文档

快速开始

PingToken 提供统一的 API 端点来访问多种 AI 大模型。所有请求发送至 https://pingtoken.cn/api/v1

curl https://pingtoken.cn/api/v1/chat/completions \
  -H "Authorization: Bearer YOUR_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "deepseek-v4-pro",
    "messages": [{"role": "user", "content": "Hello"}]
  }'

Base URL: https://pingtoken.cn/api/v1

认证方式

在控制台的令牌管理页面创建 API 令牌。每个令牌可以限制只能访问特定模型并设置速率限制。所有 API 请求必须在 Authorization 请求头中携带令牌。

Include your token in the Authorization header as a Bearer token:

Authorization: Bearer YOUR_API_TOKEN

Tokens are created from the Console → Token Management page. The raw token value is shown only once upon creation — store it securely.

对话补全

向 AI 模型发送消息并获取回复。支持流式和非流式两种模式。

Endpoint

POST https://pingtoken.cn/api/v1/chat/completions

Request Body

Response

{
  "id": "chatcmpl-abc123",
  "model": "deepseek-v4-pro",
  "choices": [{
    "index": 0,
    "message": {
      "role": "assistant",
      "content": "Hello! How can I help you today?"
    },
    "finish_reason": "stop"
  }],
  "usage": {
    "prompt_tokens": 10,
    "completion_tokens": 9,
    "total_tokens": 19
  }
}

Code Examples

import requests

url = "https://pingtoken.cn/api/v1/chat/completions"
headers = {
    "Authorization": "Bearer YOUR_API_TOKEN",
    "Content-Type": "application/json"
}
data = {
    "model": "deepseek-v4-pro",
    "messages": [
        {"role": "user", "content": "Hello, how are you?"}
    ]
}

response = requests.post(url, headers=headers, json=data)
result = response.json()

# Print the assistant's reply
print(result["choices"][0]["message"]["content"])
print(f"Tokens used: {result['usage']['total_tokens']}")

# Streaming example
data["stream"] = True
with requests.post(url, headers=headers, json=data, stream=True) as r:
    for line in r.iter_lines():
        if line:
            line = line.decode("utf-8")
            if line.startswith("data: ") and line != "data: [DONE]":
                import json
                chunk = json.loads(line[6:])
                content = chunk["choices"][0].get("delta", {}).get("content", "")
                if content:
                    print(content, end="", flush=True)

import java.net.URI;
import java.net.http.*;
import java.io.*;
import com.google.gson.*;

public class ChatExample {
    public static void main(String[] args) throws Exception {
        HttpClient client = HttpClient.newHttpClient();

        JsonObject data = new JsonObject();
        data.addProperty("model", "deepseek-v4-pro");
        JsonArray messages = new JsonArray();
        JsonObject msg = new JsonObject();
        msg.addProperty("role", "user");
        msg.addProperty("content", "Hello, how are you?");
        messages.add(msg);
        data.add("messages", messages);

        HttpRequest request = HttpRequest.newBuilder()
            .uri(URI.create("https://pingtoken.cn/api/v1/chat/completions"))
            .header("Authorization", "Bearer YOUR_API_TOKEN")
            .header("Content-Type", "application/json")
            .POST(HttpRequest.BodyPublishers.ofString(data.toString()))
            .build();

        HttpResponse<String> response = client.send(request,
            HttpResponse.BodyHandlers.ofString());

        JsonObject result = JsonParser.parseString(response.body())
            .getAsJsonObject();

        String content = result.getAsJsonArray("choices")
            .get(0).getAsJsonObject()
            .getAsJsonObject("message")
            .get("content").getAsString();
        System.out.println(content);

        int totalTokens = result.getAsJsonObject("usage")
            .get("total_tokens").getAsInt();
        System.out.println("Tokens used: " + totalTokens);
    }
}

// Requires: JDK 11+ (HttpClient), Gson for JSON parsing
// Add to pom.xml:
// <dependency>
//   <groupId>com.google.code.gson</groupId>
//   <artifactId>gson</artifactId>
//   <version>2.10.1</version>
// </dependency>

// Node.js 18+ (built-in fetch)
// For older Node.js, install: npm install node-fetch

const url = "https://pingtoken.cn/api/v1/chat/completions";
const headers = {
  "Authorization": "Bearer YOUR_API_TOKEN",
  "Content-Type": "application/json"
};
const body = {
  model: "deepseek-v4-pro",
  messages: [
    { role: "user", content: "Hello, how are you?" }
  ]
};

// Non-streaming request
const response = await fetch(url, {
  method: "POST",
  headers,
  body: JSON.stringify(body)
});
const result = await response.json();

console.log(result.choices[0].message.content);
console.log(`Tokens used: ${result.usage.total_tokens}`);

// Streaming request
body.stream = true;
const streamResp = await fetch(url, {
  method: "POST",
  headers,
  body: JSON.stringify(body)
});

const reader = streamResp.body.getReader();
const decoder = new TextDecoder();
let buffer = "";

while (true) {
  const { done, value } = await reader.read();
  if (done) break;
  buffer += decoder.decode(value, { stream: true });
  const lines = buffer.split("\n");
  buffer = lines.pop() || "";
  for (const line of lines) {
    if (line.startsWith("data: ") && line !== "data: [DONE]") {
      const chunk = JSON.parse(line.slice(6));
      const content = chunk.choices[0]?.delta?.content;
      if (content) process.stdout.write(content);
    }
  }
}

可用模型

浏览模型广场查看所有支持的模型及详细定价信息。

Note: PingToken only supports domestic Chinese AI models. Foreign models (Claude, OpenAI/GPT, Gemini, etc.) are not supported.

Popular models include:

View the complete list at the Model Plaza.

定价说明

每个模型按千 Token 分别计费，输入和输出价格不同。Pro 订阅用户享受专属折扣价格。具体价格请查看模型广场。

Usage costs are deducted from your wallet balance automatically. You can top up your balance from the Console → Wallet page.

速率限制

免费用户：60 次请求/分钟。Pro 用户：600 次请求/分钟。如需更高限制请联系我们。

Rate limits are applied per API token. When the limit is exceeded, the API returns a 429 Too Many Requests response. Each token can have its own rate limit configured during creation.

客户端配置

Configure your PingToken model in various client tools. Replace MODEL_ID with the actual model ID and YOUR_API_TOKEN with your PingToken API key.

Base URL: https://pingtoken.cn/api/v1

Cursor

File: ~/.cursor/settings.json

{
  "chat.model": "MODEL_ID",
  "chat.openAiApiOverride": "https://pingtoken.cn/api/v1",
  "chat.openAiApiKeyOverride": "YOUR_API_TOKEN"
}

Cherry Studio

在 Cherry Studio 的模型提供商配置中添加 OpenAI 兼容提供商：

{
  "type": "openai",
  "name": "PingToken",
  "apiKey": "YOUR_API_TOKEN",
  "apiUrl": "https://pingtoken.cn/api/v1",
  "models": ["MODEL_ID"]
}

Cline (VS Code Extension)

File: cline_mcp_settings.json

{
  "apiProvider": "openai",
  "openAiApiKey": "YOUR_API_TOKEN",
  "openAiBaseUrl": "https://pingtoken.cn/api/v1",
  "openAiModelId": "MODEL_ID"
}

Dify

在 Dify 的模型提供商中选择「OpenAI API Compatible」：

{
  "provider": "openai_api_compatible",
  "model": "MODEL_ID",
  "api_key": "YOUR_API_TOKEN",
  "base_url": "https://pingtoken.cn/api/v1"
}

Claude Code Router

File: ~/.claude-code-router/config.json

{
  "Providers": [
    {
      "name": "pingtoken",
      "api_base_url": "https://pingtoken.cn/api/v1/chat/completions",
      "api_key": "YOUR_API_TOKEN",
      "models": ["MODEL_ID"]
    }
  ],
  "Router": {
    "default": "pingtoken,MODEL_ID"
  }
}

Codex CLI

通过环境变量或配置文件设置：

# 环境变量方式
export CODEX_API_BASE="https://pingtoken.cn/api/v1"
export CODEX_MODEL="MODEL_ID"
export CODEX_API_KEY="YOUR_API_TOKEN"

# codex_config.json 方式:
# {
#   "apiBase": "https://pingtoken.cn/api/v1",
#   "model": "MODEL_ID",
#   "apiKey": "YOUR_API_TOKEN"
# }

Qwen Code

File: qwen_code_config.json

{
  "api_base": "https://pingtoken.cn/api/v1",
  "api_key": "YOUR_API_TOKEN",
  "model": "MODEL_ID"
}

Lingma

File: lingma_config.json

{
  "apiKey": "YOUR_API_TOKEN",
  "baseUrl": "https://pingtoken.cn/api/v1",
  "model": "MODEL_ID"
}

帮助文档

欢迎使用 PingToken 帮助文档。这里提供详细的使用指南和操作说明，帮助您快速上手平台功能。

Authorization: Bearer YOUR_API_TOKEN

import requests

url = "https://pingtoken.cn/api/v1/chat/completions"
headers = {
    "Authorization": "Bearer YOUR_API_TOKEN",
    "Content-Type": "application/json"
}
data = {
    "model": "deepseek-v4-pro",
    "messages": [{"role": "user", "content": "Hello"}]
}

response = requests.post(url, headers=headers, json=data)
print(response.json()["choices"][0]["message"]["content"])