ds2api/API.md

API 文档

本文档详细介绍 DS2API 提供的所有 API 端点。

基础信息

• Base URL: https://your-domain.com 或 http://localhost:5001
• 认证方式: Bearer Token
• 响应格式: JSON

OpenAI 兼容接口

获取模型列表

GET /v1/models

响应示例:

{
  "object": "list",
  "data": [
    {"id": "deepseek-chat", "object": "model", "owned_by": "deepseek"},
    {"id": "deepseek-reasoner", "object": "model", "owned_by": "deepseek"},
    {"id": "deepseek-chat-search", "object": "model", "owned_by": "deepseek"},
    {"id": "deepseek-reasoner-search", "object": "model", "owned_by": "deepseek"}
  ]
}

---

对话补全

POST /v1/chat/completions
Authorization: Bearer your-api-key
Content-Type: application/json

请求参数:

参数	类型	必填	说明
model	string	✅	模型名称
messages	array	✅	对话消息列表
stream	boolean	❌	是否流式输出，默认 false
temperature	number	❌	温度参数，0-2
max_tokens	number	❌	最大输出 token 数

支持的模型:

模型	thinking_enabled	search_enabled	说明
deepseek-chat	❌	❌	标准对话
deepseek-reasoner	✅	❌	深度思考（R1 推理）
deepseek-chat-search	❌	✅	联网搜索
deepseek-reasoner-search	✅	✅	深度思考 + 联网搜索

请求示例:

{
  "model": "deepseek-reasoner-search",
  "messages": [
    {"role": "system", "content": "你是一个有帮助的助手。"},
    {"role": "user", "content": "今天有什么重要新闻？"}
  ],
  "stream": true
}

流式响应格式 (stream: true):

data: {"id":"...","object":"chat.completion.chunk","choices":[{"delta":{"role":"assistant"},"index":0}]}

data: {"id":"...","object":"chat.completion.chunk","choices":[{"delta":{"reasoning_content":"让我思考一下..."},"index":0}]}

data: {"id":"...","object":"chat.completion.chunk","choices":[{"delta":{"content":"根据搜索结果..."},"index":0}]}

data: {"id":"...","object":"chat.completion.chunk","choices":[{"index":0,"finish_reason":"stop"}]}

data: [DONE]

非流式响应格式 (stream: false):

{
  "id": "chatcmpl-xxx",
  "object": "chat.completion",
  "created": 1699000000,
  "model": "deepseek-reasoner",
  "choices": [{
    "index": 0,
    "message": {
      "role": "assistant",
      "content": "回复内容",
      "reasoning_content": "思考过程（仅 reasoner 模型）"
    },
    "finish_reason": "stop"
  }],
  "usage": {
    "prompt_tokens": 10,
    "completion_tokens": 50,
    "total_tokens": 60
  }
}

---

管理接口

所有管理接口需要在请求头中携带 Authorization: Bearer <DS2API_ADMIN_KEY>。

登录

POST /admin/login
Content-Type: application/json

请求体:

{
  "key": "your-admin-key"
}

响应:

{
  "success": true,
  "token": "jwt-token",
  "expires_in": 86400
}

---

获取配置

GET /admin/config
Authorization: Bearer <jwt-token>

响应:

{
  "keys": ["api-key-1", "api-key-2"],
  "accounts": [
    {
      "email": "user@example.com",
      "password": "***",
      "token": "session-token"
    }
  ]
}

---

添加账号

POST /admin/accounts
Authorization: Bearer <jwt-token>
Content-Type: application/json

请求体:

{
  "email": "user@example.com",
  "password": "password123"
}

---

批量导入账号

POST /admin/accounts/batch
Authorization: Bearer <jwt-token>
Content-Type: application/json

请求体:

{
  "accounts": [
    {"email": "user1@example.com", "password": "pass1"},
    {"email": "user2@example.com", "password": "pass2"}
  ]
}

---

测试账号

POST /admin/accounts/test
Authorization: Bearer <jwt-token>
Content-Type: application/json

请求体:

{
  "email": "user@example.com"
}

---

批量测试所有账号

POST /admin/accounts/test-all
Authorization: Bearer <jwt-token>

---

获取队列状态

GET /admin/queue/status
Authorization: Bearer <jwt-token>

响应:

{
  "total_accounts": 5,
  "healthy_accounts": 4,
  "queue_size": 10,
  "accounts": [
    {
      "email": "user@example.com",
      "status": "healthy",
      "last_used": "2026-02-01T06:00:00Z"
    }
  ]
}

---

同步到 Vercel

POST /admin/vercel/sync
Authorization: Bearer <jwt-token>
Content-Type: application/json

请求体:

{
  "vercel_token": "your-vercel-token",
  "project_id": "your-project-id"
}

---

错误处理

所有错误响应遵循以下格式：

{
  "error": {
    "message": "错误描述",
    "type": "error_type",
    "code": "error_code"
  }
}

常见错误码:

HTTP 状态码	错误类型	说明
400	invalid_request_error	请求参数错误
401	authentication_error	API Key 无效或未提供
403	permission_denied	权限不足
429	rate_limit_error	请求过于频繁
500	internal_error	服务器内部错误
503	service_unavailable	无可用账号

---

使用示例

Python

import openai

client = openai.OpenAI(
    api_key="your-api-key",
    base_url="https://your-domain.com/v1"
)

response = client.chat.completions.create(
    model="deepseek-reasoner",
    messages=[{"role": "user", "content": "你好"}],
    stream=True
)

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

cURL

curl https://your-domain.com/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer your-api-key" \
  -d '{
    "model": "deepseek-chat",
    "messages": [{"role": "user", "content": "你好"}]
  }'

JavaScript

const response = await fetch('https://your-domain.com/v1/chat/completions', {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
    'Authorization': 'Bearer your-api-key'
  },
  body: JSON.stringify({
    model: 'deepseek-chat-search',
    messages: [{ role: 'user', content: '今天有什么新闻？' }],
    stream: true
  })
});

const reader = response.body.getReader();
const decoder = new TextDecoder();

while (true) {
  const { done, value } = await reader.read();
  if (done) break;
  console.log(decoder.decode(value));
}