curl https://你的域名/api/v1/auth/register \
  -H "Content-Type: application/json" \
  -d '{
    "username": "demo-user",
    "email": "demo@example.com",
    "password": "StrongPass123!"
  }'

curl https://你的域名/api/v1/auth/login \
  -H "Content-Type: application/json" \
  -d '{
    "username": "demo-user",
    "password": "StrongPass123!"
  }'

curl https://你的域名/api/v1/keys \
  -H "Authorization: Bearer <login-token>" \
  -H "Content-Type: application/json" \
  -d '{}'

curl https://你的域名/v1/models \
  -H "Authorization: Bearer sk-xxx"

curl https://你的域名/v1/chat/completions \
  -H "Authorization: Bearer sk-xxx" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen-turbo",
    "messages": [
      {"role": "user", "content": "你好，请介绍一下你自己"}
    ]
  }'

{
  "id": "chatcmpl-xxx",
  "object": "chat.completion",
  "model": "qwen-turbo",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "你好！我是 HCAI 平台的 AI 助手..."
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 12,
    "completion_tokens": 28,
    "total_tokens": 40
  }
}

pip install openai

from openai import OpenAI

client = OpenAI(
    api_key="sk-xxx",
    base_url="https://你的域名/v1",
)

# 先看模型 ID 列表。这里返回的是 OpenAI 风格的 id/object/owned_by，
# 不是官网价格页使用的完整价格字段。
models = client.models.list()
print(models)

response = client.chat.completions.create(
    model="qwen3-max",
    messages=[
        {"role": "system", "content": "你是一个有帮助的AI助手。"},
        {"role": "user", "content": "请解释什么是大语言模型"},
    ],
    temperature=0.7,
    max_tokens=1024,
)

print(response.choices[0].message.content)
print(f"Token 用量: {response.usage}")

npm install openai

import OpenAI from "openai";

const client = new OpenAI({
  apiKey: "sk-xxx",
    baseURL: "https://你的域名/v1",
});

const models = await client.models.list();
console.log(models.data.map((item) => item.id));

const response = await client.chat.completions.create({
  model: "qwen3-max",
  messages: [
    { role: "system", content: "你是一个有帮助的AI助手。" },
    { role: "user", content: "请解释什么是大语言模型" },
  ],
  temperature: 0.7,
  max_tokens: 1024,
});

console.log(response.choices[0].message.content);
console.log("Token 用量:", response.usage);

curl https://你的域名/v1/models \
  -H "Authorization: Bearer sk-xxx"

curl https://你的域名/v1/chat/completions \
  -H "Authorization: Bearer sk-xxx" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen3-max",
    "messages": [
      {"role": "system", "content": "你是一个有帮助的AI助手。"},
      {"role": "user", "content": "请解释什么是大语言模型"}
    ],
    "temperature": 0.7,
    "max_tokens": 1024
  }'

curl https://你的域名/v1/chat/completions \
  -H "X-API-Key: sk-xxx" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen-turbo",
    "messages": [
      {"role": "user", "content": "你好"}
    ]
  }'

pip install dashscope

# 配置环境变量
export OPENAI_API_KEY=your-hcai-api-key
export OPENAI_BASE_URL=https://hc-ai.cn/v1

# 启动 OpenCode
opencode

# 配置 API endpoint
export OPENAI_API_KEY=your-hcai-api-key
export OPENAI_BASE_URL=https://hc-ai.cn/v1

# 启动 OpenClaw
openclaw --model qwen3-max

# 通过 ANTHROPIC_API_KEY 和自定义 base URL 接入
# 设置环境变量
export ANTHROPIC_API_KEY=your-hcai-api-key
export ANTHROPIC_BASE_URL=https://hc-ai.cn/v1

# 启动 Claude Code
claude

# 配置 Hermes 使用 HCAI endpoint
export OPENAI_API_KEY=your-hcai-api-key
export OPENAI_BASE_URL=https://hc-ai.cn/v1

# 启动 Hermes
hermes chat --model qwen3-max

from openai import OpenAI

client = OpenAI(
    api_key="sk-xxx",
    base_url="https://你的域名/v1",
)

stream = client.chat.completions.create(
    model="qwen3-max",
    messages=[
        {"role": "system", "content": "你是一个有帮助的AI助手。"},
        {"role": "user", "content": "请写一首关于春天的短诗"},
    ],
    stream=True,
    temperature=0.7,
    max_tokens=1024,
)

for chunk in stream:
    delta = chunk.choices[0].delta if chunk.choices else None
    if delta and delta.content:
        print(delta.content, end="", flush=True)

print()

import OpenAI from "openai";

const client = new OpenAI({
  apiKey: "sk-xxx",
    baseURL: "https://你的域名/v1",
});

async function streamChat() {
  try {
    const stream = await client.chat.completions.create({
      model: "qwen3-max",
      messages: [
        { role: "system", content: "你是一个有帮助的AI助手。" },
        { role: "user", content: "请详细解释 JavaScript 的 Promise 机制" },
      ],
      stream: true,
      temperature: 0.7,
      max_tokens: 2048,
    });

    let fullContent = "";
    for await (const chunk of stream) {
      const delta = chunk.choices[0]?.delta;
      if (delta?.content) {
        process.stdout.write(delta.content);
        fullContent += delta.content;
      }
    }

    return fullContent;
  } catch (error) {
    if (error.status === 401) {
      console.error("认证失败：请检查 API Key 是否正确");
    } else if (error.status === 429) {
      console.error("请求频率过高：请稍后重试");
    } else if (error.status >= 500) {
      console.error("服务端错误：请稍后重试");
    } else {
      console.error("请求失败:", error.message);
    }
    throw error;
  }
}

// 带重试的流式调用
async function streamChatWithRetry(maxRetries = 3) {
  for (let attempt = 1; attempt <= maxRetries; attempt++) {
    try {
      return await streamChat();
    } catch (error) {
      if (attempt === maxRetries) throw error;
      const delay = Math.min(1000 * Math.pow(2, attempt - 1), 10000);
      console.log(`第 ${attempt} 次重试，等待 ${delay}ms...`);
      await new Promise((resolve) => setTimeout(resolve, delay));
    }
  }
}

streamChatWithRetry();

curl https://你的域名/v1/chat/completions \
  -H "Authorization: Bearer sk-xxx" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen3-max",
    "messages": [
      {
        "role": "system",
        "content": "你是一个专业的技术顾问，擅长用简洁的语言解释复杂概念。"
      },
      {
        "role": "user",
        "content": "什么是微服务架构？它有哪些优缺点？"
      }
    ],
    "temperature": 0.7,
    "max_tokens": 2048,
    "stream": false
  }'

curl https://你的域名/v1/chat/completions \
  -H "Authorization: Bearer sk-xxx" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen3-max",
    "messages": [
      {"role": "user", "content": "请写一段关于人工智能的短文"}
    ],
    "stream": true,
    "temperature": 0.8,
    "max_tokens": 1024
  }'

curl https://你的域名/v1/chat/completions \
  -H "Authorization: Bearer sk-xxx" \
  -H "X-Cache-Mode: implicit" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen3-max",
    "messages": [
      {"role": "system", "content": "这里放重复使用的长 system prompt 或知识库前缀"},
      {"role": "user", "content": "请总结以上内容的重点"}
    ],
    "temperature": 0.7,
    "max_tokens": 1024
  }'

curl https://你的域名/api/v1/media/videos/generate \
  -H "Authorization: Bearer <login-token>" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "wan2.7-t2v",
    "input": {
      "prompt": "一只橘猫在清晨的海边奔跑，电影感镜头，风吹起毛发"
    },
    "parameters": {
      "duration": 5,
      "resolution": "720P"
    }
  }'

const token = '你的登录 token';
const payload = {
  model: 'wan2.7-t2v',
  input: {
    prompt: '城市夜景中穿梭的无人机镜头，霓虹灯，节奏感强'
  },
  parameters: {
    duration: 5,
    resolution: '720P'
  }
};

const response = await fetch(window.location.origin + '/api/v1/media/videos/generate', {
  method: 'POST',
  headers: {
    'Authorization': `Bearer ${token}`,
    'Content-Type': 'application/json'
  },
  body: JSON.stringify(payload)
});

const result = await response.json();
console.log(result.output.task_id);

curl "https://你的域名/api/v1/media/tasks/task-xxx?model=wan2.7-t2v&resolution=720P&duration=5" \
  -H "Authorization: Bearer <login-token>"