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Rename experimental_StreamData to StreamData. (#1309)
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‎.changeset/real-spies-sort.md‎

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---
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'ai': patch
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---
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Remove experimental\_ prefix from StreamData.

‎docs/pages/docs/api-reference.mdx‎

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- [`StreamingTextResponse`](./api-reference/streaming-text-response)
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- [`AIStream`](./api-reference/ai-stream)
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- [`streamToResponse`](./api-reference/stream-to-response)
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- [`experimental_StreamData`](./api-reference/stream-data)
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- [`StreamData`](./api-reference/stream-data)
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## Prompt Construction Helpers
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‎docs/pages/docs/api-reference/_meta.json‎

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"use-chat": "useChat",
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"use-completion": "useCompletion",
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"ai-stream": "AIStream",
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"stream-data": "experimental_StreamData",
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"stream-data": "StreamData",
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"streaming-text-response": "StreamingTextResponse",
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"stream-to-response": "streamToResponse",
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"tokens": "<Tokens />"

‎docs/pages/docs/api-reference/providers/inkeep-stream.mdx‎

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InkeepStream,
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InkeepOnFinalMetadata,
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StreamingTextResponse,
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experimental_StreamData,
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StreamData,
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} from 'ai';
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import { InkeepAI } from '@inkeep/ai-api';
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import type { RecordsCited$ } from '@inkeep/ai-api/models/components';
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}
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// used to pass custom metadata to the client
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const data = new experimental_StreamData();
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const data = new StreamData();
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if (!response?.body) {
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throw new Error('Response body is null');
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}
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```
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This example uses the [experimental_StreamData](/docs/api-reference/stream-data) and the callback methods of `InkeepStream` to attach metadata to the response.
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This example uses the [StreamData](/docs/api-reference/stream-data) and the callback methods of `InkeepStream` to attach metadata to the response.
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### Client
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‎docs/pages/docs/api-reference/providers/mistral-stream.mdx‎

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```tsx filename="app/api/completion/route.ts" showLineNumbers
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import MistralClient from '@mistralai/mistralai';
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import {
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MistralStream,
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StreamingTextResponse,
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experimental_StreamData,
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} from 'ai';
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import { MistralStream, StreamingTextResponse, StreamData } from 'ai';
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const mistral = new MistralClient(process.env.MISTRAL_API_KEY || '');
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});
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// optional: use stream data
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const data = new experimental_StreamData();
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const data = new StreamData();
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data.append({ test: 'value' });
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‎docs/pages/docs/api-reference/stream-data.mdx‎

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---
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title: experimental_StreamData
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title: StreamData
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layout:
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toc: false
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---
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import { Callout } from 'nextra-theme-docs';
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# `experimental_StreamData`
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# `StreamData`
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The `experimental_StreamData` class allows you to stream arbitrary data to the client alongside your LLM response.
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The `StreamData` class allows you to stream arbitrary data to the client alongside your LLM response.
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For information on the implementation, see the associated [pull request](https://github.com/vercel/ai/pull/425).
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<Callout>
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The `experimental_` prefix indicates that the API is not yet stable and may
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change in the future without a major version bump.
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</Callout>
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## Usage
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### On the Server
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```jsx filename="app/api/chat/route.ts" {24-25,39-40,58-59,62-63,66-67}
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import {
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OpenAIStream,
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StreamingTextResponse,
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experimental_StreamData,
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} from 'ai';
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import { OpenAIStream, StreamingTextResponse, StreamData } from 'ai';
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import OpenAI from 'openai';
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import type { ChatCompletionCreateParams } from 'openai/resources/chat';
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});
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// Instantiate the StreamData. It works with all API providers.
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const data = new experimental_StreamData();
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const data = new StreamData();
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const stream = OpenAIStream(response, {
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experimental_onFunctionCall: async (

‎docs/pages/docs/api-reference/streaming-react-response.mdx‎

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This parameter should be a `ReadableStream`, which encapsulates the HTTP response's content. It represents the stream from which the response is read and processed.
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### `options?: {ui?: Function, data?: experimental_StreamData}`
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### `options?: {ui?: Function, data?: StreamData}`
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This optional parameter allows additional configurations for rendering React components and handling streamed data.
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The options object can include:
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- `ui?: (message: {content: string, data?: JSONValue[] | undefined}) => UINode | Promise<UINode>`: A function that receives a message object with `content` and optional `data` fields. This function should return a React component (as `UINode`) for each chunk in the stream. The `data` attribute in the message is available when the `data` option is configured to include stream data.
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- `data?: experimental_StreamData`: An instance of `experimental_StreamData` used to process and stream data along with the response.
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- `data?: StreamData`: An instance of `StreamData` used to process and stream data along with the response.
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## Returns
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‎docs/pages/docs/guides/providers/inkeep.mdx‎

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InkeepStream,
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InkeepOnFinalMetadata,
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StreamingTextResponse,
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experimental_StreamData,
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StreamData,
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} from 'ai';
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import { InkeepAI } from '@inkeep/ai-api';
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import type { RecordsCited$ } from '@inkeep/ai-api/models/components';
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}
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// used to pass custom metadata to the client
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const data = new experimental_StreamData();
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const data = new StreamData();
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if (!response?.body) {
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throw new Error('Response body is null');
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class with the default headers you probably want (hint: `'Content-Type':
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'text/plain; charset=utf-8'` is already set for you). This will provide the streamed content to the client.
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3. Lastly, we use the [experimental_StreamData](/docs/api-reference/stream-data) and callback methods of the `InkeepStream` to attach metadata to the response like `onFinalMetadata.chat_session_id` and `records_cited.citations` for use by the client.
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3. Lastly, we use the [StreamData](/docs/api-reference/stream-data) and callback methods of the `InkeepStream` to attach metadata to the response like `onFinalMetadata.chat_session_id` and `records_cited.citations` for use by the client.
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<Callout>
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It's common to save a chat to a database. To do so, you can leverage the

‎examples/next-inkeep/app/api/chat/route.ts‎

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InkeepStream,
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InkeepOnFinalMetadata,
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experimental_StreamData,
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StreamData,
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} from 'ai';
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import { InkeepAI } from '@inkeep/ai-api';
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import type { RecordsCited$ } from '@inkeep/ai-api/models/components';
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}
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// used to pass custom metadata to the client
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const data = new experimental_StreamData();
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const data = new StreamData();
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if (!response?.body) {
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throw new Error('Response body is null');

‎examples/next-langchain/app/api/stream-data-basic/route.ts‎

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StreamingTextResponse,
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LangChainStream,
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Message,
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StreamData,
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} from 'ai';
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import { ChatOpenAI } from 'langchain/chat_models/openai';
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import { AIMessage, HumanMessage } from 'langchain/schema';
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export async function POST(req: Request) {
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const { messages } = await req.json();
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const data = new experimental_StreamData();
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const data = new StreamData();
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// important: use LangChainStream from the AI SDK:
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const { stream, handlers } = LangChainStream({

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