from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://tokenhub-intl.tencentcloudmaas.com/v1",
)

target_lang = "英语"
source_text = "腾讯混元大模型已上线 TokenHub 平台，支持深度思考、结构化输出、Function Calling 等能力。"

prompt = f"""将以下文本翻译为 {target_lang}，注意只需要输出翻译后的结果，不要额外解释：
{source_text}"""

response = client.chat.completions.create(
    model="hy-mt2-plus",
    messages=[{"role": "user", "content": prompt}],
)
print(response.choices[0].message.content)

import okhttp3.*;
import com.google.gson.Gson;
import java.util.*;

public class TranslationDemo {
    public static void main(String[] args) throws Exception {
        String targetLang = "英语";
        String sourceText = "腾讯混元大模型已上线 TokenHub 平台，支持深度思考、结构化输出、Function Calling 等能力。";
        String prompt = "将以下文本翻译为 " + targetLang + "，注意只需要输出翻译后的结果，不要额外解释：\\n" + sourceText;

        Map<String, Object> body = new HashMap<>();
        body.put("model", "hy-mt2-plus");
        body.put("messages", List.of(
            Map.of("role", "user", "content", prompt)
        ));

        Request request = new Request.Builder()
            .url("https://tokenhub-intl.tencentcloudmaas.com/v1/chat/completions")
            .header("Authorization", "Bearer YOUR_API_KEY")
            .post(RequestBody.create(new Gson().toJson(body),
                MediaType.parse("application/json")))
            .build();

        try (Response response = new OkHttpClient().newCall(request).execute()) {
            System.out.println(response.body().string());
        }
    }
}

import OpenAI from 'openai';

const client = new OpenAI({
  apiKey: 'YOUR_API_KEY',
  baseURL: 'https://tokenhub-intl.tencentcloudmaas.com/v1',
});

const targetLang = '英语';
const sourceText = '腾讯混元大模型已上线 TokenHub 平台，支持深度思考、结构化输出、Function Calling 等能力。';
const prompt = `将以下文本翻译为 ${targetLang}，注意只需要输出翻译后的结果，不要额外解释：\\n${sourceText}`;

const response = await client.chat.completions.create({
  model: 'hy-mt2-plus',
  messages: [{ role: 'user', content: prompt }],
});
console.log(response.choices[0].message.content);

package main

import (
    "bytes"
    "encoding/json"
    "fmt"
    "io"
    "net/http"
)

func main() {
    targetLang := "英语"
    sourceText := "腾讯混元大模型已上线 TokenHub 平台，支持深度思考、结构化输出、Function Calling 等能力。"
    prompt := "将以下文本翻译为 " + targetLang + "，注意只需要输出翻译后的结果，不要额外解释：\\n" + sourceText

    body, _ := json.Marshal(map[string]interface{}{
        "model": "hy-mt2-plus",
        "messages": []map[string]string{
            {"role": "user", "content": prompt},
        },
    })

    req, _ := http.NewRequest("POST",
        "https://tokenhub-intl.tencentcloudmaas.com/v1/chat/completions",
        bytes.NewBuffer(body))
    req.Header.Set("Authorization", "Bearer YOUR_API_KEY")
    req.Header.Set("Content-Type", "application/json")

    resp, _ := http.DefaultClient.Do(req)
    defer resp.Body.Close()
    data, _ := io.ReadAll(resp.Body)
    fmt.Println(string(data))
}

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://tokenhub-intl.tencentcloudmaas.com/v1",
)

target_lang = "英语"
format_type = "JSON"
source_text = '{"title": "产品介绍", "description": "腾讯混元大模型已上线 TokenHub 平台", "tags": ["大模型", "翻译", "AI"]}'

prompt = f"""# 任务目标
将下方 source_text 中的 {format_type} 格式数据翻译为 {target_lang}。

# 严格约束
1. 结构锁定：绝对保持原有的 {format_type} 数据结构、缩进和层级完全不变。
2. 选择性翻译：仅翻译面向用户展示的可见文本内容。
3. 禁止修改：严禁翻译或更改任何代码标签、键名 (Key)、变量占位符（如 {{var}}、${{var}}、%s、%d 等）或代码属性。

# 数据输入
{source_text}"""

response = client.chat.completions.create(
    model="hy-mt2-plus",
    messages=[{"role": "user", "content": prompt}],
)
print(response.choices[0].message.content)

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://tokenhub-intl.tencentcloudmaas.com/v1",
)

target_lang = "英语"
SEP = "<SEP>"
source_segments = ["腾讯混元大模型已上线", "支持深度思考与工具调用", "覆盖 38 种语言互译"]
source_text = SEP.join(source_segments)

prompt = f"""请将以下文本准确翻译为 {target_lang}。你必须在译文中保留等量的分隔符，绝对不可遗漏、转义或翻译该符号，并注意分隔符的位置。
{source_text}"""

response = client.chat.completions.create(
    model="hy-mt2-plus",
    messages=[{"role": "user", "content": prompt}],
)

translated = response.choices[0].message.content.split(SEP)
for src, tgt in zip(source_segments, translated):
    print(f"{src.strip()}  →  {tgt.strip()}")

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://tokenhub-intl.tencentcloudmaas.com/v1",
)

target_lang = "英语"
background_text = "这是一篇介绍数据库系统的技术文档，上文提到的 transaction 指数据库事务，index 指数据库索引。"
source_text = "事务提交后，索引会被异步刷新到磁盘。"

prompt = f"""【背景信息】
{background_text}
请结合背景信息将以下文本翻译为 {target_lang}。
【待翻译文本】
{source_text}"""

response = client.chat.completions.create(
    model="hy-mt2-plus",
    messages=[{"role": "user", "content": prompt}],
)
print(response.choices[0].message.content)

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://tokenhub-intl.tencentcloudmaas.com/v1",
)

target_lang = "英语"
glossary = [
    ("混元大模型", "Tencent Hy"),
    ("腾讯云", "Tencent Cloud"),
    ("深度思考", "deep reasoning"),
]
source_text = "腾讯云上的混元大模型支持深度思考能力。"

glossary_text = "\\n".join(f"{src} 翻译成 {tgt}" for src, tgt in glossary)
prompt = f"""参考下面的翻译：
{glossary_text}
将以下文本翻译为 {target_lang}，注意只需要输出翻译后的结果，不要额外解释：
{source_text}"""

response = client.chat.completions.create(
    model="hy-mt2-plus",
    messages=[{"role": "user", "content": prompt}],
)
print(response.choices[0].message.content)

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://tokenhub-intl.tencentcloudmaas.com/v1",
)

target_lang = "英语"
target_style = "营销文案：语言简洁有力、富有感染力、突出卖点，适合面向海外开发者的产品介绍"
source_text = "腾讯混元大模型，开箱即用，让 AI 应用开发更简单。"

prompt = f"""请将以下文本翻译为 {target_lang}。注意翻译的风格要严格符合【{target_style}】
{source_text}"""

response = client.chat.completions.create(
    model="hy-mt2-plus",
    messages=[{"role": "user", "content": prompt}],
)
print(response.choices[0].message.content)