Quick answer
How do I call LLMwithCrypto from Node.js?
Install the official package with npm install openai, then create the client with baseURL: "https://llmwithcrypto.com/api/v1" and apiKey: process.env.LLMWITHCRYPTO_API_KEY. LLMwithCrypto answers client.chat.completions.create() in the OpenAI format for 12 open-weight models, with streaming and tool calls where the model supports them, as documented on 23 October 2026.
What you need
| Node.js | 18 or newer, ES modules (.mjs or "type": "module") |
|---|---|
| Package | openai (official) |
| Base URL | https://llmwithcrypto.com/api/v1 |
| Key | In the environment variable LLMWITHCRYPTO_API_KEY, never in the code or the browser |
How do I send one request?
Create the client once at start-up and reuse it everywhere. Keep the key on the server: a key shipped in browser code can be read by anyone who opens the page, so call the API from your backend and send only the answer to the browser.
import OpenAI from 'openai';
const client = new OpenAI({
baseURL: 'https://llmwithcrypto.com/api/v1',
apiKey: process.env.LLMWITHCRYPTO_API_KEY,
});
const resp = await client.chat.completions.create({
model: 'deepseek-v4-pro',
messages: [
{ role: 'system', content: 'Answer in two sentences.' },
{ role: 'user', content: 'What is a context window?' },
],
max_tokens: 200,
});
console.log(resp.choices[0].message.content);
console.log(resp.usage.prompt_tokens, 'in,', resp.usage.completion_tokens, 'out');
How do I run a batch without hitting the rate limit?
Run a fixed number of requests at a time. The small mapLimit helper below keeps four in flight and returns the results in order; no extra package is needed. Every account has a per-minute request and token limit, shown in the dashboard; ask support and it can be raised.
import OpenAI from 'openai';
const client = new OpenAI({
baseURL: 'https://llmwithcrypto.com/api/v1',
apiKey: process.env.LLMWITHCRYPTO_API_KEY,
});
async function translate(text) {
const resp = await client.chat.completions.create({
model: 'qwen3-235b-a22b-instruct-2507',
messages: [
{ role: 'system', content: 'Translate into Spanish. Reply with the translation only.' },
{ role: 'user', content: text },
],
max_tokens: 200,
});
return resp.choices[0].message.content;
}
// at most 4 requests in flight
async function mapLimit(items, limit, fn) {
const out = new Array(items.length);
let next = 0;
async function worker() {
while (next < items.length) {
const i = next++;
out[i] = await fn(items[i]);
}
}
await Promise.all(Array.from({ length: limit }, worker));
return out;
}
const lines = ['Your order has shipped.', 'Your payment was received.', 'Your key was revoked.'];
console.log(await mapLimit(lines, 4, translate));
How do I stream the answer?
Pass stream: true and use for await on the result. Each chunk carries a piece of text in choices[0].delta.content; with stream_options: { include_usage: true } the last chunk has the token counts.
import OpenAI from 'openai';
const client = new OpenAI({
baseURL: 'https://llmwithcrypto.com/api/v1',
apiKey: process.env.LLMWITHCRYPTO_API_KEY,
});
const stream = await client.chat.completions.create({
model: 'deepseek-v4.1-flash',
messages: [{ role: 'user', content: 'Write a haiku about latency.' }],
stream: true,
stream_options: { include_usage: true },
max_tokens: 120,
});
for await (const chunk of stream) {
const text = chunk.choices[0]?.delta?.content;
if (text) process.stdout.write(text);
if (chunk.usage) console.log(`\n${chunk.usage.prompt_tokens} in, ${chunk.usage.completion_tokens} out`);
}
How do I read the credit left?
The credits endpoint is not part of the OpenAI SDK, so call it with fetch. It is free; call it before a large batch to make sure the credit will cover it.
const res = await fetch('https://llmwithcrypto.com/api/v1/credits', {
headers: { Authorization: `Bearer ${process.env.LLMWITHCRYPTO_API_KEY}` },
});
const credits = await res.json();
console.log('credit left:', credits.balance_usd, 'USD');
How do I handle errors?
The SDK throws an OpenAI.APIError for every HTTP error, with the status in err.status and the body’s code in err.code. Test the code, not the message: insufficient_balance means top up, model_not_found means a wrong id, rate_limit_exceeded means wait and retry.
The SDK already retries some errors twice with a pause (maxRetries). For long batches, keep that default, cap concurrency as above, and log the failures you give up on. The errors page lists every status and which ones are worth a retry. Failed calls cost nothing: You pay per token from your balance: input and output tokens are counted by the model’s own tokenizer and charged at that model’s price per 1M tokens. A call that ends in an error costs nothing.
How do I move an existing OpenAI app over?
Change the client options, baseURL and apiKey, and replace every gpt-… model name with an id from the models page. Prompts, streaming code and the parsing of choices and usage stay as they are. Run your tests on the new model before you switch traffic: tool calling and JSON output follow what each model supports.
Node.js: common questions
Can I call the API from the browser?
Technically yes, but never with your key in the page. Call it from your server, or from a serverless function that holds the key.
Does the Vercel AI SDK work?
Any library that accepts an OpenAI-compatible base URL works. The API speaks the OpenAI chat completions format: point the OpenAI SDK, LangChain or any OpenAI-compatible tool at our base URL with your key, and change the model name.
What happens when the credit runs out?
Calls return 402 insufficient_balance and cost nothing. The errors page shows how to react.