toAISdkStream()
將 Mastra 串流(Agent、網絡或 Workflow)轉換成 AI SDK 兼容串流。當你需要手動轉換 Mastra 串流,以配合 AI SDK 的 createUIMessageStream() 及 createUIMessageStreamResponse() 使用時,請使用此函數。
在 Mastra 所提供的 chatRoute() 或 workflowRoute() 等路由輔助函數以外建立自訂串流端點時,此函數尤其有用。
toAISdkStream() 保留現有的 AI SDK v5/預設行為。如果你的應用程式以 AI SDK v6 型別為準,請在選項物件中傳入 version: 'v6'。
UI 串流中的結構化輸出UI 串流中的結構化輸出 的直接連結
當來源 Agent 串流包含最終結構化輸出物件時,toAISdkStream() 會將其作為自訂 AI SDK UI 資料部分輸出:
{
"type": "data-structured-output",
"data": {
"object": {}
}
}
object 欄位包含完整的結構化輸出值。這會將 Mastra 的最終結構化輸出區塊對應至 AI SDK UI 串流。系統不會輸出部分結構化輸出區塊。
使用範例使用範例 的直接連結
Next.js App Router 範例:
app/api/chat/route.ts
import { mastra } from '../../mastra'
import { createUIMessageStream, createUIMessageStreamResponse } from 'ai'
import { toAISdkStream } from '@mastra/ai-sdk'
export async function POST(req: Request) {
const { messages } = await req.json()
const myAgent = mastra.getAgent('weatherAgent')
const stream = await myAgent.stream(messages)
const uiMessageStream = createUIMessageStream({
originalMessages: messages,
execute: async ({ writer }) => {
for await (const part of toAISdkStream(stream, { from: 'agent' })) {
await writer.write(part)
}
},
})
return createUIMessageStreamResponse({
stream: uiMessageStream,
})
}
提示
在 createUIMessageStream() 中將 messages 傳給 originalMessages,以免 UI 出現重複的助手訊息。詳情請參閱疑難排解:重複的助手訊息。
參數參數 的直接連結
第一個參數是要轉換的 Mastra 串流,可以是以下其中一種:
MastraModelOutput- 來自agent.stream()的 Agent 串流MastraAgentNetworkStream- 來自agent.network()的網絡串流MastraWorkflowStream或WorkflowRunOutput- Workflow 串流
第二個參數是選項物件:
version?:
'v5' | 'v6'
= 'v5'
選擇要輸出的 AI SDK 串流合約。省略此項或傳入
'v5',即可使用現有的預設行為。當你的應用程式以 AI SDK v6 回應輔助函數的型別為準時,請傳入 'v6'。from:
'agent' | 'network' | 'workflow'
= 'agent'
正在轉換的 Mastra 串流類型。
lastMessageId?:
string
(僅限 Agent)對話中最後一則訊息的 ID。
sendStart?:
boolean
= true
(僅限 Agent)是否在串流中傳送開始事件。
sendFinish?:
boolean
= true
(僅限 Agent)是否在串流中傳送完成事件。
sendReasoning?:
boolean
= false
(僅限 Agent)是否在串流中包含 reasoning-delta 區塊。設為 true,可串流支援延伸思考模型的推理內容。
sendSources?:
boolean
= false
(僅限 Agent)是否在輸出中包含來源引文。
includeTextStreamParts?:
boolean
= true
(僅限 Workflow)是否在輸出中包含文字串流部分。
messageMetadata?:
(options: { part: UIMessageStreamPart }) => Record<string, unknown> | undefined
(僅限 Agent)接收目前串流部分,並傳回要附加至開始及完成區塊的中繼資料之函數。
onError?:
(error: unknown) => string
(僅限 Agent)用於處理串流轉換期間錯誤的函數。此函數會接收錯誤,並應傳回其字串表示。
範例範例 的直接連結
轉換 Workflow 串流轉換 Workflow 串流 的直接連結
app/api/workflow/route.ts
import { mastra } from '../../mastra'
import { createUIMessageStream, createUIMessageStreamResponse } from 'ai'
import { toAISdkStream } from '@mastra/ai-sdk'
export async function POST(req: Request) {
const { input } = await req.json()
const workflow = mastra.getWorkflow('myWorkflow')
const run = workflow.createRun()
const stream = await run.stream({ inputData: input })
const uiMessageStream = createUIMessageStream({
execute: async ({ writer }) => {
for await (const part of toAISdkStream(stream, { from: 'workflow' })) {
await writer.write(part)
}
},
})
return createUIMessageStreamResponse({
stream: uiMessageStream,
})
}
轉換網絡串流轉換網絡串流 的直接連結
app/api/network/route.ts
import { mastra } from '../../mastra'
import { createUIMessageStream, createUIMessageStreamResponse } from 'ai'
import { toAISdkStream } from '@mastra/ai-sdk'
export async function POST(req: Request) {
const { messages } = await req.json()
const routingAgent = mastra.getAgent('routingAgent')
const stream = await routingAgent.network(messages)
const uiMessageStream = createUIMessageStream({
execute: async ({ writer }) => {
for await (const part of toAISdkStream(stream, { from: 'network' })) {
await writer.write(part)
}
},
})
return createUIMessageStreamResponse({
stream: uiMessageStream,
})
}
轉換已啟用推理的 Agent 串流轉換已啟用推理的 Agent 串流 的直接連結
app/api/reasoning/route.ts
import { mastra } from '../../mastra'
import { createUIMessageStream, createUIMessageStreamResponse } from 'ai'
import { toAISdkStream } from '@mastra/ai-sdk'
export async function POST(req: Request) {
const { messages } = await req.json()
const reasoningAgent = mastra.getAgent('reasoningAgent')
const stream = await reasoningAgent.stream(messages, {
providerOptions: {
openai: { reasoningEffort: 'high' },
},
})
const uiMessageStream = createUIMessageStream({
originalMessages: messages,
execute: async ({ writer }) => {
for await (const part of toAISdkStream(stream, {
from: 'agent',
sendReasoning: true,
})) {
await writer.write(part)
}
},
})
return createUIMessageStreamResponse({
stream: uiMessageStream,
})
}
為 AI SDK v6 轉換 Agent 串流為 AI SDK v6 轉換 Agent 串流 的直接連結
app/api/chat-v6/route.ts
import { mastra } from '../../mastra'
import { createUIMessageStream, createUIMessageStreamResponse } from 'ai'
import { toAISdkStream } from '@mastra/ai-sdk'
export async function POST(req: Request) {
const { messages } = await req.json()
const myAgent = mastra.getAgent('weatherAgent')
const stream = await myAgent.stream(messages)
const uiMessageStream = createUIMessageStream({
originalMessages: messages,
execute: async ({ writer }) => {
for await (const part of toAISdkStream(stream, {
from: 'agent',
version: 'v6',
})) {
await writer.write(part)
}
},
})
return createUIMessageStreamResponse({
stream: uiMessageStream,
})
}
使用 messageMetadatausing-messagemetadata 的直接連結
app/api/chat-with-metadata/route.ts
import { mastra } from '../../mastra'
import { createUIMessageStream, createUIMessageStreamResponse } from 'ai'
import { toAISdkStream } from '@mastra/ai-sdk'
export async function POST(req: Request) {
const { messages } = await req.json()
const myAgent = mastra.getAgent('weatherAgent')
const stream = await myAgent.stream(messages)
const uiMessageStream = createUIMessageStream({
originalMessages: messages,
execute: async ({ writer }) => {
for await (const part of toAISdkStream(stream, {
from: 'agent',
messageMetadata: ({ part }) => ({
timestamp: Date.now(),
partType: part.type,
}),
})) {
await writer.write(part)
}
},
})
return createUIMessageStreamResponse({
stream: uiMessageStream,
})
}
客戶端串流轉換客戶端串流轉換 的直接連結
如果你在客戶端使用 Mastra client SDK(@mastra/client-js),並希望將串流轉換成 AI SDK 格式:
client-stream-to-ai-sdk.ts
import { MastraClient } from '@mastra/client-js'
import { createUIMessageStream } from 'ai'
import { toAISdkStream } from '@mastra/ai-sdk'
import type { ChunkType, MastraModelOutput } from '@mastra/core/stream'
const client = new MastraClient({
baseUrl: 'http://localhost:4111',
})
const agent = client.getAgent('weatherAgent')
const response = await agent.stream('What is the weather in Tokyo?')
// Convert the client SDK stream to a ReadableStream<ChunkType>
const chunkStream = new ReadableStream<ChunkType>({
async start(controller) {
await response.processDataStream({
onChunk: async chunk => {
controller.enqueue(chunk)
},
})
controller.close()
},
})
// Transform to AI SDK format
const uiMessageStream = createUIMessageStream({
execute: async ({ writer }) => {
for await (const part of toAISdkStream(chunkStream as unknown as MastraModelOutput, {
from: 'agent',
})) {
await writer.write(part)
}
},
})
for await (const part of uiMessageStream) {
console.log(part)
}