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Getting started

Serenity Edge is an OpenAI-compatible inference API run by Substrate AI on its own GPU infrastructure in Valencia, Spain. Prompts and completions are never written to disk or logs and never used for training; prompt prefixes may be cached in volatile memory for at most 24 hours (see Data residency). If your code already talks to the OpenAI API, you only need to change the base URL and the API key.

Base URLhttps://api.serenityedge.ai/v1
AuthenticationAuthorization: Bearer <key>
EndpointsPOST /v1/chat/completions, POST /v1/responses (Responses API), GET /v1/models
ModelsSee Models

1. Get an API key​

There are three ways to use Serenity Edge. Pick the one that fits you and follow its page to get a key.

Serenity Star account

Create API keys and buy prepaid credits.

Routers and marketplaces

Choose Serenity Edge as the provider from your cortecs or EUrouter account.

Enterprise

A contract with committed capacity and a service level agreement.

The examples below call the API directly at https://api.serenityedge.ai/v1, with a key from a Serenity Star account or an enterprise contract. Through a router or marketplace, use the base URL and key that the platform gives you instead, as its documentation explains.

Keep the key secret. Do not embed it in client-side code or commit it to a repository.

2. Make a request​

All examples below send the same chat completion. Replace $SERENITY_EDGE_API_KEY with your key.

curl​

curl https://api.serenityedge.ai/v1/chat/completions \
  -H "Authorization: Bearer $SERENITY_EDGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "orion-pro",
    "messages": [
      {"role": "system", "content": "You are a helpful assistant."},
      {"role": "user", "content": "Explain what a token is in one sentence."}
    ]
  }'

Python​

Install the official OpenAI library (pip install openai) and point it at Serenity Edge:

from openai import OpenAI

client = OpenAI(
    base_url="https://api.serenityedge.ai/v1",
    api_key="YOUR_SERENITY_EDGE_API_KEY",
)

completion = client.chat.completions.create(
    model="orion-pro",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Explain what a token is in one sentence."},
    ],
)

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

Node.js​

Install the official OpenAI library (npm install openai):

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://api.serenityedge.ai/v1",
  apiKey: process.env.SERENITY_EDGE_API_KEY,
});

const completion = await client.chat.completions.create({
  model: "orion-pro",
  messages: [
    { role: "system", content: "You are a helpful assistant." },
    { role: "user", content: "Explain what a token is in one sentence." },
  ],
});

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

.NET​

Install the official OpenAI NuGet package (dotnet add package OpenAI):

using System.ClientModel;
using OpenAI;
using OpenAI.Chat;

var client = new OpenAIClient(
    new ApiKeyCredential(Environment.GetEnvironmentVariable("SERENITY_EDGE_API_KEY")!),
    new OpenAIClientOptions { Endpoint = new Uri("https://api.serenityedge.ai/v1") });

ChatClient chat = client.GetChatClient("orion-pro");

ChatCompletion completion = chat.CompleteChat(
    new SystemChatMessage("You are a helpful assistant."),
    new UserChatMessage("Explain what a token is in one sentence."));

Console.WriteLine(completion.Content[0].Text);

3. Read the response​

A non-streaming response is a standard chat completion object. The usage block is what you are billed on.

{
  "id": "chatcmpl-8f0f1e2a",
  "object": "chat.completion",
  "created": 1758542400,
  "model": "orion-pro",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "A token is a small unit of text, roughly a word or part of a word, that a language model reads and writes."
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 27,
    "completion_tokens": 26,
    "total_tokens": 53,
    "prompt_tokens_details": { "cached_tokens": 0 }
  }
}

Next steps​

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