import { streamText } from "ai"

API Signature

Parameters

model:

LanguageModel

The language model to use. Example: openai('gpt-4.1')

system:

string

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

prompt:

string | Array<SystemModelMessage | UserModelMessage | AssistantModelMessage | ToolModelMessage>

The input prompt to generate the text from.

messages:

Array<SystemModelMessage | UserModelMessage | AssistantModelMessage | ToolModelMessage>

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

SystemModelMessage

role:

'system'

The role for the system message.

content:

string

The content of the message.

UserModelMessage

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.

mediaType?:

string

The IANA media type of the image.

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.

mediaType:

string

The IANA media type of the file.

AssistantModelMessage

role:

'assistant'

The role for the assistant message.

content:

string | Array<TextPart | FilePart | ReasoningPart | ToolCallPart>

The content of the message.

TextPart

type:

'text'

The type of the message part.

text:

string

The text content of the message part.

ReasoningPart

type:

'reasoning'

The type of the reasoning part.

text:

string

The reasoning text.

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.

mediaType:

string

The IANA media type of the file.

filename?:

string

The name of the file.

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.

input:

object based on zod schema

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

ToolModelMessage

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:

ToolSet

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

Tool

description?:

string

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

inputSchema:

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:

ModelMessage[]

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.

maxOutputTokens?:

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.

experimental_generateMessageId?:

() => string

Function used to generate a unique ID for each message. This is an experimental feature.

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_transform?:

StreamTextTransform | Array<StreamTextTransform>

Optional stream transformations. They are applied in the order they are provided. The stream transformations must maintain the stream structure for streamText to work correctly.

StreamTextTransform

transform:

(options: TransformOptions) => TransformStream<TextStreamPart<TOOLS>, TextStreamPart<TOOLS>>

A transformation that is applied to the stream.

TransformOptions

stopStream:

() => void

A function that stops the stream.

tools:

TOOLS

The tools that are available.

includeRawChunks?:

boolean

Whether to include raw chunks from the provider in the stream. When enabled, you will receive raw chunks with type "raw" that contain the unprocessed data from the provider. This allows access to cutting-edge provider features not yet wrapped by the AI SDK. Defaults to false.

providerOptions?:

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

Provider-specific options. The outer key is the provider name. The inner values are the metadata. Details depend on the provider.

activeTools?:

Array<TOOLNAME> | undefined

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

stopWhen?:

StopCondition<TOOLS> | Array<StopCondition<TOOLS>>

Condition for stopping the generation when there are tool results in the last step. When the condition is an array, any of the conditions can be met to stop the generation. Default: stepCountIs(1).

prepareStep?:

(options: PrepareStepOptions) => PrepareStepResult<TOOLS> | Promise<PrepareStepResult<TOOLS>>

Optional function that you can use to provide different settings for a step. You can modify the model, tool choices, active tools, system prompt, and input messages for each step.

PrepareStepFunction<TOOLS>

options:

object

The options for the step.

PrepareStepOptions

steps:

Array<StepResult<TOOLS>>

The steps that have been executed so far.

stepNumber:

number

The number of the step that is being executed.

model:

LanguageModel

The model that is being used.

messages:

Array<ModelMessage>

The messages that will be sent to the model for the current step.

PrepareStepResult<TOOLS>

model?:

LanguageModel

Change the model for this step.

toolChoice?:

ToolChoice<TOOLS>

Change the tool choice strategy for this step.

activeTools?:

Array<keyof TOOLS>

Change which tools are active for this step.

system?:

string

Change the system prompt for this step.

messages?:

Array<ModelMessage>

Modify the input messages for this step.

experimental_context?:

unknown

Context that is passed into tool execution. Experimental (can break in patch releases).

experimental_download?:

(requestedDownloads: Array<{ url: URL; isUrlSupportedByModel: boolean }>) => Promise<Array<null | { data: Uint8Array; mediaType?: string }>>

Custom download function to control how URLs are fetched when they appear in prompts. By default, files are downloaded if the model does not support the URL for the given media type. Experimental feature. Return null to pass the URL directly to the model (when supported), or return downloaded content with data and media type.

experimental_repairToolCall?:

(options: ToolCallRepairOptions) => Promise<LanguageModelV2ToolCall | 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:

ModelMessage[]

The messages in the current generation step.

toolCall:

LanguageModelV2ToolCall

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 | InvalidToolInputError

The error that occurred while parsing the tool call.

onChunk?:

(event: OnChunkResult) => Promise<void> |void

Callback that is called for each chunk of the stream. The stream processing will pause until the callback promise is resolved.

OnChunkResult

chunk:

TextStreamPart

The chunk of the stream.

TextStreamPart

type:

'text'

The type to identify the object as text delta.

text:

string

The text delta.

TextStreamPart

type:

'reasoning'

The type to identify the object as reasoning.

text:

string

The reasoning text delta.

TextStreamPart

type:

'source'

The type to identify the object as source.

source:

Source

The source.

TextStreamPart

type:

'tool-call'

The type to identify the object as tool call.

toolCallId:

string

The id of the tool call.

toolName:

string

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

input:

object based on zod schema

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

TextStreamPart

type:

'tool-call-streaming-start'

Indicates the start of a tool call streaming. Only available when streaming tool calls.

toolCallId:

string

The id of the tool call.

toolName:

string

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

TextStreamPart

type:

'tool-call-delta'

The type to identify the object as tool call delta. Only available when streaming tool calls.

toolCallId:

string

The id of the tool call.

toolName:

string

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

argsTextDelta:

string

The text delta of the tool call arguments.

TextStreamPart

type:

'tool-result'

The type to identify the object as tool result.

toolCallId:

string

The id of the tool call.

toolName:

string

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

input:

object based on zod schema

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

output:

any

The result returned by the tool after execution has completed.

onError?:

(event: OnErrorResult) => Promise<void> |void

Callback that is called when an error occurs during streaming. You can use it to log errors.

OnErrorResult

error:

unknown

The error that occurred.

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:

LanguageModelUsage

The token usage of the step.

LanguageModelUsage

inputTokens:

number | undefined

The number of input (prompt) tokens used.

outputTokens:

number | undefined

The number of output (completion) tokens used.

totalTokens:

number | undefined

The total number of tokens as reported by the provider. This number might be different from the sum of inputTokens and outputTokens and e.g. include reasoning tokens or other overhead.

reasoningTokens?:

number | undefined

The number of reasoning tokens used.

cachedInputTokens?:

number | undefined

The number of cached input tokens.

text:

string

The full text that has been generated.

reasoning:

string | undefined

The reasoning text of the model (only available for some models).

sources:

Array<Source>

Sources that have been used as input to generate the response. For multi-step generation, the sources are accumulated from all steps.

Source

sourceType:

'url'

A URL source. This is return by web search RAG models.

id:

string

The ID of the source.

url:

string

The URL of the source.

title?:

string

The title of the source.

providerMetadata?:

SharedV2ProviderMetadata

Additional provider metadata for the source.

files:

Array<GeneratedFile>

All files that were generated in this step.

GeneratedFile

base64:

string

File as a base64 encoded string.

uint8Array:

Uint8Array

File as a Uint8Array.

mediaType:

string

The IANA media type of the file.

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.

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.

onFinish?:

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

Callback that is called when the LLM response and all request tool executions (for tools that have an `execute` function) are finished.

OnFinishResult

finishReason:

The reason the model finished generating the text.

usage:

LanguageModelUsage

The token usage of the generated text.

LanguageModelUsage

inputTokens:

number | undefined

The number of input (prompt) tokens used.

outputTokens:

number | undefined

The number of output (completion) tokens used.

totalTokens:

number | undefined

The total number of tokens as reported by the provider. This number might be different from the sum of inputTokens and outputTokens and e.g. include reasoning tokens or other overhead.

reasoningTokens?:

number | undefined

The number of reasoning tokens used.

cachedInputTokens?:

number | undefined

The number of cached input tokens.

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.

text:

string

The full text that has been generated.

reasoning:

string | undefined

The reasoning text of the model (only available for some models).

reasoningDetails:

Array<ReasoningDetail>

The reasoning details of the model (only available for some models).

ReasoningDetail

type:

'text'

The type of the reasoning detail.

text:

string

The text content (only for type "text").

signature?:

string

Optional signature (only for type "text").

ReasoningDetail

type:

'redacted'

The type of the reasoning detail.

data:

string

The redacted data content (only for type "redacted").

sources:

Array<Source>

Sources that have been used as input to generate the response. For multi-step generation, the sources are accumulated from all steps.

Source

sourceType:

'url'

A URL source. This is return by web search RAG models.

id:

string

The ID of the source.

url:

string

The URL of the source.

title?:

string

The title of the source.

providerMetadata?:

SharedV2ProviderMetadata

Additional provider metadata for the source.

files:

Array<GeneratedFile>

Files that were generated in the final step.

GeneratedFile

base64:

string

File as a base64 encoded string.

uint8Array:

Uint8Array

File as a Uint8Array.

mediaType:

string

The IANA media type of the file.

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.

messages:

Array<ResponseMessage>

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.

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.

onAbort?:

(event: OnAbortResult) => Promise<void> | void

Callback that is called when a stream is aborted via AbortSignal. You can use it to perform cleanup operations.

OnAbortResult

steps:

Array<StepResult>

Details for all previously finished steps.

Returns

content:

Promise<Array<ContentPart<TOOLS>>>

The content that was generated in the last step. Automatically consumes the stream.

finishReason:

The reason why the generation finished. Automatically consumes the stream.

usage:

Promise<LanguageModelUsage>

The token usage of the last step. Automatically consumes the stream.

LanguageModelUsage

inputTokens:

number | undefined

The number of input (prompt) tokens used.

outputTokens:

number | undefined

The number of output (completion) tokens used.

totalTokens:

number | undefined

The total number of tokens as reported by the provider. This number might be different from the sum of inputTokens and outputTokens and e.g. include reasoning tokens or other overhead.

reasoningTokens?:

number | undefined

The number of reasoning tokens used.

cachedInputTokens?:

number | undefined

The number of cached input tokens.

totalUsage:

Promise<LanguageModelUsage>

The total token usage of the generated response. When there are multiple steps, the usage is the sum of all step usages. Automatically consumes the stream.

LanguageModelUsage

inputTokens:

number | undefined

The number of input (prompt) tokens used.

outputTokens:

number | undefined

The number of output (completion) tokens used.

totalTokens:

number | undefined

The total number of tokens as reported by the provider. This number might be different from the sum of inputTokens and outputTokens and e.g. include reasoning tokens or other overhead.

reasoningTokens?:

number | undefined

The number of reasoning tokens used.

cachedInputTokens?:

number | undefined

The number of cached input tokens.

providerMetadata:

Promise<ProviderMetadata | undefined>

Additional provider-specific metadata from the last step. Metadata is passed through from the provider to the AI SDK and enables provider-specific results that can be fully encapsulated in the provider.

text:

Promise<string>

The full text that has been generated. Automatically consumes the stream.

reasoning:

Promise<Array<ReasoningOutput>>

The full reasoning that the model has generated in the last step. Automatically consumes the stream.

ReasoningOutput

type:

'reasoning'

The type of the message part.

text:

string

The reasoning text.

providerMetadata?:

SharedV2ProviderMetadata

Additional provider metadata for the source.

reasoningText:

Promise<string | undefined>

The reasoning text that the model has generated in the last step. Can be undefined if the model has only generated text. Automatically consumes the stream.

sources:

Promise<Array<Source>>

Sources that have been used as input to generate the response. For multi-step generation, the sources are accumulated from all steps. Automatically consumes the stream.

Source

sourceType:

'url'

A URL source. This is return by web search RAG models.

id:

string

The ID of the source.

url:

string

The URL of the source.

title?:

string

The title of the source.

providerMetadata?:

SharedV2ProviderMetadata

Additional provider metadata for the source.

files:

Promise<Array<GeneratedFile>>

Files that were generated in the final step. Automatically consumes the stream.

GeneratedFile

base64:

string

File as a base64 encoded string.

uint8Array:

Uint8Array

File as a Uint8Array.

mediaType:

string

The IANA media type of the file.

toolCalls:

Promise<TypedToolCall<TOOLS>[]>

The tool calls that have been executed. Automatically consumes the stream.

toolResults:

Promise<TypedToolResult<TOOLS>[]>

The tool results that have been generated. Resolved when the all tool executions are finished.

request:

Promise<LanguageModelRequestMetadata>

Additional request information from the last step.

LanguageModelRequestMetadata

body:

string

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

response:

Promise<LanguageModelResponseMetadata & { messages: Array<ResponseMessage>; }>

Additional response information from the last step.

LanguageModelResponseMetadata

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<ResponseMessage>

warnings:

Promise<CallWarning[] | undefined>

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

steps:

Promise<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.

reasoning:

string | undefined

The reasoning text of the model (only available for some models).

sources:

Array<Source>

Sources that have been used as input.

Source

sourceType:

'url'

A URL source. This is return by web search RAG models.

id:

string

The ID of the source.

url:

string

The URL of the source.

title?:

string

The title of the source.

providerMetadata?:

SharedV2ProviderMetadata

Additional provider metadata for the source.

files:

Array<GeneratedFile>

Files that were generated in this step.

GeneratedFile

base64:

string

File as a base64 encoded string.

uint8Array:

Uint8Array

File as a Uint8Array.

mediaType:

string

The IANA media type of the file.

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:

LanguageModelUsage

The token usage of the generated text.

LanguageModelUsage

inputTokens:

number | undefined

The number of input (prompt) tokens used.

outputTokens:

number | undefined

The number of output (completion) tokens used.

totalTokens:

number | undefined

The total number of tokens as reported by the provider. This number might be different from the sum of inputTokens and outputTokens and e.g. include reasoning tokens or other overhead.

reasoningTokens?:

number | undefined

The number of reasoning tokens used.

cachedInputTokens?:

number | undefined

The number of cached input tokens.

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<ResponseMessage>

warnings:

Warning[] | undefined

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

isContinued:

boolean

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

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.

textStream:

AsyncIterableStream<string>

A text stream that returns only the generated text deltas. You can use it as either an AsyncIterable or a ReadableStream. When an error occurs, the stream will throw the error.

fullStream:

AsyncIterable<TextStreamPart<TOOLS>> & ReadableStream<TextStreamPart<TOOLS>>

A stream with all events, including text deltas, tool calls, tool results, and errors. You can use it as either an AsyncIterable or a ReadableStream. Only errors that stop the stream, such as network errors, are thrown.

TextStreamPart

type:

'text'

The type to identify the object as text.

text:

string

The text content.

TextStreamPart

type:

'reasoning'

The type to identify the object as reasoning.

text:

string

The reasoning text.

providerMetadata?:

ProviderMetadata

Optional provider metadata for the reasoning.

TextStreamPart

type:

'source'

The type to identify the object as source.

sourceType:

'url'

A URL source. This is returned by web search RAG models.

id:

string

The ID of the source.

url:

string

The URL of the source.

title?:

string

The title of the source.

providerMetadata?:

ProviderMetadata

Additional provider metadata for the source.

TextStreamPart

type:

'file'

The type to identify the object as file.

file:

GeneratedFile

The file.

GeneratedFile

base64:

string

File as a base64 encoded string.

uint8Array:

Uint8Array

File as a Uint8Array.

mediaType:

string

The IANA media type of the file.

TextStreamPart

type:

'tool-call'

The type to identify the object as tool call.

toolCallId:

string

The id of the tool call.

toolName:

string

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

input:

object based on tool parameters

Parameters generated by the model to be used by the tool. The type is inferred from the tool definition.

TextStreamPart

type:

'tool-call-streaming-start'

Indicates the start of a tool call streaming. Only available when streaming tool calls.

toolCallId:

string

The id of the tool call.

toolName:

string

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

TextStreamPart

type:

'tool-call-delta'

The type to identify the object as tool call delta. Only available when streaming tool calls.

toolCallId:

string

The id of the tool call.

toolName:

string

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

argsTextDelta:

string

The text delta of the tool call arguments.

TextStreamPart

type:

'tool-result'

The type to identify the object as tool result.

toolCallId:

string

The id of the tool call.

toolName:

string

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

input:

object based on tool parameters

Parameters that were passed to the tool. The type is inferred from the tool definition.

output:

tool execution return type

The result returned by the tool after execution has completed. The type is inferred from the tool execute function return type.

TextStreamPart

type:

'start-step'

Indicates the start of a new step in the stream.

request:

LanguageModelRequestMetadata

Information about the request that was sent to the language model provider.

LanguageModelRequestMetadata

body:

string

Raw request HTTP body that was sent to the provider API as a string.

warnings:

CallWarning[]

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

TextStreamPart

type:

'finish-step'

Indicates the end of the current step in the stream.

response:

LanguageModelResponseMetadata

Response metadata from the language model provider.

LanguageModelResponseMetadata

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>

The response headers.

usage:

LanguageModelUsage

The token usage of the generated text.

LanguageModelUsage

inputTokens:

number | undefined

The number of input (prompt) tokens used.

outputTokens:

number | undefined

The number of output (completion) tokens used.

totalTokens:

number | undefined

The total number of tokens as reported by the provider. This number might be different from the sum of inputTokens and outputTokens and e.g. include reasoning tokens or other overhead.

reasoningTokens?:

number | undefined

The number of reasoning tokens used.

cachedInputTokens?:

number | undefined

The number of cached input tokens.

finishReason:

The reason the model finished generating the text.

providerMetadata?:

ProviderMetadata | undefined

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

TextStreamPart

type:

'start'

Indicates the start of the stream.

TextStreamPart

type:

'finish'

The type to identify the object as finish.

finishReason:

The reason the model finished generating the text.

totalUsage:

LanguageModelUsage

The total token usage of the generated text.

LanguageModelUsage

inputTokens:

number | undefined

The number of input (prompt) tokens used.

outputTokens:

number | undefined

The number of output (completion) tokens used.

totalTokens:

number | undefined

The total number of tokens as reported by the provider. This number might be different from the sum of inputTokens and outputTokens and e.g. include reasoning tokens or other overhead.

reasoningTokens?:

number | undefined

The number of reasoning tokens used.

cachedInputTokens?:

number | undefined

The number of cached input tokens.

TextStreamPart

type:

'reasoning-part-finish'

Indicates the end of a reasoning part.

TextStreamPart

type:

'error'

The type to identify the object as error.

error:

unknown

Describes the error that may have occurred during execution.

TextStreamPart

type:

'abort'

The type to identify the object as abort.

experimental_partialOutputStream:

AsyncIterableStream<PARTIAL_OUTPUT>

A stream of partial outputs. It uses the `experimental_output` specification. AsyncIterableStream is defined as AsyncIterable<T> & ReadableStream<T>.

consumeStream:

(options?: ConsumeStreamOptions) => Promise<void>

Consumes the stream without processing the parts. This is useful to force the stream to finish. If an error occurs, it is passed to the optional `onError` callback.

ConsumeStreamOptions

onError?:

(error: unknown) => void

The error callback.

toUIMessageStream:

(options?: UIMessageStreamOptions) => AsyncIterableStream<UIMessageChunk>

Converts the result to a UI message stream. Returns an AsyncIterableStream that can be used as both an AsyncIterable and a ReadableStream.

UIMessageStreamOptions

originalMessages?:

UIMessage[]

The original messages.

onFinish?:

(options: { messages: UIMessage[]; isContinuation: boolean; responseMessage: UIMessage; isAborted: boolean; }) => void

Callback function called when the stream finishes. Provides the updated list of UI messages, whether the response is a continuation, the response message, and whether the stream was aborted.

messageMetadata?:

(options: { part: TextStreamPart<TOOLS> & { type: "start" | "finish" | "start-step" | "finish-step"; }; }) => unknown

Extracts message metadata that will be sent to the client. Called on start and finish events.

sendReasoning?:

boolean

Send reasoning parts to the client. Defaults to false.

sendSources?:

boolean

Send source parts to the client. Defaults to false.

sendFinish?:

boolean

Send the finish event to the client. Defaults to true.

sendStart?:

boolean

Send the message start event to the client. Set to false if you are using additional streamText calls and the message start event has already been sent. Defaults to true.

onError?:

(error: unknown) => string

Process an error, e.g. to log it. Returns error message to include in the data stream. Defaults to () => "An error occurred."

consumeSseStream?:

(stream: ReadableStream) => Promise<void>

Function to consume the SSE stream. Required for proper abort handling in UI message streams. Use the `consumeStream` function from the AI SDK.

pipeUIMessageStreamToResponse:

(response: ServerResponse, options?: ResponseInit & UIMessageStreamOptions) => void

Writes UI message stream output to a Node.js response-like object.

ResponseInit & UIMessageStreamOptions

status?:

number

The response status code.

statusText?:

string

The response status text.

headers?:

HeadersInit

The response headers.

pipeTextStreamToResponse:

(response: ServerResponse, init?: ResponseInit) => void

Writes text delta output to a Node.js response-like object. It sets a `Content-Type` header to `text/plain; charset=utf-8` and writes each text delta as a separate chunk.

ResponseInit