AI SDK CorestreamText
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.
Import
import { streamText } from "ai"
Parameters
model:
The language model to use. Example: openai('gpt-4-turbo')
system:
The system prompt to use that specifies the behavior of the model.
prompt:
The input prompt to generate the text from.
messages:
A list of messages that represent a conversation.
CoreUserMessage
role:
The role for the user message.
content:
The content of the message.
TextPart
type:
The type of the message part.
text:
The text content of the message part.
ImagePart
type:
The type of the message part.
image:
The image content of the message part.
CoreAssistantMessage
role:
The role for the assistant message.
content:
The content of the message.
TextPart
type:
The type of the message part.
text:
The text content of the message part.
ToolCallPart
type:
The type of the message part.
toolCallId:
The id of the tool call.
toolName:
The name of the tool, which typically would be the name of the function.
args:
Parameters generated by the model to be used by the tool.
CoreToolMessage
role:
The role for the assistant message.
content:
The content of the message.
ToolResultPart
type:
The type of the message part.
toolCallId:
The id of the tool call the result corresponds to.
toolName:
The name of the tool the result corresponds to.
result:
The result returned by the tool after execution.
isError?:
Whether the result is an error or an error message.
tools:
Tools that are accessible to and can be called by the model. The model needs to support calling tools.
CoreTool
description?:
Information about the purpose of the tool including details on how and when it can be used by the model.
parameters:
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.
execute?:
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.
maxTokens?:
Maximum number of tokens to generate.
temperature?:
Temperature setting. The value is passed through to the provider. The range depends on the provider and model. It is recommended to set either `temperature` or `topP`, but not both.
topP?:
Nucleus sampling. The value is passed through to the provider. The range depends on the provider and model. It is recommended to set either `temperature` or `topP`, but not both.
presencePenalty?:
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?:
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?:
The seed (integer) to use for random sampling. If set and supported by the model, calls will generate deterministic results.
maxRetries?:
Maximum number of retries. Set to 0 to disable retries. Default: 2.
abortSignal?:
An optional abort signal that can be used to cancel the call.
Result Object
finishReason:
The reason why the generation finished. Resolved when the response is finished.
usage:
The token usage of the generated text. Resolved when the response is finished.
TokenUsage
promptTokens:
The total number of tokens in the prompt.
completionTokens:
The total number of tokens in the completion.
totalTokens:
The total number of tokens generated.
rawResponse:
Optional raw response data.
RawResponse
header:
Response headers.
warnings:
Warnings from the model provider (e.g. unsupported settings).
textStream:
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:
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. When an error occurs, the stream will throw the error.
TextStreamPart
type:
The type to identify the object as text delta.
textDelta:
The text delta.
TextStreamPart
type:
The type to identify the object as tool call.
toolCallId:
The id of the tool call.
toolName:
The name of the tool, which typically would be the name of the function.
args:
Parameters generated by the model to be used by the tool.
TextStreamPart
type:
The type to identify the object as tool result.
toolCallId:
The id of the tool call.
toolName:
The name of the tool, which typically would be the name of the function.
args:
Parameters generated by the model to be used by the tool.
result:
The result returned by the tool after execution has completed.
TextStreamPart
type:
The type to identify the object as error.
error:
Describes the error that may have occurred during execution.
TextStreamPart
type:
The type to identify the object as finish.
finishReason:
The reason the model finished generating the text.
usage:
The token usage of the generated text.
TokenUsage
promptTokens:
The total number of tokens in the prompt.
completionTokens:
The total number of tokens in the completion.
totalTokens:
The total number of tokens generated.
toAIStream:
Converts the result to an `AIStream` object that is compatible with `StreamingTextResponse`. It can be used with the `useChat` and `useCompletion` hooks.
pipeAIStreamToResponse:
Writes stream data output to a Node.js response-like object. It sets a `Content-Type` header to `text/plain; charset=utf-8` and writes each stream data part as a separate chunk.
pipeTextStreamToResponse:
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.
toAIStreamResponse:
Converts the result to a streamed response object with a stream data part stream. It can be used with the `useChat` and `useCompletion` hooks.
toTextStreamResponse:
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.