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---
title: streamText
description: API Reference for streamText.
---
# `streamText()`
Streams text generations from a language model.
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.
```ts
import { streamText } from 'ai';
__PROVIDER_IMPORT__;
const { textStream } = streamText({
model: __MODEL__,
prompt: 'Invent a new holiday and describe its traditions.',
});
for await (const textPart of textStream) {
process.stdout.write(textPart);
}
```
For guidance on `runtimeContext`, `toolsContext`, tool `context`, and sensitive
context filtering, see [Runtime and Tool
Context](/docs/ai-sdk-core/runtime-and-tool-context).
To see `streamText` in action, check out [these examples](#examples).
## Import
<Snippet text={`import { streamText } from "ai"`} prompt={false} />
## API Signature
### Parameters
<PropertiesTable
content={[
{
name: 'model',
type: 'LanguageModel',
description: "The language model to use. Example: openai('gpt-4.1')",
},
{
name: 'instructions',
type: 'Instructions',
description:
'Instructions to use that specify the behavior of the model.',
},
{
name: 'prompt',
type: 'string | Array<SystemModelMessage | UserModelMessage | AssistantModelMessage | ToolModelMessage>',
description: 'The input prompt to generate the text from.',
},
{
name: 'messages',
type: 'Array<SystemModelMessage | UserModelMessage | AssistantModelMessage | ToolModelMessage>',
description:
'A list of messages that represent a conversation. Automatically converts UI messages from the useChat hook.',
properties: [
{
type: 'SystemModelMessage',
parameters: [
{
name: 'role',
type: "'system'",
description: 'The role for the system message.',
},
{
name: 'content',
type: 'string',
description: 'The content of the message.',
},
],
},
{
type: 'UserModelMessage',
parameters: [
{
name: 'role',
type: "'user'",
description: 'The role for the user message.',
},
{
name: 'content',
type: 'string | Array<TextPart | ImagePart | FilePart>',
description: 'The content of the message.',
properties: [
{
type: 'TextPart',
parameters: [
{
name: 'type',
type: "'text'",
description: 'The type of the message part.',
},
{
name: 'text',
type: 'string',
description: 'The text content of the message part.',
},
],
},
{
type: 'ImagePart',
parameters: [
{
name: 'type',
type: "'image'",
description: 'The type of the message part.',
},
{
name: 'image',
type: 'string | Uint8Array | Buffer | ArrayBuffer | URL',
description:
'The image content of the message part. String are either base64 encoded content, base64 data URLs, or http(s) URLs.',
},
{
name: 'mediaType',
type: 'string',
isOptional: true,
description: 'The IANA media type of the image.',
},
],
},
{
type: 'FilePart',
parameters: [
{
name: 'type',
type: "'file'",
description: 'The type of the message part.',
},
{
name: 'data',
type: 'string | Uint8Array | Buffer | ArrayBuffer | URL',
description:
'The file content of the message part. String are either base64 encoded content, base64 data URLs, or http(s) URLs.',
},
{
name: 'mediaType',
type: 'string',
description: 'The IANA media type of the file.',
},
],
},
],
},
],
},
{
type: 'AssistantModelMessage',
parameters: [
{
name: 'role',
type: "'assistant'",
description: 'The role for the assistant message.',
},
{
name: 'content',
type: 'string | Array<TextPart | FilePart | ReasoningPart | ReasoningFilePart | ToolCallPart>',
description: 'The content of the message.',
properties: [
{
type: 'TextPart',
parameters: [
{
name: 'type',
type: "'text'",
description: 'The type of the message part.',
},
{
name: 'text',
type: 'string',
description: 'The text content of the message part.',
},
],
},
{
type: 'ReasoningPart',
parameters: [
{
name: 'type',
type: "'reasoning'",
description: 'The type of the reasoning part.',
},
{
name: 'text',
type: 'string',
description: 'The reasoning text.',
},
],
},
{
type: 'ReasoningFilePart',
parameters: [
{
name: 'type',
type: "'reasoning-file'",
description: 'The type of the message part.',
},
{
name: 'data',
type: 'string | Uint8Array | Buffer | ArrayBuffer | URL',
description:
'The file data. String are either base64 encoded content, base64 data URLs, or http(s) URLs.',
},
{
name: 'mediaType',
type: 'string',
description: 'The IANA media type of the file.',
},
],
},
{
type: 'FilePart',
parameters: [
{
name: 'type',
type: "'file'",
description: 'The type of the message part.',
},
{
name: 'data',
type: 'string | Uint8Array | Buffer | ArrayBuffer | URL',
description:
'The file content of the message part. String are either base64 encoded content, base64 data URLs, or http(s) URLs.',
},
{
name: 'mediaType',
type: 'string',
description: 'The IANA media type of the file.',
},
{
name: 'filename',
type: 'string',
description: 'The name of the file.',
isOptional: true,
},
],
},
{
type: 'ToolCallPart',
parameters: [
{
name: 'type',
type: "'tool-call'",
description: 'The type of the message part.',
},
{
name: 'toolCallId',
type: 'string',
description: 'The id of the tool call.',
},
{
name: 'toolName',
type: 'string',
description:
'The name of the tool, which typically would be the name of the function.',
},
{
name: 'input',
type: 'object based on zod schema',
description:
'Parameters generated by the model to be used by the tool.',
},
],
},
],
},
],
},
{
type: 'ToolModelMessage',
parameters: [
{
name: 'role',
type: "'tool'",
description: 'The role for the assistant message.',
},
{
name: 'content',
type: 'Array<ToolResultPart>',
description: 'The content of the message.',
properties: [
{
type: 'ToolResultPart',
parameters: [
{
name: 'type',
type: "'tool-result'",
description: 'The type of the message part.',
},
{
name: 'toolCallId',
type: 'string',
description:
'The id of the tool call the result corresponds to.',
},
{
name: 'toolName',
type: 'string',
description:
'The name of the tool the result corresponds to.',
},
{
name: 'result',
type: 'unknown',
description:
'The result returned by the tool after execution.',
},
{
name: 'isError',
type: 'boolean',
isOptional: true,
description:
'Whether the result is an error or an error message.',
},
],
},
],
},
],
},
],
},
{
name: 'allowSystemInMessages',
type: 'boolean',
isOptional: true,
description:
'Whether system messages are allowed in the `prompt` or `messages` fields. Defaults to false. System messages in the `instructions` option are always allowed. Enabling this for user-controlled messages can create a prompt injection risk.',
},
{
name: 'tools',
type: 'ToolSet',
description:
'Tools that are accessible to and can be called by the model. The model needs to support calling tools.',
properties: [
{
type: 'Tool',
parameters: [
{
name: 'description',
isOptional: true,
type: 'string | ((options: { context: CONTEXT; experimental_sandbox?: Experimental_SandboxSession }) => string)',
description:
'Information about the purpose of the tool including details on how and when it can be used by the model. Provide a string for a fixed description, or a function to derive the description from the tool-specific context and optional experimental sandbox before each model call.',
},
{
name: 'inputSchema',
type: 'Zod Schema | JSON Schema',
description:
'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).',
},
{
name: 'execute',
isOptional: true,
type: 'async (parameters: T, options: ToolExecutionOptions) => RESULT',
description:
'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.',
properties: [
{
type: 'ToolExecutionOptions',
parameters: [
{
name: 'toolCallId',
type: 'string',
description:
'The ID of the tool call. You can use it e.g. when sending tool-call related information with stream data.',
},
{
name: 'messages',
type: 'ModelMessage[]',
description:
'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.',
},
{
name: 'abortSignal',
type: 'AbortSignal',
description:
'An optional abort signal that indicates that the overall operation should be aborted.',
},
],
},
],
},
],
},
],
},
{
name: 'toolChoice',
isOptional: true,
type: '"auto" | "none" | "required" | { "type": "tool", "toolName": string }',
description:
'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.',
},
{
name: 'maxOutputTokens',
type: 'number',
isOptional: true,
description: 'Maximum number of tokens to generate.',
},
{
name: 'temperature',
type: 'number',
isOptional: true,
description:
'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.',
},
{
name: 'topP',
type: 'number',
isOptional: true,
description:
'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.',
},
{
name: 'topK',
type: 'number',
isOptional: true,
description:
'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.',
},
{
name: 'presencePenalty',
type: 'number',
isOptional: true,
description:
'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.',
},
{
name: 'frequencyPenalty',
type: 'number',
isOptional: true,
description:
'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.',
},
{
name: 'stopSequences',
type: 'string[]',
isOptional: true,
description:
'Sequences that will stop the generation of the text. If the model generates any of these sequences, it will stop generating further text.',
},
{
name: 'seed',
type: 'number',
isOptional: true,
description:
'The seed (integer) to use for random sampling. If set and supported by the model, calls will generate deterministic results.',
},
{
name: 'reasoning',
type: "'provider-default' | 'none' | 'minimal' | 'low' | 'medium' | 'high' | 'xhigh'",
isOptional: true,
description:
"Controls how much reasoning the model performs before generating a response. When omitted, the provider's default behavior is used. `'provider-default'` explicitly requests the provider's default. Providers that do not support reasoning will emit a warning. If reasoning-related `providerOptions` are also set, they take precedence and this parameter is ignored. See the [reasoning guide](/docs/ai-sdk-core/reasoning) for provider-specific mapping details.",
},
{
name: 'maxRetries',
type: 'number',
isOptional: true,
description:
'Maximum number of retries. Set to 0 to disable retries. Default: 2.',
},
{
name: 'abortSignal',
type: 'AbortSignal',
isOptional: true,
description:
'An optional abort signal that can be used to cancel the call.',
},
{
name: 'timeout',
type: 'number | { totalMs?: number; stepMs?: number; chunkMs?: number; toolMs?: number; tools?: { [toolName]Ms?: number } }',
isOptional: true,
description:
'Timeout in milliseconds. Can be specified as a number or as an object with totalMs, stepMs, chunkMs, toolMs, and/or tools properties. totalMs sets the total timeout for the entire call. stepMs sets the timeout for each individual step (LLM call). chunkMs sets the timeout between stream chunks - the call will abort if no new chunk is received within this duration. toolMs sets the default timeout for all tool executions. tools sets per-tool timeout overrides using the pattern {toolName}Ms (e.g. weatherMs, slowApiMs) that take precedence over toolMs - tool names are type-checked for autocomplete. If a tool takes longer than its timeout, it aborts and returns a tool-error so the model can respond or retry. Can be used alongside abortSignal.',
},
{
name: 'headers',
type: 'Record<string, string | undefined>',
isOptional: true,
description:
'Additional HTTP headers to be sent with the request. Only applicable for HTTP-based providers.',
},
{
name: 'telemetry',
type: 'TelemetryOptions',
isOptional: true,
description: 'Telemetry configuration.',
properties: [
{
type: 'TelemetryOptions',
parameters: [
{
name: 'isEnabled',
type: 'boolean',
isOptional: true,
description:
'Enable or disable telemetry. Enabled by default. Set to `false` to opt out.',
},
{
name: 'recordInputs',
type: 'boolean',
isOptional: true,
description:
'Enable or disable input recording. Enabled by default.',
},
{
name: 'recordOutputs',
type: 'boolean',
isOptional: true,
description:
'Enable or disable output recording. Enabled by default.',
},
{
name: 'functionId',
type: 'string',
isOptional: true,
description:
'Identifier for this function. Used to group telemetry data by function.',
},
{
name: 'includeRuntimeContext',
type: '{ [KEY in keyof CONTEXT]?: boolean }',
isOptional: true,
description:
'Top-level runtime context properties that should be included in telemetry. Runtime context properties are excluded unless they are explicitly set to `true`. Lifecycle callbacks and returned results still receive the full `runtimeContext`.',
},
{
name: 'includeToolsContext',
type: '{ [TOOL_NAME in keyof InferToolSetContext<TOOLS>]?: { [KEY in keyof InferToolSetContext<TOOLS>[TOOL_NAME]]?: boolean } }',
isOptional: true,
description:
'Top-level tool context properties that should be included in telemetry, configured per tool. Tool context properties are excluded unless they are explicitly set to `true`. Lifecycle callbacks and returned results still receive the full `toolsContext`.',
},
{
name: 'integrations',
isOptional: true,
type: 'Telemetry | Telemetry[]',
description:
'Per-call telemetry integrations that receive lifecycle events. When provided, these replace any globally registered integrations for this call.',
},
],
},
],
},
{
name: 'experimental_transform',
type: 'StreamTextTransform | Array<StreamTextTransform>',
isOptional: true,
description:
'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.',
properties: [
{
type: 'StreamTextTransform',
parameters: [
{
name: 'transform',
type: '(options: TransformOptions) => TransformStream<TextStreamPart<TOOLS>, TextStreamPart<TOOLS>>',
description: 'A transformation that is applied to the stream.',
properties: [
{
type: 'TransformOptions',
parameters: [
{
name: 'stopStream',
type: '() => void',
description: 'A function that stops the stream.',
},
{
name: 'tools',
type: 'TOOLS',
description: 'The tools that are available.',
},
],
},
],
},
],
},
],
},
{
name: 'includeRawChunks',
type: 'boolean',
isOptional: true,
description:
'Deprecated. Use include.rawChunks instead. 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.',
},
{
name: 'providerOptions',
type: 'Record<string,JSONObject> | undefined',
isOptional: true,
description:
'Provider-specific options. The outer key is the provider name. The inner values are the metadata. Details depend on the provider.',
},
{
name: 'activeTools',
type: 'ActiveTools<TOOLS>',
isOptional: true,
description:
'Limits the tools that are available for the model to call without changing the tool call and result types in the result. All tools are active by default. Tool names are restricted to the string keys of the tool set.',
},
{
name: 'toolOrder',
type: 'ToolOrder<TOOLS>',
isOptional: true,
description:
'Controls the order in which tools are sent to the provider. The list can be partial. Tools not listed in `toolOrder` are sent after the listed tools, sorted alphabetically. Tool names are restricted to the string keys of the tool set.',
},
{
name: 'toolApproval',
type: 'ToolApprovalConfiguration<TOOLS, RUNTIME_CONTEXT>',
isOptional: true,
description:
"Approval configuration for this call. Pass a `GenericToolApprovalFunction` to handle all tool calls in one callback with `toolCall`, `tools`, `toolsContext`, `messages`, and `runtimeContext`, or pass a per-tool object where each key can be a status (`'not-applicable'`, `'approved'`, `'denied'`, or `'user-approval'`), an object form such as `{ type: 'denied', reason: 'blocked by policy' }`, or a `SingleToolApprovalFunction` that receives the tool input and options `toolCallId`, `messages`, `toolContext`, and `runtimeContext` (same shape as tool execution options without `abortSignal`, with `context` renamed to `toolContext`). The `RUNTIME_CONTEXT` type parameter matches the call's `runtimeContext`. A `GenericToolApprovalFunction` or `SingleToolApprovalFunction` may return `undefined` for the same effect as `'not-applicable'`. `'not-applicable'` is the default execution path and runs the tool without approval metadata. Use `'approved'`, `'denied'`, or their object forms when you want explicit automatic approval request/response parts in the output. Automatic approvals and denials can include a `reason`, which is forwarded to the emitted approval response. This setting takes precedence over a tool's `needsApproval` default.",
},
{
name: 'experimental_refineToolInput',
type: 'ToolInputRefinement<TOOLS>',
isOptional: true,
description:
'Optional mapping of tool names to functions that refine parsed tool inputs. Each function receives the typed input for its tool and must return the same input type shape. The refined input is used for tool execution, stream parts, lifecycle callbacks, and telemetry.',
},
{
name: 'stopWhen',
type: 'StopCondition<TOOLS> | Array<StopCondition<TOOLS>>',
isOptional: true,
description:
'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: isStepCount(1).',
},
{
name: 'prepareStep',
type: '(options: PrepareStepOptions) => PrepareStepResult<TOOLS> | Promise<PrepareStepResult<TOOLS>>',
isOptional: true,
description:
'Optional function that you can use to provide different settings for a step. You can modify the model, tool choices, active tools, instructions, input messages, and experimental sandbox for each step.',
properties: [
{
type: 'PrepareStepFunction<TOOLS>',
parameters: [
{
name: 'options',
type: 'object',
description: 'The options for the step.',
properties: [
{
type: 'PrepareStepOptions',
parameters: [
{
name: 'steps',
type: 'Array<StepResult<TOOLS>>',
description: 'The steps that have been executed so far.',
},
{
name: 'stepNumber',
type: 'number',
description:
'The number of the step that is being executed.',
},
{
name: 'model',
type: 'LanguageModel',
description: 'The model that is being used.',
},
{
name: 'instructions',
type: 'Instructions | undefined',
description:
'The instructions that will be sent to the model for the current step. If prepareStep returns an instructions override, those instructions carry forward to later steps.',
},
{
name: 'initialInstructions',
type: 'Instructions | undefined',
description:
'The initial instructions that were passed into generateText or streamText.',
},
{
name: 'messages',
type: 'Array<ModelMessage>',
description:
'The messages that will be sent to the model for the current step. If prepareStep returns a messages override, those messages carry forward to later steps.',
},
{
name: 'runtimeContext',
type: 'CONTEXT',
isOptional: true,
description:
'The shared runtime context passed via the `runtimeContext` setting.',
},
{
name: 'toolsContext',
type: 'InferToolSetContext<TOOLS>',
description:
'The per-tool context map passed via the `toolsContext` setting.',
},
{
name: 'experimental_sandbox',
type: 'Experimental_SandboxSession | undefined',
isOptional: true,
description:
'The experimental sandbox environment passed via the `experimental_sandbox` setting.',
},
],
},
],
},
],
},
{
type: 'PrepareStepResult<TOOLS>',
description:
'Return value that can modify settings for the current step.',
parameters: [
{
name: 'model',
type: 'LanguageModel',
isOptional: true,
description:
'Optionally override which LanguageModel instance is used for this step.',
},
{
name: 'toolChoice',
type: 'ToolChoice<TOOLS>',
isOptional: true,
description:
'Optionally set which tool the model must call, or provide tool call configuration for this step.',
},
{
name: 'activeTools',
type: 'ActiveTools<TOOLS>',
isOptional: true,
description:
'If provided, only these tools are enabled/available for this step.',
},
{
name: 'toolOrder',
type: 'ToolOrder<TOOLS>',
isOptional: true,
description:
'If provided, overrides the order in which tools are sent to the provider for this step. Tools not listed are appended alphabetically.',
},
{
name: 'instructions',
type: 'Instructions',
isOptional: true,
description:
'Optionally override the instructions sent to the model for this step. The override carries forward to later steps until prepareStep returns another instructions or system override.',
},
{
name: 'messages',
type: 'Array<ModelMessage>',
isOptional: true,
description:
'Optionally override the full set of messages sent to the model for this step.',
},
{
name: 'runtimeContext',
type: 'CONTEXT',
isOptional: true,
description:
'Shared runtime context. Changing it will affect this step and all subsequent steps.',
},
{
name: 'toolsContext',
type: 'InferToolSetContext<TOOLS>',
description:
'Per-tool context map. Changing it will affect tool-specific context in this step and all subsequent steps.',
},
{
name: 'experimental_sandbox',
type: 'Experimental_SandboxSession',
isOptional: true,
description:
'Experimental sandbox environment for this step. Changing it will affect tool execution in this step only.',
},
{
name: 'providerOptions',
type: 'ProviderOptions',
isOptional: true,
description:
'Additional provider-specific options for this step. Can be used to pass provider-specific configuration such as container IDs for Anthropic code execution.',
},
],
},
],
},
{
name: 'runtimeContext',
type: 'CONTEXT',
isOptional: true,
description:
'User-defined shared runtime context object passed to `prepareStep` and lifecycle callbacks.',
},
{
name: 'toolsContext',
type: 'InferToolSetContext<TOOLS>',
description:
'Per-tool context map keyed by tool name. Required when at least one tool defines `contextSchema`; not accepted when no tools need context.',
},
{
name: 'experimental_sandbox',
type: 'Experimental_SandboxSession',
isOptional: true,
description:
'Experimental sandbox environment that is passed through to `prepareStep`, tool description functions, and tool execution. Tools can access it from their description function options and execution options.',
},
{
name: 'experimental_download',
type: '(requestedDownloads: Array<{ url: URL; isUrlSupportedByModel: boolean }>) => Promise<Array<null | { data: Uint8Array; mediaType?: string }>>',
isOptional: true,
description:
'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.',
},
{
name: 'include',
type: '{ requestBody?: boolean; requestMessages?: boolean; rawChunks?: boolean }',
isOptional: true,
description:
'Controls inclusion of request body and request messages in step results, and raw provider chunks in the stream. By default, request body, request messages, and raw chunks are excluded to reduce memory usage. Set requestBody or requestMessages to true when you need access to the data. Set rawChunks to true when you need access to raw provider chunks.',
properties: [
{
type: 'Object',
parameters: [
{
name: 'requestBody',
type: 'boolean',
isOptional: true,
description:
'Whether to include the request body in step results. The request body can be large when sending images or files. Default: false.',
},
{
name: 'requestMessages',
type: 'boolean',
isOptional: true,
description:
'Whether to include the request messages in step results. The request messages can be large when sending images or files. Default: false.',
},
{
name: 'rawChunks',
type: 'boolean',
isOptional: true,
description:
'Whether to include raw chunks from the provider in the stream. When enabled, raw chunks with type "raw" contain unprocessed provider data. Default: false.',
},
],
},
],
},
{
name: 'repairToolCall',
type: '(options: ToolCallRepairOptions) => Promise<LanguageModelV4ToolCall | null>',
isOptional: true,
description:
'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.',
properties: [
{
type: 'ToolCallRepairOptions',
parameters: [
{
name: 'instructions',
type: 'Instructions | undefined',
description: 'The instructions provided to the model.',
},
{
name: 'system',
type: 'Instructions | undefined',
isOptional: true,
description:
'The instructions provided to the model. Deprecated: use `instructions` instead.',
},
{
name: 'messages',
type: 'ModelMessage[]',
description: 'The messages in the current generation step.',
},
{
name: 'toolCall',
type: 'LanguageModelV4ToolCall',
description: 'The tool call that failed to parse.',
},
{
name: 'tools',
type: 'TOOLS',
description: 'The tools that are available.',
},
{
name: 'inputSchema',
type: '(options: { toolName: string }) => JSONSchema7',
description:
'A function that returns the JSON Schema for a tool.',
},
{
name: 'error',
type: 'NoSuchToolError | InvalidToolInputError',
description:
'The error that occurred while parsing the tool call.',
},
],
},
],
},
{
name: 'onChunk',
type: '(event: OnChunkResult) => Promise<void> |void',
isOptional: true,
description:
'Callback that is called for each stream part. The stream processing will pause until the callback promise is resolved.',
properties: [
{
type: 'OnChunkResult',
parameters: [
{
name: 'chunk',
type: 'TextStreamPart<TOOLS>',
description:
'The stream part. This is the same union as `stream` and includes `start`, `start-step`, `text-start`, `text-delta`, `text-end`, `reasoning-start`, `reasoning-delta`, `reasoning-end`, `custom`, `source`, `file`, `reasoning-file`, `tool-call`, `tool-input-start`, `tool-input-delta`, `tool-input-end`, `tool-result`, `tool-error`, `tool-output-denied`, `tool-approval-request`, `tool-approval-response`, `finish-step`, `finish`, `abort`, `error`, and `raw`.',
properties: [
{
type: 'TextStreamPart',
parameters: [
{
name: 'type',
type: "'text-delta'",
description:
'The type to identify the object as text delta.',
},
{
name: 'text',
type: 'string',
description: 'The text delta.',
},
],
},
{
type: 'TextStreamPart',
parameters: [
{
name: 'type',
type: "'reasoning-delta'",
description:
'The type to identify the object as reasoning delta.',
},
{
name: 'text',
type: 'string',
description: 'The reasoning text delta.',
},
],
},
{
type: 'TextStreamPart',
parameters: [
{
name: 'type',
type: "'source'",
description: 'The type to identify the object as source.',
},
{
name: 'source',
type: 'Source',
description: 'The source.',
},
],
},
{
type: 'TextStreamPart',
parameters: [
{
name: 'type',
type: "'custom'",
description:
'The type to identify the object as custom content.',
},
{
name: 'kind',
type: 'string',
description:
'The kind of custom content, in the format {provider}.{provider-type} (e.g. openai.compaction).',
},
{
name: 'providerMetadata',
type: 'ProviderMetadata',
isOptional: true,
description:
'Optional provider metadata for the custom content.',
},
],
},
{
type: 'TextStreamPart',
parameters: [
{
name: 'type',
type: "'tool-call'",
description:
'The type to identify the object as tool call.',
},
{
name: 'toolCallId',
type: 'string',
description: 'The id of the tool call.',
},
{
name: 'toolName',
type: 'string',
description:
'The name of the tool, which typically would be the name of the function.',
},
{
name: 'input',
type: 'object based on zod schema',
description:
'Parameters generated by the model to be used by the tool.',
},
],
},
{
type: 'TextStreamPart',
parameters: [
{
name: 'type',
type: "'tool-input-start'",
description:
'Indicates the start of streamed tool input.',
},
{
name: 'id',
type: 'string',
description: 'The id of the tool call.',
},
{
name: 'toolName',
type: 'string',
description:
'The name of the tool, which typically would be the name of the function.',
},
],
},
{
type: 'TextStreamPart',
parameters: [
{
name: 'type',
type: "'tool-input-delta'",
description:
'The type to identify the object as streamed tool input delta.',
},
{
name: 'id',
type: 'string',
description: 'The id of the tool call.',
},
{
name: 'toolName',
type: 'string',
description:
'The name of the tool, which typically would be the name of the function.',
},
{
name: 'delta',
type: 'string',
description: 'The text delta of the tool input.',
},
],
},
{
type: 'TextStreamPart',
description: 'The result of a tool call execution.',
parameters: [
{
name: 'type',
type: "'tool-result'",
description:
'The type to identify the object as tool result.',
},
{
name: 'toolCallId',
type: 'string',
description: 'The id of the tool call.',
},
{
name: 'toolName',
type: 'string',
description:
'The name of the tool, which typically would be the name of the function.',
},
{
name: 'input',
type: 'object based on zod schema',
description:
'Parameters generated by the model to be used by the tool.',
},
{
name: 'output',
type: 'any',
description:
'The result returned by the tool after execution has completed.',
},
],
},
],
},
],
},
],
},
{
name: 'onError',
type: '(event: OnErrorResult) => Promise<void> |void',
isOptional: true,
description:
'Callback that is called when an error occurs during streaming. You can use it to log errors.',
properties: [
{
type: 'OnErrorResult',
parameters: [
{
name: 'error',
type: 'unknown',
description: 'The error that occurred.',
},
],
},
],
},
{
name: 'output',
type: 'Output',
isOptional: true,
description:
'Specification for parsing structured outputs from the LLM response.',
properties: [
{
type: 'Output',
parameters: [
{
name: 'Output.text()',
type: 'Output',
description:
'Output specification for text generation (default).',
},
{
name: 'Output.object()',
type: 'Output',
description:
'Output specification for typed object generation using schemas. When the model generates a text response, it will return an object that matches the schema.',
properties: [
{
type: 'Options',
parameters: [
{
name: 'schema',
type: 'Schema<OBJECT>',
description: 'The schema of the object to generate.',
},
{
name: 'name',
type: 'string',
isOptional: true,
description:
'Optional name of the output. Used by some providers for additional LLM guidance.',
},
{
name: 'description',
type: 'string',
isOptional: true,
description:
'Optional description of the output. Used by some providers for additional LLM guidance.',
},
],
},
],
},
{
name: 'Output.array()',
type: 'Output',
description:
'Output specification for array generation. When the model generates a text response, it will return an array of elements.',
properties: [
{
type: 'Options',
parameters: [
{
name: 'element',
type: 'Schema<ELEMENT>',
description:
'The schema of the array elements to generate.',
},
{
name: 'name',
type: 'string',
isOptional: true,
description:
'Optional name of the output. Used by some providers for additional LLM guidance.',
},
{
name: 'description',
type: 'string',
isOptional: true,
description:
'Optional description of the output. Used by some providers for additional LLM guidance.',
},
],
},
],
},
{
name: 'Output.choice()',
type: 'Output',
description:
'Output specification for choice generation. When the model generates a text response, it will return a one of the choice options.',
properties: [
{
type: 'Options',
parameters: [
{
name: 'options',
type: 'Array<string>',
description: 'The available choices.',
},