Chat completions

POST /v1/chat/completions is the OpenAI Chat Completions API. It is the one request format that every model in the catalogue accepts, so it is the safest default for new code: switch models by changing one string.

Send a request

Point any OpenAI SDK at the base URL above and use your key. Nothing else in your code changes.

curl https://api.oneaiapikey.com/v1/chat/completions \
  -H "Authorization: Bearer $RELAYKIT_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-5.6-terra",
    "messages": [
      {"role": "system", "content": "You are a concise assistant."},
      {"role": "user", "content": "Explain what an API gateway does in two sentences."}
    ],
    "max_tokens": 300
  }'

import os
from openai import OpenAI

client = OpenAI(base_url="https://api.oneaiapikey.com/v1", api_key=os.environ["RELAYKIT_API_KEY"])

reply = client.chat.completions.create(
    model="gpt-5.6-terra",
    messages=[
        {"role": "system", "content": "You are a concise assistant."},
        {"role": "user", "content": "Explain what an API gateway does in two sentences."},
    ],
    max_tokens=300,
)
print(reply.choices[0].message.content)
print(reply.usage)

import OpenAI from "openai";

const client = new OpenAI({ baseURL: "https://api.oneaiapikey.com/v1", apiKey: process.env.RELAYKIT_API_KEY });

const reply = await client.chat.completions.create({
  model: "gpt-5.6-terra",
  messages: [
    { role: "system", content: "You are a concise assistant." },
    { role: "user", content: "Explain what an API gateway does in two sentences." },
  ],
  max_tokens: 300,
});
console.log(reply.choices[0].message.content);
console.log(reply.usage);

Request fields

Other OpenAI fields (seed, n, logprobs, presence_penalty, frequency_penalty, user …) are passed to the provider as they are. Whether they have an effect depends on the model, as it would if you called the provider directly.

Roles

The API is stateless: it does not remember earlier requests. To continue a conversation, send the whole history again, with the model’s previous answers as assistant messages:

messages = [
    {"role": "system", "content": "You are a helpful SQL tutor."},
    {"role": "user", "content": "What is a LEFT JOIN?"},
    {"role": "assistant", "content": "A LEFT JOIN returns every row from the left table …"},
    {"role": "user", "content": "Show me an example with orders and customers."},
]

Every request is billed for all the tokens it sends, so a long history costs more with each turn. Trim or summarise old turns, and see prompt caching for how repeated prefixes get cheaper.

Response

{
  "id": "chatcmpl-…",
  "object": "chat.completion",
  "created": 1791420807,
  "model": "gpt-5.6-terra",
  "choices": [
    {
      "index": 0,
      "message": { "role": "assistant", "content": "An API gateway is a single entry point …" },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 31,
    "completion_tokens": 42,
    "total_tokens": 73,
    "prompt_tokens_details": { "cached_tokens": 0 },
    "completion_tokens_details": { "reasoning_tokens": 0 }
  }
}

• choices[0].message.content is the reply. With tools it may be null and tool_calls is set instead.
• finish_reason is stop (finished), length (hit max_tokens), tool_calls (wants a tool run) or content_filter.
• usage lists the tokens you are billed for. prompt_tokens_details.cached_tokens and completion_tokens_details.reasoning_tokens appear when the provider reports them. Reasoning tokens are already included in completion_tokens.
• The X-Request-Id response header identifies the request. Quote it if you contact support.

The response carries token counts, not a price. The cost of each request is on the usage page; the rates are in the models table.

Claude models in this format

Claude models accept chat completions too: the gateway translates the request to Anthropic’s format and the answer back. Most code works unchanged. The differences:

• If you leave out max_tokens, the gateway sends 8,192, because Anthropic’s API requires a limit. Set your own.
• response_format is not forwarded to Claude. Use a forced tool or the Messages endpoint instead (see Structured output).
• n, seed, logprobs, presence_penalty, frequency_penalty and logit_bias have no Anthropic equivalent and are dropped.
• reasoning_effort turns on Claude’s extended thinking; the thinking text comes back as reasoning_content (see Reasoning models).
• Images and PDFs given by URL are downloaded by the gateway and sent to Claude inline.

If you need Anthropic-only features such as cache_control breakpoints, use the Anthropic Messages endpoint with claude-sonnet-5-5 instead.

Related

• Streaming: show the reply as it is written.
• Errors: every status code and what to do about it.
• API reference: the full endpoint list.