Quickstart

The gateway base URL is https://llms.party/v1. Authenticate with your API key:

export LLMS_PARTY_KEY="sk-..."

1. Confirm the key

GET /v1/models is scoped to what the key may call. It is the cheapest round-trip and the first thing to try when a request fails.

curl -sS "https://llms.party/v1/models" \
  -H "Authorization: Bearer $LLMS_PARTY_KEY"

const response = await fetch('https://llms.party/v1/models', {
  headers: { authorization: `Bearer ${process.env.LLMS_PARTY_KEY}` },
});
const { data } = await response.json();
console.log(data);

import os
import requests
 
response = requests.get(
    "https://llms.party/v1/models",
    headers={"Authorization": f"Bearer {os.environ['LLMS_PARTY_KEY']}"},
    timeout=30,
)
print(response.json()["data"])

A 401 means the key is wrong or revoked. An empty data array means the key has no model groups.

2. First completion

curl -sS "https://llms.party/v1/chat/completions" \
  -H "Authorization: Bearer $LLMS_PARTY_KEY" \
  -H "content-type: application/json" \
  -d '{
    "model": "deepseek-flash",
    "messages": [{"role": "user", "content": "Explain an LLM gateway in one sentence."}]
  }'

import OpenAI from 'openai';
 
const client = new OpenAI({
  baseURL: 'https://llms.party/v1',
  apiKey: process.env.LLMS_PARTY_KEY,
});
 
const completion = await client.chat.completions.create({
  model: 'deepseek-flash',
  messages: [
    { role: 'user', content: 'Explain an LLM gateway in one sentence.' },
  ],
});
 
console.log(completion.choices[0]?.message.content);

import os
 
from openai import OpenAI
 
client = OpenAI(
    base_url="https://llms.party/v1",
    api_key=os.environ["LLMS_PARTY_KEY"],
)
 
completion = client.chat.completions.create(
    model="deepseek-flash",
    messages=[{"role": "user", "content": "Explain an LLM gateway in one sentence."}],
)
 
print(completion.choices[0].message.content)

Any OpenAI-compatible client works. Chat, streaming and vision use the OpenAI chat shape; video uses the video API.

3. Stream it

Set "stream": true and read SSE.

curl -N -sS "https://llms.party/v1/chat/completions" \
  -H "Authorization: Bearer $LLMS_PARTY_KEY" \
  -H "content-type: application/json" \
  -d '{
    "model": "deepseek-v4-pro",
    "stream": true,
    "messages": [{"role": "user", "content": "Plan a migration in three bullets."}]
  }'

const stream = await client.chat.completions.create({
  model: 'deepseek-v4-pro',
  stream: true,
  messages: [{ role: 'user', content: 'Plan a migration in three bullets.' }],
});
 
for await (const chunk of stream) {
  process.stdout.write(chunk.choices[0]?.delta?.content ?? '');
}

stream = client.chat.completions.create(
    model="deepseek-v4-pro",
    stream=True,
    messages=[{"role": "user", "content": "Plan a migration in three bullets."}],
)
 
for chunk in stream:
    print(chunk.choices[0].delta.content or "", end="")

4. Try it without a terminal

Chat playground

Same completion, streamed inline, against the live gateway.

Video generation

Create a MiniMax H3 or BytePlus Seedance job and watch it poll.

Errors & limits

What each status code means and where budgets bite.