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feat: Add reasoning.effort: none parameter for gpt-5.1 (#657)
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‎.changeset/olive-waves-type.md‎

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---
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'@openai/agents-openai': patch
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'@openai/agents-core': patch
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---
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feat: Add reasoning.effort: none parameter for gpt-5.1

‎examples/basic/hello-world-gpt-5.1.ts‎

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import {
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Agent,
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OpenAIChatCompletionsModel,
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run,
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withTrace,
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} from '@openai/agents';
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import OpenAI from 'openai';
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import { z } from 'zod';
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const output = z.object({
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title: z.string(),
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description: z.string(),
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});
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async function main() {
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withTrace('GPT-5.1 None Reasoning Assistant', async () => {
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const prompt =
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'Tell me about recursion in programming in a few sentences. Quickly responding with a single answer is fine.';
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const agent = new Agent({
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name: 'GPT-5.1 Responses Assistant',
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model: 'gpt-5.1',
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instructions: "You're a helpful assistant.",
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modelSettings: {
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reasoning: { effort: 'none' },
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text: { verbosity: 'low' },
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},
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outputType: output,
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});
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const result = await run(agent, prompt);
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console.log(result.finalOutput);
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const completionsAgent = new Agent({
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name: 'GPT-5.1 Chat Completions Assistant',
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model: new OpenAIChatCompletionsModel(new OpenAI(), 'gpt-5.1'),
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instructions: "You're a helpful assistant.",
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modelSettings: {
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reasoning: { effort: 'none' },
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text: { verbosity: 'low' },
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},
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outputType: output,
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});
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const completionsResult = await run(completionsAgent, prompt);
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console.log(completionsResult.finalOutput);
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});
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}
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main().catch((error) => {
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console.error(error);
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process.exit(1);
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});

‎examples/basic/hello-world-gpt-5.ts‎

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import { Agent, OpenAIChatCompletionsModel, run } from '@openai/agents';
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import {
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Agent,
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OpenAIChatCompletionsModel,
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run,
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withTrace,
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} from '@openai/agents';
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import OpenAI from 'openai';
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import { z } from 'zod';
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});
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async function main() {
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const prompt =
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'Tell me about recursion in programming. Quickly responding with a single answer is fine.';
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withTrace('GPT-5 Assistant', async () => {
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const prompt =
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'Tell me about recursion in programming in a few sentences. Quickly responding with a single answer is fine.';
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const agent = new Agent({
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name: 'GPT-5 Assistant',
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model: 'gpt-5',
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instructions: "You're a helpful assistant.",
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modelSettings: {
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reasoning: { effort: 'minimal' },
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text: { verbosity: 'low' },
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},
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outputType: output,
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});
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const agent = new Agent({
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name: 'GPT-5 Assistant',
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model: 'gpt-5',
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instructions: "You're a helpful assistant.",
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modelSettings: {
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reasoning: { effort: 'minimal' },
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text: { verbosity: 'low' },
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},
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outputType: output,
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});
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const result = await run(agent, prompt);
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console.log(result.finalOutput);
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const result = await run(agent, prompt);
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console.log(result.finalOutput);
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// The following code works in the same way:
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// const agent2 = agent.clone({
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// modelSettings: {
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// providerData: {
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// reasoning: { effort: 'minimal' },
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// text: { verbosity: 'low' },
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// }
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// },
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// });
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// const result2 = await run(agent2, prompt);
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// console.log(result2.finalOutput);
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// The following code works in the same way:
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// const agent2 = agent.clone({
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// modelSettings: {
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// providerData: {
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// reasoning: { effort: 'minimal' },
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// text: { verbosity: 'low' },
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// }
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// },
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// });
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// const result2 = await run(agent2, prompt);
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// console.log(result2.finalOutput);
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const completionsAgent = new Agent({
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name: 'GPT-5 Assistant',
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model: new OpenAIChatCompletionsModel(new OpenAI(), 'gpt-5'),
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instructions: "You're a helpful assistant.",
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modelSettings: {
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reasoning: { effort: 'minimal' },
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text: { verbosity: 'low' },
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},
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outputType: output,
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});
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const completionsResult = await run(completionsAgent, prompt);
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console.log(completionsResult.finalOutput);
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const completionsAgent = new Agent({
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name: 'GPT-5 Assistant',
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model: new OpenAIChatCompletionsModel(new OpenAI(), 'gpt-5'),
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instructions: "You're a helpful assistant.",
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modelSettings: {
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reasoning: { effort: 'minimal' },
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text: { verbosity: 'low' },
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},
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outputType: output,
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});
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const completionsResult = await run(completionsAgent, prompt);
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console.log(completionsResult.finalOutput);
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// The following code works in the same way:
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// const completionsAgent2 = completionsAgent.clone({
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// modelSettings: {
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// providerData: {
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// reasoning_effort: 'minimal',
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// verbosity: 'low',
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// }
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// },
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// });
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// const completionsResult2 = await run(completionsAgent2, prompt);
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// console.log(completionsResult2.finalOutput);
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// The following code works in the same way:
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// const completionsAgent2 = completionsAgent.clone({
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// modelSettings: {
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// providerData: {
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// reasoning_effort: 'minimal',
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// verbosity: 'low',
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// }
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// },
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// });
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// const completionsResult2 = await run(completionsAgent2, prompt);
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// console.log(completionsResult2.finalOutput);
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});
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}
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main().catch((error) => {

‎examples/basic/package.json‎

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"start:dynamic-system-prompt": "tsx dynamic-system-prompt.ts",
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"start:hello-world": "tsx hello-world.ts",
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"start:hello-world-gpt-5": "tsx hello-world-gpt-5.ts",
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"start:hello-world-gpt-5.1": "tsx hello-world-gpt-5.1.ts",
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"start:hello-world-gpt-oss": "tsx hello-world-gpt-oss.ts",
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"start:lifecycle-example": "tsx lifecycle-example.ts",
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"start:local-image": "tsx local-image.ts",

‎packages/agents-core/src/model.ts‎

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* Reducing reasoning effort can result in faster responses and fewer tokens used on reasoning in a response.
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*/
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export type ModelSettingsReasoningEffort =
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| 'minimal'
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| 'none' // for gpt-5.1
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| 'minimal' // for gpt-5
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| 'low'
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| 'medium'
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| 'high'

‎packages/agents-openai/test/openaiChatCompletionsModel.test.ts‎

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expect(options).toEqual({ headers: HEADERS, signal: undefined });
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});
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it('passes none reasoning effort through to chat completions payloads', async () => {
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const client = new FakeClient();
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const response = {
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id: 'gpt-5.1-response',
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choices: [{ message: { content: 'done' } }],
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usage: { prompt_tokens: 0, completion_tokens: 0, total_tokens: 0 },
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} as any;
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client.chat.completions.create.mockResolvedValue(response);
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const model = new OpenAIChatCompletionsModel(client as any, 'gpt-5.1');
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const req: any = {
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input: 'prompt',
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modelSettings: {
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reasoning: { effort: 'none' },
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},
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tools: [],
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outputType: 'text',
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handoffs: [],
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tracing: false,
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};
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await withTrace('gpt-5.1 none', () => model.getResponse(req));
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expect(client.chat.completions.create).toHaveBeenCalledTimes(1);
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const [args, options] = client.chat.completions.create.mock.calls[0];
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expect(args.reasoning_effort).toBe('none');
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expect(options).toEqual({ headers: HEADERS, signal: undefined });
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});
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it('handles function tool calls', async () => {
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const client = new FakeClient();
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const response = {

‎packages/agents-openai/test/openaiResponsesModel.test.ts‎

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});
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});
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it('passes none reasoning effort to the Responses API payload', async () => {
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await withTrace('test', async () => {
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const fakeResponse = {
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id: 'res-none',
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usage: {
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input_tokens: 1,
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output_tokens: 1,
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total_tokens: 2,
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},
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output: [],
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};
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const createMock = vi.fn().mockResolvedValue(fakeResponse);
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const fakeClient = {
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responses: { create: createMock },
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} as unknown as OpenAI;
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const model = new OpenAIResponsesModel(fakeClient, 'gpt-5.1');
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const request = {
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systemInstructions: undefined,
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input: 'hi',
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modelSettings: {
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reasoning: { effort: 'none' },
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},
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tools: [],
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outputType: 'text',
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handoffs: [],
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tracing: false,
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signal: undefined,
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};
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await model.getResponse(request as any);
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expect(createMock).toHaveBeenCalledTimes(1);
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const [args] = createMock.mock.calls[0];
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expect(args.reasoning).toEqual({ effort: 'none' });
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});
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});
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it('getStreamedResponse yields events and calls client with stream flag', async () => {
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await withTrace('test', async () => {
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const fakeResponse = { id: 'res2', usage: {}, output: [] };

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