AI
AI SDK CorestreamObject

streamObject()

Streams a typed, structured object for a given prompt and zod schema using a language model.

It can be used to force the language model to return structured data, e.g. for information extraction, synthetic data generation, or classification tasks.

import { openai } from '@ai-sdk/openai';
import { streamObject } from 'ai';
import { z } from 'zod';


const { partialObjectStream } = await streamObject({
  model: openai('gpt-4-turbo'),
  schema: z.object({
    recipe: z.object({
      name: z.string(),
      ingredients: z.array(z.string()),
      steps: z.array(z.string()),
    }),
  }),
  prompt: 'Generate a lasagna recipe.',
});


for await (const partialObject of partialObjectStream) {
  console.clear();
  console.log(partialObject);
}

Import 

import { streamObject } from "ai"

API Signature

Parameters

model:

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

mode:

'auto' | 'json' | 'tool'
The mode to use for object generation. Not every model supports all modes. Defaults to 'auto'.

schema:

Zod Schema | JSON Schema
The schema that describes the shape of the object to generate. It is sent to the model to generate the object and used to validate the output. You can either pass in a Zod schema or a JSON schema (using the `jsonSchema` function).

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>
A list of messages that represent a conversation.
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>
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.
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.

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.

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_telemetry?:

TelemetrySettings
Telemetry configuration. Experimental feature.
TelemetrySettings

isEnabled?:

boolean
Enable or disable telemetry. Disabled by default while experimental.

functionId?:

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

metadata?:

Record<string, string | number | boolean | Array<null | undefined | string> | Array<null | undefined | number> | Array<null | undefined | boolean>>
Additional information to include in the telemetry data.

onFinish?:

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

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.

object:

T | undefined
The generated object (typed according to the schema). Can be undefined if the final object does not match the schema.

error:

unknown | undefined
Optional error object. This is e.g. a TypeValidationError when the final object does not match the schema.

warnings:

Warning[] | undefined
Warnings from the model provider (e.g. unsupported settings).

rawResponse:

RawResponse
Optional raw response data.
RawResponse

headers:

Record<string, string>
Response headers.

Returns

usage:

Promise<CompletionTokenUsage>
The token usage of the generated text. Resolved when the response is finished.
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.

object:

Promise<T>
The generated object (typed according to the schema). Resolved when the response is finished.

partialObjectStream:

AsyncIterableStream<DeepPartial<T>>
Stream of partial objects. It gets more complete as the stream progresses. Note that the partial object is not validated. If you want to be certain that the actual content matches your schema, you need to implement your own validation for partial results.

textStream:

AsyncIterableStream<string>
Text stream of the JSON representation of the generated object. It contains text chunks. When the stream is finished, the object is valid JSON that can be parsed.

fullStream:

AsyncIterableStream<ObjectStreamPart<T>>
Stream of different types of events, including partial objects, errors, and finish events. Only errors that stop the stream, such as network errors, are thrown.
ObjectPart

type:

'object'

object:

DeepPartial<T>
The partial object that was generated.
TextDeltaPart

type:

'text-delta'

textDelta:

string
The text delta for the underlying raw JSON text.
ErrorPart

type:

'error'

error:

unknown
The error that occurred.
FinishPart

type:

'finish'

finishReason:

FinishReason

logprobs:

Logprobs

usage:

Usage
Token usage.

rawResponse:

RawResponse
Optional raw response data.
RawResponse

headers:

Record<string, string>
Response headers.

warnings:

Warning[] | undefined
Warnings from the model provider (e.g. unsupported settings).

pipeTextStreamToResponse:

(response: ServerResponse, init?: { headers?: Record<string, string>; status?: number } => 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.

toTextStreamResponse:

(init?: ResponseInit) => Response
Creates a simple text stream response. Each text delta is encoded as UTF-8 and sent as a separate chunk. Non-text-delta events are ignored.

Examples