API Documentation

Authorization: Bearer xb_live_<your-api-key>

curl https://xable.com.cn/v1/chat/completions \
  -H "Authorization: Bearer xb_live_<your-key>" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "deepseek-v4-flash",
    "messages": [
      {"role": "system", "content": "你是一个有用的助手"},
      {"role": "user", "content": "请用中文介绍一下你自己"}
    ],
    "temperature": 0.7,
    "max_tokens": 2048,
    "top_p": 1,
    "frequency_penalty": 0,
    "presence_penalty": 0,
    "stream": false
  }'

curl https://xable.com.cn/v1/images/generations \
  -H "Authorization: Bearer xb_live_<your-key>" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "deepseek-v4-flash",
    "prompt": "A futuristic city with neon lights, digital art style",
    "n": 1,
    "size": "1024x1024"
  }'

from openai import OpenAI

client = OpenAI(
    base_url="https://xable.com.cn/v1",
    api_key="xb_live_<your-key>"
)

response = client.images.generate(
    model="stable-diffusion-xl-free",
    prompt="A futuristic city with neon lights",
    n=1,
    size="1024x1024"
)

print(response.data[0].url)

from openai import OpenAI

client = OpenAI(
    base_url="https://xable.com.cn/v1",
    api_key="xb_live_<your-key>"
)

# 非流式聊天
response = client.chat.completions.create(
    model="deepseek-v4-flash",
    messages=[
        {"role": "system", "content": "你是一个有用的助手"},
        {"role": "user", "content": "请用中文介绍 XABLE 平台"}
    ],
    temperature=0.7,
    max_tokens=1024
)
print(response.choices[0].message.content)

# 流式聊天
stream = client.chat.completions.create(
    model="deepseek-v4-flash",
    messages=[{"role": "user", "content": "你好"}],
    stream=True
)
for chunk in stream:
    if chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="")

import OpenAI from "openai"

const client = new OpenAI({
  baseURL: "https://xable.com.cn/v1",
  apiKey: "xb_live_<your-key>"
})

// 非流式聊天
const response = await client.chat.completions.create({
  model: "deepseek-v4-flash",
  messages: [
    { role: "system", content: "你是一个有用的助手" },
    { role: "user", content: "请用中文介绍 XABLE 平台" }
  ],
  temperature: 0.7,
  max_tokens: 1024
})
console.log(response.choices[0].message.content)

// 流式聊天
const stream = await client.chat.completions.create({
  model: "deepseek-v4-flash",
  messages: [{ role: "user", content: "你好" }],
  stream: true
})
for await (const chunk of stream) {
  if (chunk.choices[0]?.delta?.content) {
    process.stdout.write(chunk.choices[0].delta.content)
  }
}

package main

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

func main() {
    cfg := openai.DefaultConfig("xb_live_<your-key>")
    cfg.BaseURL = "https://xable.com.cn/v1"
    client := openai.NewClientWithConfig(cfg)

    // 非流式聊天
    resp, err := client.CreateChatCompletion(
        context.Background(),
        openai.ChatCompletionRequest{
            Model: "deepseek-v4-flash",
            Messages: []openai.ChatCompletionMessage{
                {Role: "system", Content: "你是一个有用的助手"},
                {Role: "user", Content: "请用中文介绍 XABLE 平台"},
            },
        },
    )
    if err != nil {
        panic(err)
    }
    fmt.Println(resp.Choices[0].Message.Content)
}

import com.theokanning.openai.OpenAiService;
import com.theokanning.openai.completion.chat.*;

List<ChatMessage> messages = new ArrayList<>();
messages.add(new ChatMessage("system", "你是一个有用的助手"));
messages.add(new ChatMessage("user", "请用中文介绍 XABLE 平台"));

OpenAiService service = new OpenAiService("xb_live_<your-key>", 30);
service.setBaseUrl("https://xable.com.cn/v1");

ChatCompletionRequest request = ChatCompletionRequest.builder()
    .model("deepseek-v4-flash")
    .messages(messages)
    .build();

service.createChatCompletion(request).getChoices()
    .forEach(c -> System.out.println(c.getMessage().getContent()));