introduction.mdx

title	description
Quickstart Guide	Let's create a Generative AI application in minutes.

## Why Prem?

Prem is a platform that's packaged with the necessary tools to effortlessly integrate Generative AI into your applications.

With Prem you can:

• Simultaneously test and monitor LLMs in the Prem Lab: Compare the performance of multiple models and find the best fit for your use case.
• Train models in the Prem Gym: Leverage Prem’s ability to autonomously fine-tune models. The Gym is your place to beef up your deployment models by continuously fine-tuning your data in order to improve performance.
• Seamlessly create RAG-based assistants: Prem is capable of interacting with your documents. Just upload the documents, and we’ll take care of the rest.
• Launch and use the Prem JavaScript and Python SDKs: Integrate your custom AI into your applications with minimal effort.

Quickstart{" "}

✌️ This guide shows you how to create a Generative AI application with Prem in minutes.

Click here to sign up

We set up a starter project for you already. You can either use the starter project provided or create a new project from scratch. It's up to you.  Make sure to take note of your Project ID. You'll need it to use the SDK. You can find your **Project ID** on the Project page under each project's title or on the Set Up page.

## Choose an SDK and install Prem also exposes a simple [REST API](/api-reference/introduction) for interacting with the platform. ```bash Python pip install premai ```

npm install @premai/prem-sdk

Run your first project.

from premai import Prem

client = Prem(api_key=YOUR_API_KEY)

project_id = PROJECT_ID

system_prompt = "You're a helpful assistant"

messages = [
    {"role": "user", "content": "Who won the world series in 2020?"},
]

response = client.chat.completions.create(
    project_id=project_id,
    system_prompt=system_prompt,
    messages=messages,
)

print(response.choices)

import Prem from "@premai/prem-sdk";

const client = new Prem({
  apiKey: API_KEY,
});

const project_id = PROJECT_ID;

const system_prompt = "You're a helpful assistant";
const messages = [
  { role: "user", content: "Who won the World Series in 2020?" },
];

async function chatCompletion() {
  const responseSync = await client.chat.completions.create({
    project_id,
    system_prompt,
    messages,
  });

  console.log(responseSync);
}

Next steps

• Continue to test LLMs in the Lab.
• Check out the API reference.
• Connect your documents to the LLM to enhance its knowledge.
• Fine-tune your LLMs in the Gym.

Read the guides

Start your journey with Prem by creating an account.

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Create and manage projects to organize your work.

<Card title="Lab" icon="flask" href="/get-started/lab"

Experiment with different models in the Lab.

Monitor your AI integration. Upload documents to your repositories. Launch your preferred model. Train your own Model. Integrate Prem into your products.