ドキュメント

クイックスタート

PingTokenは複数のAIモデルにアクセスするための統一APIエンドポイントを提供します。すべてのリクエストは次のURLに送信されます： 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

認証

コンソールのトークン管理ページからAPIトークンを作成します。各トークンは特定のモデルとレート制限に制限できます。すべてのAPIリクエストのAuthorizationヘッダーにトークンを含めてください。

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.

チャット補完

AIモデルにメッセージを送信し、応答を受信します。ストリーミングモードと非ストリーミングモードの両方をサポートしています。

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);
    }
  }
}

利用可能なモデル

モデル広場ですべてのサポートモデルと詳細な価格をご覧いただけます。

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.

料金

各モデルは1,000トークンごとに課金され、入力と出力で異なる料金が設定されています。Proユーザーは割引料金が適用されます。具体的な価格はモデル広場をご確認ください。

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

レート制限

無料ユーザー：60リクエスト/分。Proユーザー：600リクエスト/分。より高い制限についてはお問い合わせください。

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.

クライアント設定

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"
}

ヘルプドキュメント

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"])