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lgrammeldancer
lgrammel
and
dancer
authored
feat: forward id, streaming start, streaming end of content blocks (#6812)
## Background When streaming, it was not possible to distinguish different content of the same type (e.g. 2 text content parts) sent from Anthropic and OpenAI APIs. This prevents building UIs where e.g. multiple reasoning blocks stream at the same time, or where a text part is followed by sources and then by further text parts. ## Summary * text and reasoning parts have ids, and start/delta/end events when streaming ## Verification Source streaming with anthropic server side tool call in UI. ## Future Work * add state field to ui message reasoning and text parts --------- Co-authored-by: josh <josh@afterima.ge>
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‎.changeset/angry-dragons-tan.md

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---
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'@ai-sdk/provider': major
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---
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feat: forward id, streaming start, streaming end of content blocks

‎examples/ai-core/src/middleware/your-log-middleware.ts

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@@ -29,8 +29,8 @@ export const yourLogMiddleware: LanguageModelV2Middleware = {
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LanguageModelV2StreamPart
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>({
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transform(chunk, controller) {
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if (chunk.type === 'text') {
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generatedText += chunk.text;
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if (chunk.type === 'text-delta') {
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generatedText += chunk.delta;
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}
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controller.enqueue(chunk);

‎examples/ai-core/src/stream-object/mock.ts

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@@ -8,12 +8,14 @@ async function main() {
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model: new MockLanguageModelV2({
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doStream: async () => ({
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stream: convertArrayToReadableStream([
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{ type: 'text', text: '{ ' },
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{ type: 'text', text: '"content": ' },
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{ type: 'text', text: `"Hello, ` },
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{ type: 'text', text: `world` },
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{ type: 'text', text: `!"` },
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{ type: 'text', text: ' }' },
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{ type: 'text-start', id: '0' },
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{ type: 'text-delta', id: '0', delta: '{ ' },
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{ type: 'text-delta', id: '0', delta: '"content": ' },
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{ type: 'text-delta', id: '0', delta: `"Hello, ` },
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{ type: 'text-delta', id: '0', delta: `world` },
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{ type: 'text-delta', id: '0', delta: `!"` },
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{ type: 'text-delta', id: '0', delta: ' }' },
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{ type: 'text-end', id: '0' },
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{
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type: 'finish',
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finishReason: 'stop',

‎examples/ai-core/src/stream-text/cohere-raw-chunks.ts

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import { cohere } from '@ai-sdk/cohere';
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import 'dotenv/config';
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async function main() {
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const model = cohere('command-r-plus');
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console.log('=== COHERE RAW STREAMING CHUNKS ===');
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const { stream } = await model.doStream({
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prompt: [
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{
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role: 'user',
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content: [{ type: 'text', text: 'Count from 1 to 3 slowly.' }],
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},
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],
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includeRawChunks: true,
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});
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let textChunkCount = 0;
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let rawChunkCount = 0;
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let fullText = '';
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const reader = stream.getReader();
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try {
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while (true) {
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const { done, value: chunk } = await reader.read();
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if (done) break;
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if (chunk.type === 'raw') {
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rawChunkCount++;
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console.log(
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'Raw chunk',
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rawChunkCount,
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':',
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JSON.stringify(chunk.rawValue),
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);
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} else {
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console.log('Processed chunk:', chunk.type, JSON.stringify(chunk));
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}
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}
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} finally {
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reader.releaseLock();
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}
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console.log();
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console.log('Text chunks:', textChunkCount);
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console.log('Raw chunks:', rawChunkCount);
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console.log('Final text:', fullText);
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}
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main().catch(console.error);

‎examples/ai-core/src/stream-text/mistral-raw-chunks.ts

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import { mistral } from '@ai-sdk/mistral';
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import { streamText } from 'ai';
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import 'dotenv/config';
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async function main() {
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const result = streamText({
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model: mistral('mistral-small-latest'),
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prompt: 'Count from 1 to 3 slowly.',
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includeRawChunks: true,
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});
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let textChunkCount = 0;
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let rawChunkCount = 0;
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for await (const chunk of result.fullStream) {
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if (chunk.type === 'text') {
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textChunkCount++;
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console.log('Text chunk', textChunkCount, ':', chunk.text);
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} else if (chunk.type === 'raw') {
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rawChunkCount++;
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console.log(
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'Raw chunk',
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rawChunkCount,
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':',
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JSON.stringify(chunk.rawValue),
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);
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}
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}
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console.log();
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console.log('Text chunks:', textChunkCount);
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console.log('Raw chunks:', rawChunkCount);
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console.log('Final text:', await result.text);
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}
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main().catch(console.error);

‎examples/ai-core/src/stream-text/mock.ts

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@@ -7,9 +7,11 @@ async function main() {
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model: new MockLanguageModelV2({
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doStream: async () => ({
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stream: convertArrayToReadableStream([
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{ type: 'text', text: 'Hello' },
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{ type: 'text', text: ', ' },
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{ type: 'text', text: `world!` },
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{ type: 'text-start', id: '0' },
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{ type: 'text-delta', id: '0', delta: 'Hello' },
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{ type: 'text-delta', id: '0', delta: ', ' },
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{ type: 'text-delta', id: '0', delta: `world!` },
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{ type: 'text-end', id: '0' },
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{
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type: 'finish',
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finishReason: 'stop',

‎examples/ai-core/src/stream-text/openai-compatible-raw-chunks.ts

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import { createOpenAICompatible } from '@ai-sdk/openai-compatible';
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import { streamText } from 'ai';
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import 'dotenv/config';
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async function main() {
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const openaiCompatible = createOpenAICompatible({
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baseURL: 'https://api.openai.com/v1',
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name: 'openai-compatible',
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headers: {
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Authorization: `Bearer ${process.env.OPENAI_API_KEY}`,
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},
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});
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const result = streamText({
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model: openaiCompatible.completionModel('gpt-3.5-turbo-instruct'),
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prompt: 'Hello, World!',
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includeRawChunks: true,
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});
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let textChunkCount = 0;
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let rawChunkCount = 0;
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let otherChunkCount = 0;
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for await (const chunk of result.fullStream) {
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console.log('Chunk type:', chunk.type, 'Chunk:', JSON.stringify(chunk));
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if (chunk.type === 'text') {
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textChunkCount++;
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console.log('Text chunk', textChunkCount, ':', chunk.text);
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} else if (chunk.type === 'raw') {
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rawChunkCount++;
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console.log(
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'Raw chunk',
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rawChunkCount,
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':',
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JSON.stringify(chunk.rawValue),
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);
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} else {
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otherChunkCount++;
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console.log('Other chunk', otherChunkCount, ':', chunk.type);
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}
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}
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console.log();
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console.log('Text chunks:', textChunkCount);
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console.log('Raw chunks:', rawChunkCount);
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console.log('Other chunks:', otherChunkCount);
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console.log('Final text:', await result.text);
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}
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main().catch(console.error);

‎examples/ai-core/src/stream-text/smooth-stream-chinese.ts

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doStream: async () => ({
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stream: simulateReadableStream({
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chunks: [
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{ type: 'text', text: '你好你好你好你好你好' },
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{ type: 'text', text: '你好你好你好你好你好' },
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{ type: 'text', text: '你好你好你好你好你好' },
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{ type: 'text', text: '你好你好你好你好你好' },
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{ type: 'text', text: '你好你好你好你好你好' },
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{ type: 'text-start', id: '0' },
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{ type: 'text-delta', id: '0', delta: '你好你好你好你好你好' },
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{ type: 'text-delta', id: '0', delta: '你好你好你好你好你好' },
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{ type: 'text-delta', id: '0', delta: '你好你好你好你好你好' },
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{ type: 'text-delta', id: '0', delta: '你好你好你好你好你好' },
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{ type: 'text-delta', id: '0', delta: '你好你好你好你好你好' },
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{ type: 'text-end', id: '0' },
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{
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type: 'finish',
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finishReason: 'stop',

‎examples/ai-core/src/stream-text/smooth-stream-japanese.ts

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doStream: async () => ({
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stream: simulateReadableStream({
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chunks: [
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{ type: 'text', text: 'こんにちは' },
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{ type: 'text', text: 'こんにちは' },
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{ type: 'text', text: 'こんにちは' },
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{ type: 'text', text: 'こんにちは' },
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{ type: 'text', text: 'こんにちは' },
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{ type: 'text-start', id: '0' },
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{ type: 'text-delta', id: '0', delta: 'こんにちは' },
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{ type: 'text-delta', id: '0', delta: 'こんにちは' },
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{ type: 'text-delta', id: '0', delta: 'こんにちは' },
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{ type: 'text-delta', id: '0', delta: 'こんにちは' },
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{ type: 'text-end', id: '0' },
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{
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type: 'finish',
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finishReason: 'stop',

‎examples/ai-core/src/stream-text/xai-raw-chunks.ts

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import { xai } from '@ai-sdk/xai';
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import { streamText } from 'ai';
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import 'dotenv/config';
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async function main() {
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const result = streamText({
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model: xai('grok-beta'),
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prompt: 'Count from 1 to 3 slowly.',
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includeRawChunks: true,
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});
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let textChunkCount = 0;
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let rawChunkCount = 0;
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for await (const chunk of result.fullStream) {
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if (chunk.type === 'text') {
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textChunkCount++;
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console.log('Text chunk', textChunkCount, ':', chunk.text);
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} else if (chunk.type === 'raw') {
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rawChunkCount++;
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console.log(
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'Raw chunk',
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rawChunkCount,
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':',
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JSON.stringify(chunk.rawValue),
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);
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}
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}
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console.log();
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console.log('Text chunks:', textChunkCount);
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console.log('Raw chunks:', rawChunkCount);
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console.log('Final text:', await result.text);
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}
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main().catch(console.error);

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