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KirschXvercel-ai-sdk[bot]
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Backport conflicts for PR #9857 to release-v5.0
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‎.changeset/six-roses-peel.md‎

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---
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'@ai-sdk/react': patch
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'ai': patch
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---
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Added finishReason on useChat onFinish callbck

‎content/docs/07-reference/02-ai-sdk-ui/01-use-chat.mdx‎

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@@ -275,6 +275,13 @@ Allows you to easily create a conversational user interface for your chatbot app
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type: 'boolean',
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description: `True if errors during streaming caused the response to stop early.`,
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},
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{
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name: 'finishReason',
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type: "'stop' | 'length' | 'content-filter' | 'tool-calls' | 'error' | 'other' | 'unknown'",
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isOptional: true,
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description:
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'The reason why the model finished generating the response. Undefined if the finish reason was not provided by the model.',
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},
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],
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},
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],

‎examples/next-openai/app/use-chat-data-ui-parts/page.tsx‎

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import ChatInput from '@/components/chat-input';
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import { useChat } from '@ai-sdk/react';
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import { DefaultChatTransport, UIMessage } from 'ai';
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import { DefaultChatTransport, UIMessage, type FinishReason } from 'ai';
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import { useState } from 'react';
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type MyMessage = UIMessage<
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never,
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>;
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export default function Chat() {
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const [lastFinishReason, setLastFinishReason] = useState<
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FinishReason | undefined
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>(undefined);
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const { error, status, sendMessage, messages, regenerate, stop } =
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useChat<MyMessage>({
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transport: new DefaultChatTransport({
@@ -24,6 +28,9 @@ export default function Chat() {
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onData: dataPart => {
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console.log('dataPart', JSON.stringify(dataPart, null, 2));
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},
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onFinish: ({ finishReason }) => {
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setLastFinishReason(finishReason);
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},
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});
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return (
@@ -94,6 +101,12 @@ export default function Chat() {
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</div>
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)}
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{messages.length > 0 && (
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<div className="mt-4 text-gray-500">
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Finish reason: {String(lastFinishReason)}
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</div>
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)}
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<ChatInput status={status} onSubmit={text => sendMessage({ text })} />
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</div>
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);

‎packages/ai/src/agent/create-agent-ui-stream-response.test.ts‎

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import { LanguageModelV3CallOptions } from '@ai-sdk/provider';
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import { tool } from '@ai-sdk/provider-utils';
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import {
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convertArrayToReadableStream,
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convertReadableStreamToArray,
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} from '@ai-sdk/provider-utils/test';
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import { beforeEach, describe, expect, it } from 'vitest';
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import { z } from 'zod/v4';
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import { MockLanguageModelV3 } from '../test/mock-language-model-v3';
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import { createAgentUIStreamResponse } from './create-agent-ui-stream-response';
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import { ToolLoopAgent } from './tool-loop-agent';
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describe('createAgentUIStreamResponse', () => {
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describe('when using tools toModelOutput', () => {
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let recordedInputs: LanguageModelV3CallOptions[];
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let response: Response;
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let decodedChunks: string[];
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beforeEach(async () => {
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recordedInputs = [];
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const agent = new ToolLoopAgent({
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model: new MockLanguageModelV3({
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doStream: async input => {
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recordedInputs.push(input);
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return {
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stream: convertArrayToReadableStream([
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{
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type: 'stream-start',
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warnings: [],
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},
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{
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type: 'response-metadata',
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id: 'id-0',
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modelId: 'mock-model-id',
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timestamp: new Date(0),
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},
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{ type: 'text-start', id: '1' },
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{ type: 'text-delta', id: '1', delta: 'Hello' },
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{ type: 'text-delta', id: '1', delta: ', ' },
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{ type: 'text-delta', id: '1', delta: `world!` },
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{ type: 'text-end', id: '1' },
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{
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type: 'finish',
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finishReason: 'stop',
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usage: {
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inputTokens: 10,
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outputTokens: 10,
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totalTokens: 20,
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},
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providerMetadata: {
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testProvider: { testKey: 'testValue' },
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},
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},
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]),
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};
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},
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}),
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tools: {
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example: tool({
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description: 'Example tool',
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inputSchema: z.object({
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input: z.string(),
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}),
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outputSchema: z.object({
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value: z.string(),
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}),
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// important: tool has toModelOutput that needs to be called
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toModelOutput: output => ({
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type: 'content',
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value: [{ type: 'text', text: output.value }],
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}),
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}),
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},
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});
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response = await createAgentUIStreamResponse({
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agent,
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messages: [
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{
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role: 'user',
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id: 'msg-1',
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parts: [
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{
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type: 'text' as const,
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text: 'Hello, world!',
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},
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],
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},
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{
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role: 'assistant',
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id: 'msg-2',
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parts: [
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{
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type: 'tool-example' as const,
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toolCallId: 'call-1',
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state: 'output-available',
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input: {
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input: 'Hello, world!',
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},
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output: {
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value: 'Example tool: Hello, world!',
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},
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},
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],
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},
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],
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});
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// consume the response
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const decoder = new TextDecoder();
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const encodedStream = response.body!;
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const chunks = await convertReadableStreamToArray(encodedStream);
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decodedChunks = chunks.map(chunk => decoder.decode(chunk));
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});
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it('should have a single call that contains the tool result as text', () => {
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expect(recordedInputs).toMatchInlineSnapshot(`
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[
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{
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"abortSignal": undefined,
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"frequencyPenalty": undefined,
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"headers": undefined,
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"includeRawChunks": false,
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"maxOutputTokens": undefined,
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"presencePenalty": undefined,
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"prompt": [
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{
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"content": [
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{
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"providerOptions": undefined,
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"text": "Hello, world!",
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"type": "text",
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},
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],
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"providerOptions": undefined,
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"role": "user",
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},
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{
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"content": [
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{
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"input": {
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"input": "Hello, world!",
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},
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"providerExecuted": undefined,
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"providerOptions": undefined,
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"toolCallId": "call-1",
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"toolName": "example",
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"type": "tool-call",
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},
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],
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"providerOptions": undefined,
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"role": "assistant",
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},
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{
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"content": [
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{
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"output": {
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"type": "content",
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"value": [
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{
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"text": "Example tool: Hello, world!",
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"type": "text",
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},
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],
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},
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"providerOptions": undefined,
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"toolCallId": "call-1",
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"toolName": "example",
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"type": "tool-result",
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},
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],
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"providerOptions": undefined,
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"role": "tool",
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},
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],
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"providerOptions": undefined,
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"responseFormat": undefined,
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"seed": undefined,
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"stopSequences": undefined,
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"temperature": undefined,
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"toolChoice": {
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"type": "auto",
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},
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"tools": [
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{
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"description": "Example tool",
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"inputSchema": {
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"$schema": "http://json-schema.org/draft-07/schema#",
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"additionalProperties": false,
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"properties": {
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"input": {
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"type": "string",
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},
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},
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"required": [
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"input",
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],
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"type": "object",
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},
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"name": "example",
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"providerOptions": undefined,
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"type": "function",
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},
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],
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"topK": undefined,
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"topP": undefined,
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},
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]
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`);
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});
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it('should return the UI message stream response', () => {
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expect(decodedChunks).toMatchInlineSnapshot(`
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[
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"data: {"type":"start"}
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",
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"data: {"type":"start-step"}
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",
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"data: {"type":"text-start","id":"1"}
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",
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"data: {"type":"text-delta","id":"1","delta":"Hello"}
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",
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"data: {"type":"text-delta","id":"1","delta":", "}
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",
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"data: {"type":"text-delta","id":"1","delta":"world!"}
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",
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"data: {"type":"text-end","id":"1"}
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",
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"data: {"type":"finish-step"}
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",
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"data: {"type":"finish","finishReason":"stop"}
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",
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"data: [DONE]
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",
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]
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`);
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});
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});
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});

‎packages/ai/src/generate-text/__snapshots__/stream-text.test.ts.snap‎

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"data: {"type":"finish-step"}
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",
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"data: {"type":"finish"}
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"data: {"type":"finish","finishReason":"error"}
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",
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"data: [DONE]
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"data: {"type":"finish-step"}
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",
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"data: {"type":"finish"}
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"data: {"type":"finish","finishReason":"error"}
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",
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"data: [DONE]
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"type": "finish-step",
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},
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{
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"finishReason": "error",
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"type": "finish",
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},
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]
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"type": "finish-step",
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},
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{
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"finishReason": "stop",
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"type": "finish",
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},
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]
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"type": "finish-step",
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},
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{
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"finishReason": "error",
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"type": "finish",
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},
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]
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"data: {"type":"finish-step"}
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",
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"data: {"type":"finish"}
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"data: {"type":"finish","finishReason":"error"}
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",
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"data: [DONE]
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"data: {"type":"finish-step"}
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",
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"data: {"type":"finish"}
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"data: {"type":"finish","finishReason":"error"}
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",
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"data: [DONE]

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