8/27/2024

Creating a REST API with Ollama

Welcome to your ultimate guide on Creating a REST API with Ollama! If you're looking to delve into the enchanting world of APIs and leverage the power of LLMs (Large Language Models) like Llama, you've landed in the right place. Here, we'll walk through how to harness Ollama for creating a custom REST API that suits your needs and more!

What is Ollama?

So, what exactly is Ollama? It's an Open Source tool that makes it incredibly SIMPLE to run various LLM locally. Ollama allows you to interact with different models easily, making it possible to build applications with them without breaking a sweat. You can read more about Ollama on their GitHub page and their official site.

Setting Up Ollama

Before we dive into creating an API, let’s get Ollama up and running smoothly on your machine.
  1. Installation: If you don't have Ollama yet, installation is a breeze. You can install Ollama on various platforms.
    • For Linux: Just run the following command in your terminal:
      1 2 bash curl -fsSL https://ollama.com/install.sh | sh
    • On macOS: Download the installation package here.
    • For Windows: Grab your copy here.
  2. Running the Server: With Ollama installed, you can start the server using:
    1 2 bash ollama serve
    This will allow you to access the API locally on your machine, typically at
    1 http://localhost:11434
    .
  3. Verify Server Run: After starting the server, open your browser and head to
    1 http://localhost:11434
    to ensure everything's running. You should see the Ollama interface.

Understanding Ollama’s API Endpoints

Once your Ollama server is running, it's time to explore the API endpoints it provides. According to the established documentation, Ollama exposes various endpoints to achieve a wide range of functionalities:
  • Generate Completion: You can generate text based on a prompt through the
    1 /api/generate
    endpoint.
  • Generate Chat Completion: For conversational interfaces, you can use the
    1 /api/chat
    endpoint.
  • Model Management: Create, copy, delete, and manage your models seamlessly.

Example API Call

Let's kick things off with a simple API call to generate completions. Open your terminal and execute:
1 2 bash curl http://localhost:11434/api/generate -d '{ "model": "llama3.1", "prompt":"Why is the sky blue?" }'
When you run this, you'll receive a JSON response with the generated text. This use of curl illustrates one of the many straightforward interactions you can have with the Ollama API.

Creating a Basic REST API with Ollama

Now that we have the grasp of the basic setup, let’s create a REST API using Ollama. We’ll build a simple Express application that connects to the Ollama API, providing all the functionality you need. Here’s a step-by-step breakdown.

1. Set up Your Node.js Environment

First, let's set up a Node.js Express application. If you haven't already, make sure you have Node.js & NPM (Node Package Manager) installed. Then, run the following commands in your terminal:
1 2 3 4 5 bash mkdir my-ollama-api cd my-ollama-api npm init -y npm install express body-parser axios

2. Creating Your Basic Server

Create a file named app.js in your project folder. This will be our main server file. Populate it with the following code: ```javascript const express = require('express'); const bodyParser = require('body-parser'); const axios = require('axios');
const app = express(); const PORT = 3000;
app.use(bodyParser.json());
app.post('/api/chat', async (req, res) => { const { messages } = req.body; try { const response = await axios.post('http://localhost:11434/api/chat', { model: "llama3", messages }); res.json(response.data); } catch (error) { res.status(500).send('Error contacting Ollama API.'); } });
app.listen(PORT, () => { console.log(
1 Server is running on http://localhost:${PORT}
); }); ``` This code sets up an Express server that listens on port 3000. It also has a POST route that will interact with the Ollama API.

3. Starting Your Server

In the terminal, run:
1 2 bash node app.js
Now your server is up and running! You can test it by sending a POST request to
1 http://localhost:3000/api/chat
using Postman or any API testing tool of your choice.

4. Sending Requests to the Ollama API

In our
1 /api/chat
endpoint, we use Axios to send a POST request to the Ollama chat endpoint. Here’s how you would call it:
1 2 3 4 5 6 7 8 9 json { "messages": [ { "role": "user", "content": "Why is the sky blue?" } ] }
This lets the Ollama API understand context and respond as a chat assistant would.

Customizing Your API

You might want to customize your API for various needs. Here are some ideas:
  • Add additional endpoints for other LLama models.
  • Include error handling mechanisms!
  • Cache responses to improve speed.

Using Arsturn to Enhance Your API Experience

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Wrapping Up

Creating a REST API with Ollama is not just a whimsy idea—it’s an extraordinary step into harnessing the tremendous capability of LLMs locally. You can have various applications, from chatbots to automated responses on YOUR websites, elevating how users interact with your content!
So get started today and enjoy the journey of building your own API with Ollama, while also exploring the endless possibilities that Arsturn brings to your digital experience!

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