WorldRouter

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API reference

API reference

WorldRouter exposes an OpenAI-compatible /chat/completions endpoint. Any SDK or HTTP client that accepts a custom base URL can call it with no code changes. For image and video generation, see Media Generation.

Tip:

New to WorldRouter? Run through the Quickstart first for an API key, the base URL, and a connection test. This page assumes you already have both.

Chat completions

Endpoint

Endpoint
POST https://inference-api-pre-d80ca3.worldrouter.ai/v1/chat/completions

Authentication

Pass your API key as a Bearer token in the Authorization header:

Authorization: Bearer your_api_key

Keys are scoped to your account. Create and rotate them in the API Keys dashboard.

Request body

FieldRequiredDescription
modelyesModel ID to route to, e.g. gpt-5.4. See the Models catalog.
messagesyesArray of chat messages. Must contain at least one entry.
temperaturenoSampling temperature. Defaults depend on the model.
max_tokensnoUpper bound on output tokens. On reasoning models the budget can be fully consumed by hidden reasoning tokens, which returns an empty content with finish_reason: "length".
streamnoWhen true, the response is a Server-Sent Events stream of deltas.
tools / tool_choicenoFunction calling, same schema as OpenAI.

Any other field in the OpenAI /chat/completions schema (top_p, stop, seed, response_format, …) is accepted unchanged.

Response

A non-streaming response matches the OpenAI shape:

{
"id": "chatcmpl-...",
"object": "chat.completion",
"created": 1738960610,
"model": "gpt-5.4",
"choices": [
  {
    "index": 0,
    "message": { "role": "assistant", "content": "Hello! How can I help you today?" },
    "finish_reason": "stop"
  }
],
"usage": {
  "prompt_tokens": 13,
  "completion_tokens": 9,
  "total_tokens": 22
}
}

Examples

curl
curl https://inference-api-pre-d80ca3.worldrouter.ai/v1/chat/completions \
  -H "Authorization: Bearer your_api_key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-5.4",
    "messages": [{ "role": "user", "content": "Hello" }]
  }'
python
from openai import OpenAI

client = OpenAI(
    api_key="your_api_key",
    base_url="https://inference-api-pre-d80ca3.worldrouter.ai/v1",
)

response = client.chat.completions.create(
    model="gpt-5.4",
    messages=[{"role": "user", "content": "Hello"}],
)

print(response.choices[0].message.content)
javascript
import OpenAI from "openai";

const client = new OpenAI({
  apiKey: "your_api_key",
  baseURL: "https://inference-api-pre-d80ca3.worldrouter.ai/v1",
});

const response = await client.chat.completions.create({
  model: "gpt-5.4",
  messages: [{ role: "user", content: "Hello" }],
});

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

Streaming

Set stream: true in the request body. The response becomes a Server-Sent Events stream. Each chunk follows the OpenAI chat.completion.chunk shape, and the stream terminates with a data: [DONE] line:

curl
curl https://inference-api-pre-d80ca3.worldrouter.ai/v1/chat/completions \
  -H "Authorization: Bearer your_api_key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-5.4",
    "stream": true,
    "messages": [{ "role": "user", "content": "Hello" }]
  }'
python
from openai import OpenAI

client = OpenAI(
    api_key="your_api_key",
    base_url="https://inference-api-pre-d80ca3.worldrouter.ai/v1",
)

stream = client.chat.completions.create(
    model="gpt-5.4",
    messages=[{"role": "user", "content": "Hello"}],
    stream=True,
)

for chunk in stream:
    delta = chunk.choices[0].delta.content
    if delta:
        print(delta, end="", flush=True)
javascript
import OpenAI from "openai";

const client = new OpenAI({
  apiKey: "your_api_key",
  baseURL: "https://inference-api-pre-d80ca3.worldrouter.ai/v1",
});

const stream = await client.chat.completions.create({
  model: "gpt-5.4",
  messages: [{ role: "user", content: "Hello" }],
  stream: true,
});

for await (const chunk of stream) {
  const delta = chunk.choices[0]?.delta?.content;
  if (delta) process.stdout.write(delta);
}

Error codes

CodeMeaningFix
400Invalid request (unknown model, malformed body, unsupported parameter)Verify the model ID matches the Models page (IDs are case-sensitive) and check the request body against the field table above.
401Invalid or missing API keyCheck that your key is set correctly and has not been revoked in the dashboard.
402Insufficient creditsTop up on the Credits page, then retry.
429Rate limitedBack off and retry with exponential delay. Consider spreading load across models.
500Server errorRetry the request. If it persists, try a different model or contact support.

See also

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