秒云Tokens管家 一站式可观测大模型API智能网关

# 使用标准 OpenAI 兼容 SDK，仅需配置秒云Tokens管家统一 BaseURL 与 API Key 即可调用全网大模型
from openai import OpenAI

client = OpenAI(
    api_key="my-sk-xxxxxxxxxxxxxxxxxxxxxxxx",  # 秒云Tokens管家颁发的统一企业密钥
    base_url="https://maas.miaoyun.net.cn/v1"   # 秒云Tokens管家分发路由集群
)

stream = client.chat.completions.create(
    model="qwen3.8-max",  # 支持一键切换 kimi-k3 / glm-5.3 / deepseek-v4-pro 等
    messages=[
        {"role": "system", "content": "You are an enterprise AI architect."},
        {"role": "user", "content": "请评测当前秒云异构算力网关在高并发大模型场景下的吞吐与前缀缓存收益"}
    ],
    stream=True
)

for chunk in stream:
    print(chunk.choices[0].delta.content or "", end="", flush=True)

// 采用行业通用 go-openai 库 (github.com/sashabaranov/go-openai)
package main

import (
    "context"
    "errors"
    "fmt"
    "io"
    openai "github.com/sashabaranov/go-openai"
)

func main() {
    config := openai.DefaultConfig("my-sk-xxxxxxxxxxxxxxxxxxxxxxxx")
    config.BaseURL = "https://maas.miaoyun.net.cn/v1" // 秒云Tokens管家统一端点

    client := openai.NewClientWithConfig(config)
    ctx := context.Background()

    req := openai.ChatCompletionRequest{
        Model: "kimi-k3", // 可无缝切换 deepseek-v4-pro / glm-5.3
        Messages: []openai.ChatCompletionMessage{
            {Role: openai.ChatMessageRoleUser, Content: "分析微服务架构迁移至秒云容器云(MYCP)方案"},
        },
        Stream: true,
    }

    stream, err := client.CreateChatCompletionStream(ctx, req)
    if err != nil { panic(err) }
    defer stream.Close()

    for {
        response, err := stream.Recv()
        if errors.Is(err, io.EOF) { break }
        if err != nil { panic(err) }
        fmt.Print(response.Choices[0].Delta.Content)
    }
}

// 企业级 Java 17+ 标准 SDK 或 Spring AI / OkHttp3 流式接入示例
import com.theokanning.openai.client.OpenAiApi;
import com.theokanning.openai.service.OpenAiService;
import com.theokanning.openai.completion.chat.*;
import java.time.Duration;
import java.util.List;

public class MiaoYunGatewayClient {
    public static void main(String[] args) {
        // 秒云Tokens 管家 分发地址与统一鉴权 Key
        OpenAiApi api = OpenAiApi.builder()
            .baseUrl("https://maas.miaoyun.net.cn/v1")
            .apiKey("my-sk-xxxxxxxxxxxxxxxxxxxxxxxx")
            .timeout(Duration.ofSeconds(60))
            .build();
        OpenAiService service = new OpenAiService(api);

        ChatCompletionRequest request = ChatCompletionRequest.builder()
            .model("deepseek-v4-pro")
            .messages(List.of(
                new ChatMessage("system", "You are an enterprise AI architect."),
                new ChatMessage("user", "计算秒云智能运维分析平台(MYDI)的指标收敛模型")
            ))
            .stream(true)
            .build();

        // 零阻断 SSE 流式接收
        service.streamChatCompletion(request)
            .doOnError(Throwable::printStackTrace)
            .blockingForEach(chunk -> {
                String content = chunk.getChoices().get(0).getMessage().getContent();
                if (content != null) System.out.print(content);
            });
    }
}

// Node.js / TypeScript 官方 SDK 接入方式
import OpenAI from 'openai';

const openai = new OpenAI({
  apiKey: 'my-sk-xxxxxxxxxxxxxxxxxxxxxxxx',  // 秒云Tokens管家统一 API Key
  baseURL: 'https://maas.miaoyun.net.cn/v1',  // 秒云Tokens管家路由地址
});

async function main() {
  const stream = await openai.chat.completions.create({
    model: 'glm-5.3',
    messages: [{ role: 'user', content: '评估生产环境大模型动态分池与前缀缓存策略' }],
    stream: true,
  });

  for await (const chunk of stream) {
    process.stdout.write(chunk.choices[0]?.delta?.content || '');
  }
}
main();

# 直接通过终端或 CI/CD 流水线调用 秒云Tokens 管家 流式接口
curl -N -X POST https://maas.miaoyun.net.cn/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer my-sk-xxxxxxxxxxxxxxxxxxxxxxxx" \
  -d '{
    "model": "qwen3.8-max",
    "messages": [
      {"role": "system", "content": "You are an enterprise AI agent."},
      {"role": "user", "content": "Hello MiaoYun Tokens Gateway!"}
    ],
    "stream": true
  }'