GPT-5 for Microsoft Developers

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using OpenAI.Responses;

OpenAIResponseClient client = new(
    model: "gpt-5",
    apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
);

await foreach (var update in client.CreateResponseStreamingAsync(
    userInputText: "Explain beta-reduction in lambda calculus.",
    new ResponseCreationOptions
    {
        ReasoningOptions = new ResponseReasoningOptions
        {
            ReasoningEffortLevel = ResponseReasoningEffortLevel.High,
        },
    }))
{
    if (update is StreamingResponseContentPartDeltaUpdate delta)
    {
        Console.Write(delta.Text);
    }
}

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import os

import openai
from azure.identity import DefaultAzureCredential, get_bearer_token_provider

client = openai.AzureOpenAI(
    api_version=os.environ["AZURE_OPENAI_VERSION"],
    azure_endpoint=os.environ["AZURE_OPENAI_ENDPOINT"],
    azure_ad_token_provider=get_bearer_token_provider(DefaultAzureCredential(),
        "https://cognitiveservices.azure.com/.default"),
)

response = client.chat.completions.create(
    model=os.environ["AZURE_OPENAI_DEPLOYMENT"],
    messages=[
        {"role": "user", "content": "Explain beta-reduction in lambda calculus."},
    ],
    reasoning_effort="minimal",
    verbosity="low"
)
print(response.choices[0].message.content)

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import { AzureOpenAI } from "openai";
import dotenv from "dotenv";

dotenv.config();

const endpoint = process.env.AZURE_INFERENCE_ENDPOINT; // Foundry项目端点
const key = process.env.AZURE_INFERENCE_KEY; // API密钥
const deployment = process.env.AZURE_OPENAI_DEPLOYMENT || "gpt-5";

const client = new AzureOpenAI({
    endpoint,
    apiKey: key,
    apiVersion: "2025-01-01-preview",
    deployment,
});

const schema = {
    name: "math_explanation",
    schema: {
        type: "object",
        properties: {
            steps: { type: "array", items: { type: "string" } },
            answer: { type: "number" },
        },
        required: ["steps", "answer"],
        additionalProperties: false,
    },
    strict: true,
};

const result = await client.chat.completions.create({
    model: deployment,
    messages: [
        { role: "system", content: "Return JSON only." },
        { role: "user", content: "What is 23 * 7? Show your steps." },
    ],
    response_format: { type: "json_schema", json_schema: schema },
});

const content = result.choices[0].message?.content ?? "{}";
const data = JSON.parse(content);
console.log("Steps:", data.steps);
console.log("Answer:", data.answer);

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示例输出 "What is 23 * 7? Show your steps.":

Steps: [
  'Break 23 into 20 and 3: (20 + 3) * 7',
  'Multiply: 20 * 7 = 140',
  'Multiply: 3 * 7 = 21',
  'Add the results: 140 + 21 = 161'
]
Answer: 161

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import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.ChatModel;
import com.openai.models.responses.Response;
import com.openai.models.responses.ResponseCreateParams;

// 使用`OPENAI_API_KEY`、`OPENAI_ORG_ID`和`OPENAI_PROJECT_ID`环境变量配置
OpenAIClient client = OpenAIOkHttpClient.fromEnv();

ResponseCreateParams params = ResponseCreateParams.builder()
        .input("Say this is a test")
        .model(ChatModel.GPT_5)
        .build();
Response response = client.responses().create(params);