> ## Documentation Index > Fetch the complete documentation index at: https://docs.orq.ai/llms.txt > Use this file to discover all available pages before exploring further. # OpenAI > Route OpenAI model requests through Orq.ai's AI Router. Set up your API key and access GPT, DALL-E, and Whisper models with caching and fallbacks. ## Setup Your API Key To use OpenAI with Orq.ai, follow these steps: 1. Navigate to **AI Router** > Providers 2. Find **OpenAI** in the list 3. Click the **Configure** button next to OpenAI 4. In the modal that opens, select **Setup your own API Key** 5. Enter a name for this configuration (e.g., "OpenAI Production") 6. Paste your OpenAI API Key into the provided field 7. Click **Save** to complete the setup Your OpenAI API key is now configured and ready to use with Orq.ai in **AI Studio** or through the **AI Router**. ## Available Models The **AI Router** supports all current OpenAI models. Here are the most commonly used: ### Recommended Models | Model | Context | Best For | | ---------------------- | ------- | -------------------------------------- | | `openai/gpt-5.4` | 128K | Latest GPT-5 generation | | `openai/gpt-5.2-pro` | 128K | Most advanced, production-ready | | `openai/gpt-4o` | 128K | High performance, widely available | | `openai/gpt-4o-mini` | 128K | Cost-effective with strong performance | | `openai/gpt-3.5-turbo` | 4K | Budget-friendly for simple tasks | #### Latest Generation (GPT-5.x) * `openai/gpt-5.4` - Latest GPT-5 generation * `openai/gpt-5.2-pro` - Most capable, production-ready * `openai/gpt-5.2-chat-latest` - GPT-5.2 latest * `openai/gpt-5.2` - GPT-5.2 base * `openai/gpt-5.1-chat-latest` - GPT-5.1 latest * `openai/gpt-5.1` - GPT-5.1 base * `openai/gpt-5-pro` - GPT-5 advanced * `openai/gpt-5-chat-latest` - GPT-5 latest * `openai/gpt-5-mini` - GPT-5 fast * `openai/gpt-5-nano` - GPT-5 lightweight * `openai/gpt-5` - GPT-5 base #### Current Generation (GPT-4.x) * `openai/gpt-4.1-2025-04-14` - GPT-4.1 April 2025 * `openai/gpt-4.1-mini-2025-04-14` - GPT-4.1 mini April 2025 * `openai/gpt-4.1-nano-2025-04-14` - GPT-4.1 nano April 2025 * `openai/gpt-4.1` - GPT-4.1 base * `openai/gpt-4.1-mini` - GPT-4.1 mini * `openai/gpt-4.1-nano` - GPT-4.1 nano * `openai/gpt-4o` - Latest GPT-4o, recommended * `openai/gpt-4o-2024-11-20` - GPT-4o November 2024 * `openai/gpt-4o-2024-08-06` - GPT-4o August 2024 * `openai/gpt-4o-2024-05-13` - GPT-4o May 2024 * `openai/gpt-4o-mini` - Optimized for speed and cost * `openai/gpt-4o-mini-2024-07-18` - GPT-4o mini July 2024 * `openai/gpt-4-turbo` - High-performance model * `openai/gpt-4-turbo-2024-04-09` - GPT-4 Turbo April 2024 #### Legacy Models * `openai/gpt-3.5-turbo` - Cost-effective, widely used * `openai/gpt-3.5-turbo-0125` - GPT-3.5 Turbo January 2025 * `openai/gpt-3.5-turbo-16k` - Extended context #### Reasoning Models (Advanced) * `openai/o3-pro` - Advanced reasoning * `openai/o3-2025-04-16` - O3 April 2025 * `openai/o3` - O3 foundation * `openai/o3-mini` - O3 lightweight * `openai/o3-mini-2025-01-31` - O3-mini January 2025 * `openai/o1-pro` - Professional reasoning * `openai/o1-2024-12-17` - O1 December 2024 * `openai/o1` - O1 foundation * `openai/o4-mini-2025-04-16` - O4-mini April 2025 * `openai/o4-mini` - O4-mini base For a complete and up-to-date list of all available OpenAI models, see [Supported Models](/docs/proxy/supported-models#chat-models). All models are available through the **AI Router** with the `openai/` prefix. Use `openai/gpt-5.4` for the latest model, or `openai/gpt-4o` for the best balance of performance, cost, and availability. Reasoning models (`o1`, `o1-pro`, `o3`, `o3-pro`, `o4-mini`) require developer mode enabled in your OpenAI account. Enable it in your account settings and accept the reasoning model terms before using these models. Configure `reasoning_effort` for o1 and o3 models through the **AI Router**. ## Quick Start Access OpenAI's GPT models through the **AI Router**. ```typescript Typescript theme={"theme":{"light":"github-light","dark":"github-dark"}} import OpenAI from "openai"; const openai = new OpenAI({ apiKey: process.env.ORQ_API_KEY, baseURL: "https://api.orq.ai/v3/router", }); const response = await openai.chat.completions.create({ model: "openai/gpt-4o", messages: [ { role: "user", content: "Explain quantum computing in simple terms", }, ], }); console.log(response.choices[0].message.content); ``` ## Using the AI Router Access OpenAI's GPT models (GPT-4, GPT-4o, GPT-4 Turbo) through the **AI Router** with advanced chat completions, streaming, function calling, and intelligent model routing. All OpenAI models are available with consistent formatting and automatic request logging. OpenAI models use the provider slug format: `openai/model-name`. For example: `openai/gpt-4o` ### Prerequisites Before making requests to the **AI Router**, you need to configure your environment and install the SDKs if you choose to use them. **Router Endpoint** To use the **AI Router** with OpenAI models, configure your OpenAI SDK client with the base URL: ``` https://api.orq.ai/v3/router ``` **Required Headers** Include the following headers in all requests: ``` Authorization: Bearer $ORQ_API_KEY Content-Type: application/json ``` Optional headers for advanced routing: ``` X-Orq-Provider: openai X-Orq-Virtual-Key: your-virtual-key-name (optional) ``` **Getting your API Key:** 1. Go to [API Keys](/docs/router/api-keys) 2. Click **Create API Key** and copy it 3. Store it in your environment as `ORQ_API_KEY` **SDK Installation** Install the OpenAI SDK for your language: ```bash Node.js/TypeScript theme={"theme":{"light":"github-light","dark":"github-dark"}} npm install openai # or yarn add openai ``` ```bash Python theme={"theme":{"light":"github-light","dark":"github-dark"}} pip install openai ``` If your OpenAI code is already functionning, you only need to change the `base_url` and `api_key` to the router endpoint and `ORQ_API_KEY`. ### Chat Completions Send messages to OpenAI models and get intelligent responses: ```typescript Typescript theme={"theme":{"light":"github-light","dark":"github-dark"}} const response = await openai.chat.completions.create({ model: "openai/gpt-4o", messages: [ { role: "system", content: "You are a helpful assistant that explains complex concepts simply.", }, { role: "user", content: "Explain machine learning", }, ], temperature: 0.7, max_tokens: 500, }); console.log(response.choices[0].message.content); ``` ```python Python theme={"theme":{"light":"github-light","dark":"github-dark"}} response = client.chat.completions.create( model="openai/gpt-4o", messages=[ { "role": "system", "content": "You are a helpful assistant that explains complex concepts simply." }, { "role": "user", "content": "Explain machine learning" } ], temperature=0.7, max_tokens=500 ) print(response.choices[0].message.content) ``` ### Function Calling OpenAI models support function calling for structured interactions: ```typescript Typescript theme={"theme":{"light":"github-light","dark":"github-dark"}} const response = await openai.chat.completions.create({ model: "openai/gpt-4o", messages: [ { role: "user", content: "What's the weather in San Francisco?", }, ], tools: [ { type: "function", function: { name: "get_weather", description: "Get the current weather in a location", parameters: { type: "object", properties: { location: { type: "string", description: "The city and state, e.g. San Francisco, CA", }, unit: { type: "string", enum: ["celsius", "fahrenheit"], }, }, required: ["location"], }, }, }, ], }); const toolCall = response.choices[0].message.tool_calls?.[0]; if (toolCall?.type === "function") { console.log(`Calling function: ${toolCall.function.name}`); console.log(`Arguments: ${toolCall.function.arguments}`); } ``` ```python Python theme={"theme":{"light":"github-light","dark":"github-dark"}} response = client.chat.completions.create( model="openai/gpt-4o", messages=[ { "role": "user", "content": "What's the weather in San Francisco?" } ], tools=[ { "type": "function", "function": { "name": "get_weather", "description": "Get the current weather in a location", "parameters": { "type": "object", "properties": { "location": { "type": "string", "description": "The city and state, e.g. San Francisco, CA" }, "unit": { "type": "string", "enum": ["celsius", "fahrenheit"] } }, "required": ["location"] } } } ] ) tool_call = response.choices[0].message.tool_calls[0] print(f"Calling function: {tool_call.function.name}") print(f"Arguments: {tool_call.function.arguments}") ``` Full reference for function tools, `tool_choice`, parallel calls, and streaming with tool calls through the **AI Router**. ### Streaming Stream responses for real-time output and improved user experience: ```typescript Typescript theme={"theme":{"light":"github-light","dark":"github-dark"}} const stream = await openai.chat.completions.create({ model: "openai/gpt-4o", messages: [ { role: "user", content: "Write a short poem about the ocean", }, ], stream: true, }); for await (const chunk of stream) { const content = chunk.choices[0]?.delta?.content || ""; process.stdout.write(content); } console.log("\n"); ``` ```python Python theme={"theme":{"light":"github-light","dark":"github-dark"}} stream = client.chat.completions.create( model="openai/gpt-4o", messages=[ { "role": "user", "content": "Write a short poem about the ocean" } ], stream=True ) for chunk in stream: print(chunk.choices[0].delta.content or "", end="", flush=True) print() ``` ```bash cURL theme={"theme":{"light":"github-light","dark":"github-dark"}} curl -X POST https://api.orq.ai/v3/router/chat/completions \ -H "Authorization: Bearer $ORQ_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "openai/gpt-4o", "messages": [ { "role": "user", "content": "Write a short poem about the ocean" } ], "stream": true }' ``` ## Using the Responses API The Responses API combines the best of Chat Completions and Assistants APIs. Use `responses.create()` with the **AI Router**: Add web search to Responses API calls with `web_search_preview` tools. Use the `reasoning` object with o-series models on the Responses API. ### Endpoint ``` POST https://api.orq.ai/v3/router/responses ``` ### Basic Usage Configure the OpenAI SDK to use the **AI Router** and call the Responses API: ```bash cURL theme={"theme":{"light":"github-light","dark":"github-dark"}} curl -X POST https://api.orq.ai/v3/router/responses \ -H "Authorization: Bearer $ORQ_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "openai/gpt-4o", "input": "Write a three sentence bedtime story about a unicorn" }' ``` ```typescript Node.js/TypeScript theme={"theme":{"light":"github-light","dark":"github-dark"}} import OpenAI from "openai"; const openai = new OpenAI({ apiKey: process.env.ORQ_API_KEY, baseURL: "https://api.orq.ai/v3/router", }); const response = await openai.responses.create({ model: "openai/gpt-4o", input: "Write a three sentence bedtime story about a unicorn", }); console.log(response); ``` ```python Python theme={"theme":{"light":"github-light","dark":"github-dark"}} from openai import OpenAI import os client = OpenAI( api_key=os.environ.get('ORQ_API_KEY'), base_url="https://api.orq.ai/v3/router" ) response = client.responses.create( model="openai/gpt-4o", input="Write a three sentence bedtime story about a unicorn" ) print(response) ``` ### With Streaming Stream responses for real-time output: ```bash cURL theme={"theme":{"light":"github-light","dark":"github-dark"}} curl -X POST https://api.orq.ai/v3/router/responses \ -H "Authorization: Bearer $ORQ_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "openai/gpt-4o", "input": "Explain quantum computing", "stream": true }' ``` ```typescript Typescript theme={"theme":{"light":"github-light","dark":"github-dark"}} const stream = await openai.responses.create({ model: "openai/gpt-4o", input: "Explain quantum computing", stream: true, }); for await (const event of stream) { console.log(event); } ``` ```python Python theme={"theme":{"light":"github-light","dark":"github-dark"}} stream = client.responses.create( model="openai/gpt-4o", input="Explain quantum computing", stream=True ) for event in stream: print(event) ``` ### With Tools Use function calling with the Responses API: ```bash cURL theme={"theme":{"light":"github-light","dark":"github-dark"}} curl -X POST https://api.orq.ai/v3/router/responses \ -H "Authorization: Bearer $ORQ_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "openai/gpt-4o", "input": "What'\''s the weather in New York?", "tools": [ { "type": "function", "function": { "name": "get_weather", "description": "Get current weather for a location", "parameters": { "type": "object", "properties": { "location": { "type": "string", "description": "City and state" } }, "required": ["location"] } } } ] }' ``` ```typescript Typescript theme={"theme":{"light":"github-light","dark":"github-dark"}} const response = await openai.responses.create({ model: "openai/gpt-4o", input: "What's the weather in New York?", tools: [ { type: "function", function: { name: "get_weather", description: "Get current weather for a location", parameters: { type: "object", properties: { location: { type: "string", description: "City and state", }, }, required: ["location"], }, }, }, ], }); console.log(response); ``` ```python Python theme={"theme":{"light":"github-light","dark":"github-dark"}} response = client.responses.create( model="openai/gpt-4o", input="What's the weather in New York?", tools=[ { "type": "function", "function": { "name": "get_weather", "description": "Get current weather for a location", "parameters": { "type": "object", "properties": { "location": { "type": "string", "description": "City and state" } }, "required": ["location"] } } } ] ) print(response) ``` ## Automatic Request Logging All requests made through the **AI Router** are automatically logged to your dashboard. You can view: * **Request details**: Model used, tokens, latency * **Cost tracking**: Per-request and aggregate costs * **Error monitoring**: Failed requests with error messages * **Performance metrics**: Response times and throughput No additional configuration is needed. Logging happens automatically. ## Troubleshooting | Issue | Problem | Solution | | ---------------------- | ------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | Rate Limiting | Too many requests to OpenAI API | Implement exponential backoff for retries. The AI Router automatically retries failed requests with appropriate delays. | | High Latency | Slow response times | Monitor dashboard for model performance. Consider using `gpt-3.5-turbo` for latency-sensitive applications. | | Invalid Request Errors | Malformed API requests | Verify model name format (`openai/model-name`). Ensure required fields are present in messages array. Check that messages contain valid role values (user, assistant, system). | | API Errors | HTTP errors from OpenAI | Handle errors with try/catch. Check error status codes and messages. Use the AI Router's automatic retry mechanism. | ## Reference * [OpenAI API Documentation](https://platform.openai.com/docs/) * [Model Pricing](https://openai.com/pricing) * [API Reference](https://platform.openai.com/docs/api-reference) * [Chat Completions Guide](https://platform.openai.com/docs/guides/chat-completions)