OdiRouter Model API

Model API provides different invocation protocols for different model types. Multimodal models usually use an asynchronous task protocol: create a task, poll its status, and retrieve the result. Large language models usually use synchronous or streaming protocols, returning text or incremental output within a single request.

Confirmed routes

Capability	Method	Path	Notes
Model list	GET	/v1/models	List available models
Chat Completions	POST	/v1/chat/completions	OpenAI-compatible messages
Responses	POST	/v1/responses	Unified Responses API
Multimodal submit	POST	/model/v1/queue/{endpoint}	Creates a queue request for the endpoint
Task status	GET	/model/v1/queue/{endpoint}/requests/{request_id}/status	Returns the current task status
Result fetch	GET	/model/v1/queue/{endpoint}/requests/{request_id}/response	Returns the result after completion
Task cancellation	PUT	/model/v1/queue/{endpoint}/requests/{request_id}/cancel	Cancels the task when supported
Sora-style video	POST	/v1/videos	Separate multipart video endpoint

LLM

OdiRouter LLM API is for Chat Completions and Responses API calls. Endpoints use the unified /v1 prefix, and the platform handles API Key authentication, balance checks, and request tracing.

Docs

Base configuration Base URL, authentication, common headers, and SDK configuration.

Chat Completions OpenAI-compatible non-streaming chat completions.

Streaming Responses Chat Completions streaming responses returned as SSE events.

Responses API Unified Responses API path and response handling.

Errors Common error responses, HTTP status codes, and client handling suggestions.

Quick call

curl

export BASE_URL="https://odirouter.ai/v1"
export API_KEY="YOUR_API_KEY"

curl -sS "${BASE_URL}/chat/completions" \
  -H "Authorization: Bearer ${API_KEY}" \
  -H "Content-Type: application/json" \
  -H "X-Request-Id: demo-$(date +%s)" \
  -d '{
    "model": "gpt-4.1",
    "messages": [
      {
        "role": "user",
        "content": "Introduce OdiRouter LLM API in one sentence"
      }
    ],
    "temperature": 0.7
  }'

Python

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://odirouter.ai/v1",
)

response = client.chat.completions.create(
    model="gpt-4.1",
    messages=[
        {
            "role": "user",
            "content": "Introduce OdiRouter LLM API in one sentence",
        }
    ],
)

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

Multimodal models

Multimodal models use an asynchronous queue protocol: create a task, poll its status, and retrieve the result after completion. To stop execution, send a cancellation request. The endpoint in the URL directly uses the OdiRouter model ID, and the request body directly passes the model parameter object.

Lifecycle docs

Base configuration Base URL, authentication, endpoint, and request path.

Create task Create a multimodal task and save the fields needed for later queries.

Poll status Query task status and distinguish waiting, completion, and failure states.

Get result Retrieve image, video, audio, 3D, text, or file outputs.

Cancel task Cancel a task and understand cancellation-related states.

Errors and limitations Common errors, unsupported capabilities, and handling suggestions.

Complete code example

curl

export BASE_URL="https://odirouter.ai/model"
export ENDPOINT="nano_banana_2"
export API_KEY="YOUR_API_KEY"

COMMON_HEADERS=(
  -H "Authorization: Bearer ${API_KEY}"
  -H "Content-Type: application/json"
)

SUBMIT_RESPONSE="$(curl -sS -X POST "${BASE_URL}/v1/queue/${ENDPOINT}" \
  "${COMMON_HEADERS[@]}" \
  -d '{
    "prompt": "a cinematic photo of a cat astronaut"
  }')"

echo "${SUBMIT_RESPONSE}" | jq .

REQUEST_ID="$(echo "${SUBMIT_RESPONSE}" | jq -r '.request_id')"
STATUS_URL="$(echo "${SUBMIT_RESPONSE}" | jq -r '.status_url')"
RESPONSE_URL="$(echo "${SUBMIT_RESPONSE}" | jq -r '.response_url')"

while true; do
  STATUS_RESPONSE="$(curl -sS "${STATUS_URL}" "${COMMON_HEADERS[@]}")"
  echo "${STATUS_RESPONSE}" | jq .

  STATUS="$(echo "${STATUS_RESPONSE}" | jq -r '.status')"
  ERROR="$(echo "${STATUS_RESPONSE}" | jq -r '.error // empty')"

  if [ "${STATUS}" = "COMPLETED" ]; then
    if [ -n "${ERROR}" ]; then
      echo "task failed: ${ERROR}"
      exit 1
    fi
    break
  fi

  sleep 3
done

curl -sS "${RESPONSE_URL}" "${COMMON_HEADERS[@]}" | jq .

Python

import time
import requests

BASE_URL = "https://odirouter.ai/model"
ENDPOINT = "nano_banana_2"
API_KEY = "YOUR_API_KEY"

headers = {
    "Authorization": f"Bearer {API_KEY}",
    "Content-Type": "application/json",
}

submit_resp = requests.post(
    f"{BASE_URL}/v1/queue/{ENDPOINT}",
    headers=headers,
    json={
        "prompt": "a cinematic photo of a cat astronaut",
    },
    timeout=30,
)
submit_resp.raise_for_status()
submit_body = submit_resp.json()

request_id = submit_body["request_id"]
status_url = submit_body["status_url"]
response_url = submit_body["response_url"]

while True:
    status_resp = requests.get(status_url, headers=headers, timeout=30)
    status_resp.raise_for_status()
    status_body = status_resp.json()

    status = status_body["status"]
    if status == "COMPLETED":
        if "error" in status_body:
            raise RuntimeError(f"{status_body.get('error_type')}: {status_body['error']}")
        break

    time.sleep(3)

result_resp = requests.get(response_url, headers=headers, timeout=30)
result_resp.raise_for_status()
result_body = result_resp.json()

print("request_id:", request_id)
print("result:", result_body)