We give you the option to use the Prem AI API, the PremAI SDK, or the OpenAI SDK.For API usage documentation, refer to the API Reference.

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Create an API Key 🔑

Click the API Key button on the sidebar. Then click the + Create API Key button. Afterwards, copy the API key and save it in a secure location. Create an API Key

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Use with PremAI SDK

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Install the PremAI SDK

npm install premai

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List Models

import PremAI from 'premai';

const client = new PremAI({
  apiKey: process.env['PREMAI_API_KEY'], // This is the default and can be omitted
});

const response = await client.models.list();

console.log(response.data);

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Check Model Status

This is useful to check if a model is running or not. If it is not running, you can load it up using the load method.
The model name can be replaced with the name of your fine-tuned models as well.
import PremAI from 'premai';

const client = new PremAI({
  apiKey: process.env['PREMAI_API_KEY'] // This is the default and can be omitted
});

const response = await client.models.check_status(model="llama3.2-3b");

console.log(response);

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Load Model

This is useful to load up a model for inference.
The model name can be replaced with the name of your fine-tuned models as well.
import PremAI from 'premai';

const client = new PremAI({
  apiKey: process.env['PREMAI_API_KEY'] // This is the default and can be omitted
});

const response = await client.models.load(model="llama3.2-3b"); // Or any other model you want to load up

const modelStatus = await client.models.check_status(model="llama3.2-3b");

console.log(modelStatus);

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Unload Model

This is useful to unload a model from the server.
The model name can be replaced with the name of your fine-tuned models as well.
import PremAI from 'premai';

const client = new PremAI({
  apiKey: process.env['PREMAI_API_KEY'] // This is the default and can be omitted
});

const response = await client.models.unload(model="llama3.2-3b"); // Or any other model you want to load up

console.log(response);

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Chat Completions

import PremAI from 'premai';

const client = new PremAI({
  apiKey: process.env['PREMAI_API_KEY'], // This is the default and can be omitted
});

const response = await client.chat.completions({
    messages: [{
        role: 'user',
        content: 'Write a one-sentence bedtime story about a unicorn.'
    }],
    model: 'llama3.2-3b'
});

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

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Chat Completion with Streaming

Streaming is not supported for the PremAI SDK. Will be supported in the future.

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Use with OpenAI SDK

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Install the OpenAI SDK

npm install openai

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List Models

import OpenAI from 'openai';

const client = new OpenAI({
  baseURL: "https://studio.premai.io/api/v1/",
  apiKey: process.env['PREMAI_API_KEY'], // This is the default and can be omitted
});

const response = await client.models.list();

console.log(response.data);

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Chat Completions

The model name can be replaced with the name of your fine-tuned models as well.
import OpenAI from "openai";

const client = new OpenAI({
    baseURL: "https://studio.premai.io/api/v1/",
    apiKey: process.env.PREMAI_API_KEY,
});

//Create a chat completion
const response = await client.chat.completions.create({
    model: "llama3.2-3b", //Or any other model you want to use
    messages: [{ role: "user", content: "Write a one-sentence bedtime story about a unicorn." }]
});

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

​
Chat Completion with Streaming

import OpenAI from "openai";

const client = new OpenAI({
    baseURL: "https://studio.premai.io/api/v1/",
    apiKey: process.env.PREMAI_API_KEY,
});

//Create a chat completion
const response = await client.chat.completions.create({
    model: "llama3.2-3b", //Or any other model you want to use
    messages: [{ role: "user", content: "Write a one-sentence bedtime story about a unicorn." }],
    stream: true,
});

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