快速开始

只需几个步骤即可上手使用 LW AI API。

第 1 步:获取 API 密钥

请联系 support@linkwo.com 获取 API 密钥。详见 认证

第 2 步:发起你的第一次请求

使用 cURL

curl https://openapi.linkwo.ai/v1/chat/completions \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "deepseek/deepseek-v4-pro",
    "messages": [
      {"role": "user", "content": "Say hello in 5 languages"}
    ]
  }'

使用 Python(OpenAI SDK)

pip install openai
from openai import OpenAI

client = OpenAI(
    base_url="https://openapi.linkwo.ai/v1",
    api_key="YOUR_API_KEY"
)

response = client.chat.completions.create(
    model="deepseek/deepseek-v4-pro",
    messages=[
        {"role": "user", "content": "Say hello in 5 languages"}
    ]
)

print(response.choices[0].message.content)

使用 Node.js(OpenAI SDK)

npm install openai
import OpenAI from 'openai';

const client = new OpenAI({
  baseURL: 'https://openapi.linkwo.ai/v1',
  apiKey: 'YOUR_API_KEY',
});

const response = await client.chat.completions.create({
  model: 'deepseek/deepseek-v4-pro',
  messages: [{ role: 'user', content: 'Say hello in 5 languages' }],
});

console.log(response.choices[0].message.content);

第 3 步:尝试流式响应

如需实时响应,可使用流式传输:

stream = client.chat.completions.create(
    model="deepseek/deepseek-v4-pro",
    messages=[{"role": "user", "content": "Write a poem about AI"}],
    stream=True
)

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

可用模型

模型上下文适用场景
deepseek/deepseek-v4-pro1M复杂推理、编码、数学
deepseek/deepseek-v4-flash1M快速响应、通用任务
z-ai/glm-5.1200K中文、通用场景
z-ai/glm-5.21M高级推理、长上下文
linkwo/fusion多模型编排
astra64K金融和能源领域任务

完整列表请见 模型概览

下一步