SLLY API · 接口文档

Authorization: Bearer sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

x-api-key: sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
anthropic-version: 2023-06-01

curl https://staging.sllyapi.com/v1/chat/completions \
  -H "Authorization: Bearer sk-your-key-here" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-5.5",
    "messages": [
      {"role": "user", "content": "你好，请用一句话介绍自己"}
    ]
  }'

from openai import OpenAI

client = OpenAI(
    api_key="sk-your-key-here",
    base_url="https://staging.sllyapi.com/v1",
)

resp = client.chat.completions.create(
    model="gpt-5.5",
    messages=[
        {"role": "system", "content": "你是一名专业助手"},
        {"role": "user",   "content": "用一句话解释什么是 RAG"},
    ],
    temperature=0.7,
    max_tokens=500,
)
print(resp.choices[0].message.content)
print("usage:", resp.usage)

import OpenAI from 'openai';

const client = new OpenAI({
  apiKey: 'sk-your-key-here',
  baseURL: 'https://staging.sllyapi.com/v1',
});

const resp = await client.chat.completions.create({
  model: 'gpt-5.5',
  messages: [{ role: 'user', content: '你好' }],
  max_tokens: 500,
});
console.log(resp.choices[0].message.content);

{
  "id": "chatcmpl-xxx",
  "object": "chat.completion",
  "created": 1712340000,
  "model": "gpt-5.5",
  "choices": [
    {
      "index": 0,
      "message": { "role": "assistant", "content": "..." },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 18,
    "completion_tokens": 31,
    "total_tokens": 49
  }
}

curl https://staging.sllyapi.com/v1/messages \
  -H "x-api-key: sk-your-key-here" \
  -H "anthropic-version: 2023-06-01" \
  -H "content-type: application/json" \
  -d '{
    "model": "claude-opus-4-7",
    "max_tokens": 1024,
    "messages": [{"role": "user", "content": "Hello"}]
  }'

resp = client.embeddings.create(
    model="text-embedding-3-large",
    input=["你好世界", "RAG 是什么"],
)
print(resp.data[0].embedding)   # 3072 维向量
print("usage:", resp.usage)     # 仅 prompt_tokens 计费

resp = client.images.generate(
    model="dall-e-3",
    prompt="一只在月球上喝咖啡的猫，超现实主义风格",
    size="1024x1024",
    n=1,
)
print(resp.data[0].url)   # 临时图片 URL，建议立即下载或转存

resp = client.audio.speech.create(
    model="tts-1", voice="alloy", input="你好，欢迎使用 SLLY API"
)
resp.stream_to_file("hello.mp3")

with open("audio.mp3", "rb") as f:
    resp = client.audio.transcriptions.create(model="whisper-1", file=f)
print(resp.text)

{
  "error": {
    "type":    "invalid_request_error",
    "message": "model \"xxx\" has no pricing configured",
    "code":    "pricing_unavailable"
  },
  "request_id": "req_xxx"
}

stream = client.chat.completions.create(
    model="gpt-5.5",
    messages=[{"role": "user", "content": "写一首关于秋天的短诗"}],
    stream=True,
)
for chunk in stream:
    delta = chunk.choices[0].delta.content
    if delta:
        print(delta, end="", flush=True)

tools = [{
    "type": "function",
    "function": {
        "name": "get_weather",
        "description": "查询指定城市天气",
        "parameters": {
            "type": "object",
            "properties": {
                "city": {"type": "string", "description": "城市名"},
                "unit": {"type": "string", "enum": ["c", "f"]}
            },
            "required": ["city"]
        }
    }
}]

resp = client.chat.completions.create(
    model="gpt-5.5",
    messages=[{"role": "user", "content": "北京今天天气怎么样？"}],
    tools=tools,
    tool_choice="auto",
)
tool_call = resp.choices[0].message.tool_calls[0]
print(tool_call.function.name, tool_call.function.arguments)

resp = client.chat.completions.create(
    model="gpt-5.5",
    messages=[{
        "role": "user",
        "content": [
            {"type": "text", "text": "这张图里有什么？"},
            {"type": "image_url",
             "image_url": {"url": "https://example.com/cat.jpg"}}
        ],
    }],
)