Supported models in AI Gateway

curl "https://my.orq.ai/v3/router/responses" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $ORQ_API_KEY" \
  -d '{
    "model": "openai/gpt-5.6-sol",
    "input": "Write a one-sentence bedtime story about a unicorn."
  }'

from openai import OpenAI
import os

client = OpenAI(
  base_url="https://my.orq.ai/v3/router",
  api_key=os.getenv("ORQ_API_KEY"),
)

response = client.responses.create(
  model="openai/gpt-5.6-sol",
  input="Write a one-sentence bedtime story about a unicorn."
)

print(response.output_text)

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: 'https://my.orq.ai/v3/router',
  apiKey: process.env.ORQ_API_KEY,
});

async function main() {
  const response = await client.responses.create({
    model: "openai/gpt-5.6-sol",
    input: "Write a one-sentence bedtime story about a unicorn."
  });

  console.log(response.output_text);
}

main();

curl https://my.orq.ai/v3/router/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $ORQ_API_KEY" \
  -d '{
    "model": "openai/gpt-5.6-sol",
    "messages": [
      {
        "role": "system",
        "content": "You are a helpful assistant."
      },
      {
        "role": "user",
        "content": "Hello!"
      }
    ]
  }'

from openai import OpenAI
import os

client = OpenAI(
  base_url="https://my.orq.ai/v3/router",
  api_key=os.getenv("ORQ_API_KEY"),
)

completion = client.chat.completions.create(
  model="openai/gpt-5.6-sol",
  messages=[
    {"role": "system", "content": "You are a helpful assistant."},
    {"role": "user", "content": "Hello!"}
  ]
)

print(completion.choices[0].message)

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: 'https://my.orq.ai/v3/router',
  apiKey: process.env.ORQ_API_KEY,
});

async function main() {
  const completion = await client.chat.completions.create({
    messages: [{ role: "system", content: "You are a helpful assistant." }],
    model: "openai/gpt-5.6-sol"
  });

  console.log(completion.choices[0]);
}

main();

curl https://my.orq.ai/v3/router/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $ORQ_API_KEY" \
  -d '{
    "model": "openai/gpt-3.5-turbo-instruct",
    "prompt": "Once upon a time",
    "max_tokens": 100
  }'

from openai import OpenAI
import os

client = OpenAI(
  base_url="https://my.orq.ai/v3/router",
  api_key=os.getenv("ORQ_API_KEY"),
)

completion = client.completions.create(
  model="openai/gpt-3.5-turbo-instruct",
  prompt="Once upon a time",
  max_tokens=100
)

print(completion.choices[0].text)

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: 'https://my.orq.ai/v3/router',
  apiKey: process.env.ORQ_API_KEY,
});

async function main() {
  const completion = await client.completions.create({
    model: "openai/gpt-3.5-turbo-instruct",
    prompt: "Once upon a time",
    max_tokens: 100
  });

  console.log(completion.choices[0].text);
}

main();

curl https://my.orq.ai/v3/router/embeddings \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $ORQ_API_KEY" \
  -d '{
    "model": "openai/text-embedding-3-small",
    "input": "Hello world"
  }'

from openai import OpenAI
import os

client = OpenAI(
  base_url="https://my.orq.ai/v3/router",
  api_key=os.getenv("ORQ_API_KEY"),
)

embedding = client.embeddings.create(
  model="openai/text-embedding-3-small",
  input="Hello world"
)

print(embedding.data[0].embedding)

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: 'https://my.orq.ai/v3/router',
  apiKey: process.env.ORQ_API_KEY,
});

async function main() {
  const embedding = await client.embeddings.create({
    model: "openai/text-embedding-3-small",
    input: "Hello world"
  });

  console.log(embedding.data[0].embedding);
}

main();

curl https://my.orq.ai/v3/router/images/generations \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $ORQ_API_KEY" \
  -d '{
    "model": "openai/gpt-image-2",
    "prompt": "A beautiful sunset over mountains",
    "n": 1,
    "size": "1024x1024"
  }'

from openai import OpenAI
import os

client = OpenAI(
  base_url="https://my.orq.ai/v3/router",
  api_key=os.getenv("ORQ_API_KEY"),
)

response = client.images.generate(
  model="openai/gpt-image-2",
  prompt="A beautiful sunset over mountains",
  n=1,
  size="1024x1024"
)

print(response.data[0].url)

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: 'https://my.orq.ai/v3/router',
  apiKey: process.env.ORQ_API_KEY,
});

async function main() {
  const response = await client.images.generate({
    model: "openai/gpt-image-2",
    prompt: "A beautiful sunset over mountains",
    n: 1,
    size: "1024x1024"
  });

  console.log(response.data[0].url);
}

main();

curl https://my.orq.ai/v3/router/images/edits \
  -H "Authorization: Bearer $ORQ_API_KEY" \
  -F model="openai/gpt-image-2" \
  -F image="@body-lotion.png" \
  -F image="@bath-bomb.png" \
  -F image="@incense-kit.png" \
  -F image="@soap.png" \
  -F prompt="Generate a photorealistic image of a gift basket on a white background labeled 'Relax & Unwind' with a ribbon and handwriting-like font, containing all the items in the reference pictures."

import base64
from openai import OpenAI
import os

client = OpenAI(
  base_url="https://my.orq.ai/v3/router",
  api_key=os.getenv("ORQ_API_KEY"),
)

prompt = """
Generate a photorealistic image of a gift basket on a white background
labeled 'Relax & Unwind' with a ribbon and handwriting-like font,
containing all the items in the reference pictures.
"""

result = client.images.edit(
    model="openai/gpt-image-2",
    image=[
        open("body-lotion.png", "rb"),
        open("bath-bomb.png", "rb"),
        open("incense-kit.png", "rb"),
        open("soap.png", "rb"),
    ],
    prompt=prompt
)

image_base64 = result.data[0].b64_json
image_bytes = base64.b64decode(image_base64)

# Save the image to a file
with open("gift-basket.png", "wb") as f:
    f.write(image_bytes)

import fs from "fs";
import OpenAI, { toFile } from "openai";

const client = new OpenAI({
  baseURL: 'https://my.orq.ai/v3/router',
  apiKey: process.env.ORQ_API_KEY,
});

const imageFiles = [
    "bath-bomb.png",
    "body-lotion.png",
    "incense-kit.png",
    "soap.png",
];

const images = await Promise.all(
    imageFiles.map(async (file) =>
        await toFile(fs.createReadStream(file), null, {
            type: "image/png",
        })
    ),
);

const response = await client.images.edit({
    model: "openai/gpt-image-2",
    image: images,
    prompt: "Create a lovely gift basket with these four items in it",
});

// Save the image to a file
const image_base64 = response.data[0].b64_json;
const image_bytes = Buffer.from(image_base64, "base64");
fs.writeFileSync("basket.png", image_bytes);

curl https://my.orq.ai/v3/router/moderations \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $ORQ_API_KEY" \
  -d '{
    "model": "openai/omni-moderation-latest",
    "input": "I want to check if this text is appropriate."
  }'

from openai import OpenAI
import os

client = OpenAI(
  base_url="https://my.orq.ai/v3/router",
  api_key=os.getenv("ORQ_API_KEY"),
)

response = client.moderations.create(
  model="openai/omni-moderation-latest",
  input="I want to check if this text is appropriate."
)

print(response.results[0])

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: 'https://my.orq.ai/v3/router',
  apiKey: process.env.ORQ_API_KEY,
});

async function main() {
  const response = await client.moderations.create({
    model: "openai/omni-moderation-latest",
    input: "I want to check if this text is appropriate.",
  });

  console.log(response.results[0]);
}

main();

curl https://my.orq.ai/v3/router/classify \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $ORQ_API_KEY" \
  -d '{
    "model": "typesafe/jev-latest",
    "state": "The package arrived two days late and the box was damaged.",
    "questions": {
      "is_complaint": {
        "type": "noul",
        "instructions": "Does the customer report a problem with their order?"
      }
    }
  }'

import os
import requests

response = requests.post(
  "https://my.orq.ai/v3/router/classify",
  headers={"Authorization": f"Bearer {os.environ.get('ORQ_API_KEY')}"},
  json={
    "model": "typesafe/jev-latest",
    "state": "The package arrived two days late and the box was damaged.",
    "questions": {
      "is_complaint": {
        "type": "noul",
        "instructions": "Does the customer report a problem with their order?",
      }
    },
  },
)

print(response.json()["answers"])

const response = await fetch("https://my.orq.ai/v3/router/classify", {
  method: "POST",
  headers: {
    "Content-Type": "application/json",
    Authorization: `Bearer ${process.env.ORQ_API_KEY}`,
  },
  body: JSON.stringify({
    model: "typesafe/jev-latest",
    state: "The package arrived two days late and the box was damaged.",
    questions: {
      is_complaint: {
        type: "noul",
        instructions: "Does the customer report a problem with their order?",
      },
    },
  }),
});

console.log((await response.json()).answers);

curl https://my.orq.ai/v3/router/rerank \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $ORQ_API_KEY" \
  -d '{
    "model": "cohere/rerank-v4.0-pro",
    "query": "What is machine learning?",
    "documents": [
      "Machine learning is a branch of AI",
      "Machine learning uses data to improve",
      "AI is changing the world"
    ]
  }'

curl https://my.orq.ai/v3/router/ocr \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $ORQ_API_KEY" \
  -d '{
    "model": "mistral/mistral-ocr-4-0",
    "document": {
      "type": "document_url",
      "document_url": "https://example.com/document.pdf"
    }
  }'