imMAAS API 文档

https://immaas.com/v1

curl https://immaas.com/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-your-api-key" \
  -d '{
    "model": "gpt-5.5",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

from openai import OpenAI

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

resp = client.chat.completions.create(
    model="gpt-5.5",
    messages=[{"role": "user", "content": "Hello!"}],
)
print(resp.choices[0].message.content)

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://immaas.com/v1",
  apiKey: "sk-your-api-key",
});

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

Authorization: Bearer sk-your-api-key

curl -X POST https://immaas.com/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-xxx" \
  -d '{
    "model": "claude-sonnet-5",
    "messages": [
      {"role": "system", "content": "You are a helpful assistant."},
      {"role": "user", "content": "用一句话介绍量子计算"}
    ],
    "max_tokens": 1024
  }'

from openai import OpenAI

client = OpenAI(base_url="https://immaas.com/v1", api_key="sk-xxx")

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

curl https://immaas.com/v1/models \
  -H "Authorization: Bearer sk-xxx"

curl -X POST https://immaas.com/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-xxx" \
  -d '{"model": "gpt-5.6", "messages": [{"role": "user", "content": "1+1=?"}]}'

curl -X POST https://immaas.com/v1/images/generations \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-xxx" \
  -d '{
    "model": "gpt-image-2",
    "prompt": "A serene lake at sunset, mountains in the background",
    "size": "1024x1024",
    "n": 1
  }'

import time, requests

BASE = "https://immaas.com/v1"
HEADERS = {"Authorization": "Bearer sk-xxx"}

# 1. 提交视频任务
r = requests.post(f"{BASE}/videos", headers=HEADERS, json={
    "model": "kling-v3",
    "prompt": "赛博朋克城市夜景，霓虹灯闪烁，电影级画质",
    "duration": "5",
})
task_id = r.json()["task_id"]

# 2. 每 5 秒轮询直到完成
while True:
    resp = requests.get(f"{BASE}/videos/{task_id}", headers=HEADERS).json()
    if resp["status"] == "completed":
        print("video:", resp["url"])  # MP4 直链
        break
    time.sleep(5)

curl -X POST https://immaas.com/v1/audio/speech \
  -H "Authorization: Bearer sk-xxx" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-4o-mini-tts",
    "input": "欢迎使用 imMAAS，一个密钥接入全球大模型。",
    "voice": "alloy",
    "response_format": "mp3"
  }' \
  --output speech.mp3

from openai import OpenAI

client = OpenAI(base_url="https://immaas.com/v1", api_key="sk-xxx")

with client.audio.speech.with_streaming_response.create(
    model="gpt-4o-mini-tts",
    voice="alloy",
    input="欢迎使用 imMAAS，一个密钥接入全球大模型。",
) as resp:
    resp.stream_to_file("speech.mp3")

curl -X POST https://immaas.com/v1/audio/transcriptions \
  -H "Authorization: Bearer sk-xxx" \
  -F file="@meeting.mp3" \
  -F model="gpt-4o-transcribe" \
  -F language="zh"

from openai import OpenAI

client = OpenAI(base_url="https://immaas.com/v1", api_key="sk-xxx")

with open("meeting.mp3", "rb") as f:
    resp = client.audio.transcriptions.create(
        model="gpt-4o-transcribe",
        file=f,
        language="zh",
        response_format="verbose_json",  # 返回分段 + 时间戳
    )
print(resp.text)

import asyncio, json, base64
import websockets   # pip install websockets

URL = "wss://immaas.com/v1/realtime?model=gpt-realtime"

async def main():
    async with websockets.connect(URL, extra_headers={
        "Authorization": "Bearer sk-xxx",
        "OpenAI-Beta": "realtime=v1",
    }) as ws:
        # 1. 发送音频（16kHz 16bit PCM，base64 编码）
        with open("input.pcm", "rb") as f:
            await ws.send(json.dumps({
                "type": "input_audio_buffer.append",
                "audio": base64.b64encode(f.read()).decode(),
            }))
        await ws.send(json.dumps({"type": "input_audio_buffer.commit"}))
        # 2. 触发回复并接收音频流
        await ws.send(json.dumps({
            "type": "response.create",
            "response": {"modalities": ["audio", "text"]},
        }))
        async for msg in ws:
            evt = json.loads(msg)
            if evt["type"] == "response.audio.delta":
                print("收到音频分片", len(evt["delta"]))
            elif evt["type"] == "response.done":
                break

asyncio.run(main())

import time, requests

BASE = "https://immaas.com/v1"
HEADERS = {"Authorization": "Bearer sk-xxx"}

# 1. 提交音乐任务
r = requests.post(f"{BASE}/audio/music", headers=HEADERS, json={
    "model": "suno-v5",
    "prompt": "City pop, warm male voice, relaxed and romantic, with saxophone",
    "lyrics": "[Verse] … [Chorus] …",   # 可选；留空则自动生成
    "instrumental": False,
    "duration": 120,
})
task_id = r.json()["task_id"]

# 2. 轮询直到完成（音乐生成通常 30-120 秒）
while True:
    resp = requests.get(f"{BASE}/audio/music/{task_id}", headers=HEADERS).json()
    if resp["status"] == "completed":
        print("audio:", resp["url"])   # MP3 直链
        break
    time.sleep(5)

curl -X POST https://immaas.com/v1/embeddings \
  -H "Authorization: Bearer sk-xxx" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "text-embedding-3-large",
    "input": "imMAAS 是一个全球大模型 API 聚合平台",
    "dimensions": 1024
  }'

curl -X POST https://immaas.com/v1/rerank \
  -H "Authorization: Bearer sk-xxx" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "rerank-v4",
    "query": "如何降低 API 转换成本",
    "documents": [
      "imMAAS 按 token 计费，充值即用",
      "人民币直充无需境外信用卡",
      "多渠道冗余保障服务可用性"
    ],
    "top_n": 3
  }'

{
  "results": [
    {"index": 0, "relevance_score": 0.92},
    {"index": 1, "relevance_score": 0.31},
    {"index": 2, "relevance_score": 0.05}
  ]
}