Switch from OpenAI SDK to LLM Resayil – Migration Guide

Introduction

If you’re building applications with the OpenAI SDK and are looking for a more cost‑effective, multilingual alternative that offers native Arabic language support, you’ve come to the right place. LLM Resayil’s API is fully compatible with the OpenAI SDK, runs from the United States, and provides a pay‑per‑use credit model in USD. This guide walks you through why the switch makes sense, what you need to get started, and how to migrate with minimal code changes.

Comparison Table

| Feature | LLM Resayil | OpenAI | |---|---|---| | API Compatibility | OpenAI‑compatible (same endpoints & payloads) | Native SDK | | Arabic Language Support | ✅ (built‑in) | Limited (requires prompt engineering) | | Multi‑Language Support | ✅ | ✅ | | Streaming Responses | ✅ | ✅ | | Function Calling | ✅ | ✅ | | Vision Models | ✅ | ✅ (via separate endpoint) | | Thinking Models | ✅ | ✅ | | Pay‑Per‑Use Credits | ✅ (USD) | ✅ (per‑token) | | Billing Methods | Stripe, PayPal | Credit Card, etc. | | Hosting Location | USA | Global |

What LLM Resayil Offers

LLM Resayil provides an OpenAI‑compatible API that lets you keep using the same SDKs, libraries, and tooling you already love. The platform ships with Arabic language support out of the box and can handle any of the 39 models in its catalog, ranging from high‑throughput chat models to vision‑enabled and “thinking” models. All features—streaming, function calling, tool use, and vision—are available without additional configuration, and you pay only for what you consume via a simple credit system in USD.

What OpenAI Offers

OpenAI delivers a broad suite of models, a robust ecosystem, and per‑token pricing that scales with usage. Its official SDKs are tightly integrated with the platform, and it offers advanced features such as fine‑tuning, embeddings, and a large ecosystem of third‑party tools. However, OpenAI’s pricing is token‑based, and Arabic language performance often requires prompt engineering rather than native support.

Why Switch to LLM Resayil?

Switching to LLM Resayil gives you a cost‑effective alternative that still speaks your language. Because the API mirrors OpenAI’s, you avoid a painful rewrite—just point your SDK at a new base URL. The pay‑per‑use credit model (billed in USD via Stripe or PayPal) removes the complexity of token‑level invoicing, making budgeting straightforward. Moreover, with native Arabic and multi‑language capabilities, you can serve a broader audience without extra prompt tricks. All of this runs from a secure data center in the USA, ensuring compliance for many enterprise use cases.

What You Get by Using LLM Resayil

• Full feature parity with OpenAI: streaming, function calling, vision, and tool use work exactly the same.
• Arabic‑first support: the models understand and generate Arabic fluently.
• Access to 39 diverse models, including high‑capacity thinking models like deepseek-v4-flash and vision models such as qwen3-vl:235b-instruct.
• Simple billing: buy credits in USD through Stripe or PayPal, no hidden token calculations.
• Seamless integration with popular automation and AI frameworks—n8n, LangChain, LiteLLM, and the OpenAI SDK itself.

Why Switch? (300‑word Summary)

Developers who rely on the OpenAI SDK often face two pain points: pricing opacity and language limitations. LLM Resayil solves both. Its pay‑per‑use credit system (USD only) lets you purchase exactly the amount you need, billed via Stripe or PayPal, eliminating the need to monitor token counts. At the same time, the platform’s Arabic language support is baked into every model, so you can build chatbots, translation tools, or content generators that work natively in Arabic and dozens of other languages.

Because the API is OpenAI‑compatible, you keep your existing code, testing pipelines, and CI/CD workflows. All you need to do is change the base URL and provide your Resayil API key. The migration is therefore quick, low‑risk, and cost‑saving—perfect for teams that want to expand globally without overhauling their stack.

Prerequisites for Migration (≈200 words)

1. LLM Resayil account – sign up at https://llm.resayil.io and generate an API key.
2. Billing setup – add either a Stripe or PayPal payment method; all charges are in USD.
3. Familiarity with the OpenAI SDK – you’ll continue using the same Python (openai) or JavaScript (openai) client libraries.
4. No new SDK installation – because the endpoints and payloads are identical, the existing OpenAI SDK works out‑of‑the‑box.
5. Optional – review the list of 39 models on the portal to pick the one that best fits your use case.

Step‑By‑Step Migration: Updating Your Code (≈350 words)

1. Change the Base URL

Both the Python and JavaScript OpenAI clients allow you to override the API base URL. Replace https://api.openai.com/v1 with https://llm.resayil.io/v1.

import openai

openai.api_key = "YOUR_RESAYIL_API_KEY"
openai.base_url = "https://llm.resayil.io/v1"

const { Configuration, OpenAIApi } = require("openai");

const configuration = new Configuration({
  apiKey: "YOUR_RESAYIL_API_KEY",
  basePath: "https://llm.resayil.io/v1",
});
const openai = new OpenAIApi(configuration);

2. Keep the Same Payload

The request body for /v1/chat/completions does not change. Below is a minimal chat request that uses the deepseek-v4-flash model (a chat‑oriented model from the catalog).

response = openai.ChatCompletion.create(
    model="deepseek-v4-flash",
    messages=[{"role": "user", "content": "Hello, how are you?"}],
    stream=False,
)
print(response.choices[0].message.content)

(async () => {
  const response = await openai.createChatCompletion({
    model: "deepseek-v4-flash",
    messages: [{ role: "user", content: "Hello, how are you?" }],
    stream: false,
  });
  console.log(response.data.choices[0].message.content);
})();

3. Verify Connectivity

Hit the health endpoint first:

curl https://llm.resayil.io/v1/health

A 200 OK response means you’re ready to send real requests.

4. Update Environment Variables

Store the new base URL and API key in your CI environment (e.g., RESAYIL_API_KEY and RESAYIL_BASE_URL). This keeps your codebase clean and makes future switches trivial.

Feature Parity: What You Can Keep Using (≈250 words)

| OpenAI Feature | LLM Resayil Equivalent | |---|---| | Streaming | Set stream=True (Python) or stream: true (JS) – works exactly the same. | | Function Calling | Use the same functions schema; responses include function_call objects. | | Tool Use | Supported via the same tool_calls field. | | Vision | Vision‑enabled models like qwen3-vl:235b-instruct accept image inputs using the same multipart format. | | Thinking Models | Models such as deepseek-v4-flash or kimi-k2-thinking provide chain‑of‑thought capabilities without extra flags. | | Arabic & Multi‑Language | Native support – no special prompt tricks needed. |

Because the JSON structures are identical, you do not need to refactor your existing logic for these advanced capabilities. Simply point at the new endpoint and continue using the same SDK calls.

Pricing Model: Pay‑Per‑Use Credits vs. OpenAI’s Token Pricing (≈150 words)

LLM Resayil bills you in USD credits. You purchase credits via Stripe or PayPal and consume them as you call any endpoint. This model removes the need to calculate token counts for each request, simplifying budgeting and cost‑tracking.

OpenAI, by contrast, charges per token. While flexible, it requires developers to monitor token usage to avoid surprise bills. With Resayil’s credit system, you know exactly how many credits you have left, and there are no hidden per‑token fees.

Both platforms offer a pay‑per‑use approach—no subscription or upfront commitment is required.

Testing Your Migration (≈120 words)

1. Health Check – GET https://llm.resayil.io/v1/health should return { "status": "ok" }.
2. Simple Chat Test – run the Python or JavaScript snippet above and confirm you receive a response.
3. Streaming Test – set stream=True and iterate over the response chunks.
4. Function Call Test – include a functions array and verify the returned function_call payload matches OpenAI’s format.
5. Vision Test – if using a vision model, send a multipart request with an image file and ensure the model returns a description.

If all tests pass, your migration is successful.

Conclusion: Next Steps and Resources (≈120 words)

Migrating from the OpenAI SDK to LLM Resayil is straightforward: update the base URL, keep your existing payloads, and enjoy native Arabic support plus a transparent credit‑based pricing model. Explore the 39 models in the catalog to find the best fit for your workload, and leverage ready‑made integrations with LangChain, n8n, LiteLLM, and the OpenAI SDK itself. For full reference, visit the API documentation, check the pricing page, and create your account at the registration portal. Happy building!

Frequently Asked Questions

Q: Is LLM Resayil fully compatible with the OpenAI Python SDK?

A: Yes. LLM Resayil is OpenAI compatible; you only need to change the base URL and provide your Resayil API key.

Q: Do I need to rewrite my existing function calling code?

A: No. Function calling is supported via the same schema as OpenAI. Just update the endpoint.

Q: What payment methods does LLM Resayil accept?

A: Stripe and PayPal, billed in USD on a pay‑per‑use credit basis.

Q: Does LLM Resayil support streaming like OpenAI?

A: Yes. Streaming is supported. Set stream=True in your request as you would with OpenAI.

Q: Can I use LLM Resayil with LangChain or n8n?

A: Yes. LLM Resayil integrates with LangChain, n8n, LiteLLM, and the OpenAI SDK directly.

Call to Action

Ready to cut costs and add native Arabic support? Register now, grab some credits, and start experimenting with the pricing page. For deeper technical details, head over to the API docs.