OpenAI SDK drop-in integration - Orq.ai Documentation

AI Gateway

Overview

The OpenAI SDK provides powerful tools for building AI applications with GPT models. Connecting the SDK to Orq.ai’s AI Gateway transforms any OpenAI integration into a production-ready system with enterprise-grade capabilities, complete observability, and access to 300+ models across 20+ providers.

Key Benefits

Orq.ai’s AI Gateway enhances the OpenAI SDK with:

Complete Observability

Track every API call, token usage, and model interaction with detailed traces and analytics

Built-in Reliability

Automatic fallbacks, retries, and load balancing for production resilience

Cost Optimization

Real-time cost tracking and spend management across all AI operations

Multi-Provider Access

Access 300+ LLMs and 20+ providers through a single, unified integration

Prerequisites

Before integrating the OpenAI SDK with Orq.ai, ensure the following are in place:

An Orq.ai account and API Key
Python 3.8+ or Node.js 18+ with TypeScript support
OpenAI SDK installed

To set up an API key, see API keys & Endpoints.

To use libraries with private models, see Onboarding Private Models.

Installation

npm install openai

pip install openai

Configuration

Set the Base URL to the AI Gateway to route calls through the API without changing any other part of the code. The Orq.ai AI Gateway provides Platform Traces, keeping full compatibility and a unified API with all models while using the OpenAI SDK.

base_url: https://api.orq.ai/v3/router

Text Generation

Basic text generation with the OpenAI SDK through Orq.ai:

import OpenAI from "openai";

const openai = new OpenAI({
  baseURL: "https://api.orq.ai/v3/router",
  apiKey: process.env.ORQ_API_KEY,
});

const response = await openai.responses.create({
  model: "openai/gpt-4o",
  instructions: "You are a helpful assistant.",
  input: "Hello!",
});

console.log(response.output_text);

from openai import OpenAI
import os

client = OpenAI(
    base_url="https://api.orq.ai/v3/router",
    api_key=os.environ.get("ORQ_API_KEY"),
)

response = client.responses.create(
    model="openai/gpt-4o",
    instructions="You are a helpful assistant.",
    input="Hello!",
)

print(response.output_text)

import OpenAI from "openai";

const openai = new OpenAI({
  baseURL: "https://api.orq.ai/v3/router",
  apiKey: process.env.ORQ_API_KEY,
});

const completion = await openai.chat.completions.create({
  model: "openai/gpt-4o",
  messages: [
    { role: "system", content: "You are a helpful assistant." },
    { role: "user", content: "Hello!" },
  ],
});

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

from openai import OpenAI
import os

client = OpenAI(
    base_url="https://api.orq.ai/v3/router",
    api_key=os.environ.get("ORQ_API_KEY"),
)

completion = client.chat.completions.create(
    model="openai/gpt-4o",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Hello!"},
    ],
)

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

Streaming Responses

Stream responses for real-time output:

import OpenAI from "openai";

const openai = new OpenAI({
  baseURL: "https://api.orq.ai/v3/router",
  apiKey: process.env.ORQ_API_KEY,
});

const stream = await openai.responses.create({
  model: "openai/gpt-4o",
  input: "Write a short story about robots.",
  stream: true,
});

for await (const event of stream) {
  if (event.type === "response.output_text.delta") {
    process.stdout.write(event.delta);
  }
}

from openai import OpenAI
import os

client = OpenAI(
    base_url="https://api.orq.ai/v3/router",
    api_key=os.environ.get("ORQ_API_KEY"),
)

stream = client.responses.create(
    model="openai/gpt-4o",
    input="Write a short story about robots.",
    stream=True,
)

for event in stream:
    if event.type == "response.output_text.delta":
        print(event.delta, end="", flush=True)

import OpenAI from "openai";

const openai = new OpenAI({
  baseURL: "https://api.orq.ai/v3/router",
  apiKey: process.env.ORQ_API_KEY,
});

const stream = await openai.chat.completions.create({
  model: "openai/gpt-4o",
  messages: [{ role: "user", content: "Write a short story about robots." }],
  stream: true,
});

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

from openai import OpenAI
import os

client = OpenAI(
    base_url="https://api.orq.ai/v3/router",
    api_key=os.environ.get("ORQ_API_KEY"),
)

stream = client.chat.completions.create(
    model="openai/gpt-4o",
    messages=[{"role": "user", "content": "Write a short story about robots."}],
    stream=True,
)

for chunk in stream:
    if chunk.choices and chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="", flush=True)

Model Selection

With Orq.ai, you can use any supported model from 20+ providers:

import OpenAI from "openai";

const openai = new OpenAI({
  baseURL: "https://api.orq.ai/v3/router",
  apiKey: process.env.ORQ_API_KEY,
});

const claudeResponse = await openai.responses.create({
  model: "anthropic/claude-sonnet-4-6",
  input: "Explain machine learning",
});

const geminiResponse = await openai.responses.create({
  model: "google-ai/gemini-2.5-flash",
  input: "Explain machine learning",
});

const groqResponse = await openai.responses.create({
  model: "groq/llama-3.3-70b-versatile",
  input: "Explain machine learning",
});

from openai import OpenAI
import os

client = OpenAI(
    base_url="https://api.orq.ai/v3/router",
    api_key=os.environ.get("ORQ_API_KEY"),
)

claude_response = client.responses.create(
    model="anthropic/claude-sonnet-4-6",
    input="Explain machine learning",
)

gemini_response = client.responses.create(
    model="google-ai/gemini-2.5-flash",
    input="Explain machine learning",
)

groq_response = client.responses.create(
    model="groq/llama-3.3-70b-versatile",
    input="Explain machine learning",
)

​AI Gateway

​Overview

​Key Benefits

Complete Observability

Built-in Reliability

Cost Optimization

Multi-Provider Access

​Prerequisites

​Installation

​Configuration

​Text Generation

​Streaming Responses

​Model Selection

AI Gateway

Overview

Key Benefits

Prerequisites

Installation

Configuration

Text Generation

Streaming Responses

Model Selection