API Reference Documentation

curl -X POST "https://api.sanki.ink/v1/chat/completions" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "MiniMax-M3",
    "messages": [
      {"role": "user", "content": "Hello, Sanki!"}
    ]
  }'

curl -X POST "https://api.sanki.ink/v1/messages" \
  -H "x-api-key: YOUR_API_KEY" \
  -H "anthropic-version: 2023-06-01" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "deepseek-v4-pro",
    "max_tokens": 1024,
    "messages": [
      {"role": "user", "content": "Hello, Sanki!"}
    ]
  }'

sk-yt1zAiMnFWCH3OwAfwXZEMGRnIgLq1mxkxxUSlDaHgq3jOGTlSJUc6TPUuMzo
└sk─── 61 char base62 (A-Z a-z 0-9) ───────────────────────┘

Authorization: Bearer YOUR_API_KEY

x-api-key: YOUR_API_KEY
anthropic-version: 2023-06-01

curl -X POST "https://api.sanki.ink/v1/chat/completions" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "MiniMax-M3",
    "messages": [
      {"role": "system", "content": "你是专业的 AI 助手"},
      {"role": "user", "content": "解释量子计算"}
    ],
    "temperature": 0.7,
    "max_tokens": 1024
  }'

from openai import OpenAI

client = OpenAI(
    base_url="https://api.sanki.ink/v1",
    api_key="YOUR_API_KEY"
)

response = client.chat.completions.create(
    model="gpt-4o",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

print(response.choices[0].message.content)

{
  "id": "chatcmpl-abc123",
  "object": "chat.completion",
  "created": 1700000000,
  "model": "MiniMax-M3",
  "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
  }
}

curl -X POST "https://api.sanki.ink/v1/messages" \
  -H "x-api-key: YOUR_API_KEY" \
  -H "anthropic-version: 2023-06-01" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "deepseek-v4-pro",
    "max_tokens": 1024,
    "system": "你是专业的 AI 助手",
    "messages": [
      {"role": "user", "content": "解释量子计算"}
    ]
  }'

from anthropic import Anthropic

client = Anthropic(
    base_url="https://api.sanki.ink/v1",
    api_key="YOUR_API_KEY"
)

response = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=1024,
    system="你是专业的 AI 助手",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

print(response.content[0].text)

{
  "id": "msg_abc123",
  "type": "message",
  "role": "assistant",
  "model": "deepseek-v4-pro",
  "content": [
    {
      "type": "text",
      "text": "Hello! How can I help you today?"
    }
  ],
  "usage": {
    "input_tokens": 10,
    "output_tokens": 9
  }
}

curl -X POST "https://api.sanki.ink/v1/responses" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-4o",
    "input": "解释量子计算的基本原理",
    "max_output_tokens": 1024
  }'

curl -X POST "https://api.sanki.ink/v1/images/generations" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "doubao-seedream-4-0-250828",
    "prompt": "a cat sitting on a cloud",
    "n": 1,
    "size": "1024x1024"
  }'

{
  "created": 1720000000,
  "data": [
    {
      "url": "https://...",
      "revised_prompt": "A detailed illustration of..."
    }
  ]
}

curl -X POST "https://api.sanki.ink/v1/videos/generations" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "kling-v1",
    "prompt": "a sunset over the ocean with waves",
    "duration": 5,
    "size": "1920x1080"
  }'

{
  "task_id": "task_abc123",
  "status": "processing",
  "message": "Video generation started"
}

curl "https://api.sanki.ink/v1/videos/task_abc123" \
  -H "Authorization: Bearer YOUR_API_KEY"

{
  "task_id": "task_abc123",
  "status": "completed",
  "video_url": "https://...",
  "duration": 5,
  "size": "1920x1080"
}

curl -X POST "https://api.sanki.ink/v1/chat/completions" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "MiniMax-M3",
    "messages": [{"role": "user", "content": "讲个故事"}],
    "stream": true
  }'

curl "https://api.sanki.ink/v1/models" \
  -H "Authorization: Bearer YOUR_API_KEY"

{
  "error": {
    "type": "insufficient_quota",
    "message": "余额不足，当前余额 ¥0.50，本次调用需要 ¥0.15",
    "code": 402
  }
}

pip install openai

from openai import OpenAI

client = OpenAI(
    base_url="https://api.sanki.ink/v1",
    api_key="YOUR_API_KEY"
)

response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Hello!"}]
)

print(response.choices[0].message.content)

npm install openai

import OpenAI from 'openai';

const client = new OpenAI({
  baseURL: 'https://api.sanki.ink/v1',
  apiKey: 'YOUR_API_KEY',
});

const response = await client.chat.completions.create({
  model: 'gpt-4o',
  messages: [{ role: 'user', content: 'Hello!' }],
});

console.log(response.choices[0].message.content);

pip install anthropic

from anthropic import Anthropic

client = Anthropic(
    base_url="https://api.sanki.ink/v1",
    api_key="YOUR_API_KEY"
)

response = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Hello!"}]
)

print(response.content[0].text)

export ANTHROPIC_BASE_URL="https://api.sanki.ink/v1"
export ANTHROPIC_API_KEY="YOUR_SANKI_API_KEY"

go get github.com/sashabaranov/go-openai

package main

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

func main() {
    config := openai.DefaultConfig("YOUR_API_KEY")
    config.BaseURL = "https://api.sanki.ink/v1"
    client := openai.NewClientWithConfig(config)

    resp, err := client.CreateChatCompletion(context.Background(), openai.ChatCompletionRequest{
        Model: "deepseek-v4-pro",
        Messages: []openai.ChatCompletionMessage{
            {Role: "user", Content: "Hello!"},
        },
    })
    if err != nil {
        panic(err)
    }
    fmt.Println(resp.Choices[0].Message.Content)
}