TokenMark 开发者文档

SDK 示例

TokenMark 兼容 OpenAI SDK。只需把 base_url / baseURL 指向 https://tokenmark.org/v1api_key 换成你的 sk- 密钥。

curl

curl https://tokenmark.org/v1/chat/completions \
  -H "Authorization: Bearer sk-你的密钥" \
  -H "Content-Type: application/json" \
  -d '{"model": "chat", "messages": [{"role": "user", "content": "你好"}]}'

Python(openai 官方 SDK)

from openai import OpenAI

client = OpenAI(
    base_url="https://tokenmark.org/v1",
    api_key="sk-你的密钥",
)

# 非流式
resp = client.chat.completions.create(
    model="chat",
    messages=[{"role": "user", "content": "你好"}],
)
print(resp.choices[0].message.content)

# 流式
stream = client.chat.completions.create(
    model="chat",
    messages=[{"role": "user", "content": "写一首诗"}],
    stream=True,
)
for chunk in stream:
    if chunk.choices and chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="", flush=True)

Node.js(openai 官方 SDK)

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://tokenmark.org/v1",
  apiKey: "sk-你的密钥",
});

const resp = await client.chat.completions.create({
  model: "chat",
  messages: [{ role: "user", content: "你好" }],
});
console.log(resp.choices[0].message.content);

通用 OpenAI 兼容客户端

任意支持自定义 Base URL 的客户端均可接入:

客户端 Base URL 填写
NextChat (ChatGPT-Next-Web) https://tokenmark.org/v1
Cherry Studio https://tokenmark.org/v1
LangChain(OpenAI 兼容) https://tokenmark.org/v1
LiteLLM https://tokenmark.org/v1

获取可用模型

curl https://tokenmark.org/v1/models \
  -H "Authorization: Bearer sk-你的密钥"

返回的模型 ID 直接填入 model 参数。不同账户等级(免费版/标准版/VIP/企业版)可用的模型范围不同,超出范围的模型返回校验错误。