8/27/2024

Setting Up Ollama with GitHub Actions

Introduction

Are you ready to unleash the POWER of AI right in your own development workflow? 🛠️ Introducing Ollama, a tool that allows you to run large language models like Llama 3.1, Mistral, and many others locally. With the integration of GitHub Actions, you can automate your AI tasks beautifully and efficiently!

In this post, we’ll dive into setting up Ollama with GitHub Actions, guiding you step-by-step on how to orchestrate this powerful combination for your own needs. Let’s go!

What is Ollama?

Ollama is an innovative platform that simplifies the process of using large language models. Ready to get up & running? You can learn more about Ollama’s capabilities here! With Ollama, you can easily pull models, run them locally, and even train chatbots using your own datasets.

Why Use GitHub Actions?

GitHub Actions offers a flexible CI/CD solution that enables you to automate your workflows right from your GitHub repository. Want to streamline testing, deployments, or even create a schedule for running scripts? You can use GitHub Actions to automate these processes effortlessly!

Key Benefits of Using GitHub Actions with Ollama:

Automate Routine Tasks: Let your code run automatically, like when new code is pushed.
Real-Time Feedback: Get immediate results on whether tasks succeed or fail.
Seamless Integration: Integrate with other GitHub features effortlessly.
Custom Workflows: Design workflows specifically tailored to your project needs.

Setting Up Ollama in Your Development Environment

Before diving into GitHub Actions, let’s make sure Ollama is properly set up locally. Here’s what you need to do:

Step 1: Install Ollama

You can install Ollama on different operating systems easily. For example:

Linux: Run the command below in your terminal:

1
curl -fsSL https://ollama.com/install.sh | sh

macOS: Download the installer and run it from here.
Windows: Download the setup file from here.

Step 2: Pull Your Desired Model

Ollama provides a rich library of models. Use the following command to pull the model you want:

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ollama pull llama3.1

To check the available models, you can visit the Ollama model library.

Step 3: Run Ollama

To run Ollama locally, just use:

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ollama serve

This serves the model which you can access via a local API.

Integrating GitHub Actions

Now, let’s integrate GitHub Actions to automate tasks related to Ollama in your repository. First, we’ll setup a basic workflow.

Step 1: Create GitHub Actions Workflow

In your project repository, create a folder named

.github/workflows/

. Inside this folder, create a new YAML file named

ollama_workflow.yml

Step 2: Define the Workflow

Insert the following code into your

ollama_workflow.yml

file:

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name: Ollama Workflow

on:
  push:
    branches:
      - main
  pull_request:
    branches:
      - main

jobs:
  ollama:
    runs-on: ubuntu-latest
    steps:
      - name: Checkout Code
        uses: actions/checkout@v2

      - name: Install Ollama
        run: curl -fsSL https://ollama.com/install.sh | sh

      - name: Run Ollama
        run: |
          ollama serve &  
          sleep 5    # wait for the Ollama server to be ready

      - name: Call Ollama API
        run: |
          curl -d '{ "model": "llama3.1", "prompt": "Why is the sky blue?" }' \
          -H 'Content-Type: application/json' \
          http://localhost:11434/api/generate

Step 3: Commit Your Changes

After creating the workflow file, commit & push your changes to the

main

branch of your repository. GitHub Actions will automatically initiate this workflow upon your next push!

Step 4: Monitor Workflow Results

You can check the status of your GitHub Actions by navigating to the

Actions

tab in your repository on GitHub. Here you will find the results of your workflows including logs to check for assurances that Ollama is working as expected.

Best Practices for Using Ollama with GitHub Actions

Use Environment Variables: Utilize secrets for API keys or sensitive data instead of hardcoding them.
Limit Model Size: Consider the available resources, as larger models might have longer loading times.
Monitor Logs: Regularly check logs after the Action is executed to catch errors early on.

Troubleshooting Common Issues

If you run into troubles while setting up Ollama in GitHub Actions, here are some helpful tips:

Connection Issues: Ensure that the Ollama server is running. You might encounter connection issues if
1ollama serve
hasn’t fully started yet. Adding a
1sleep
command after the
1serve
command can help.
Action Failures: If your workflow fails, check the logs for the specific step that failed to diagnose the issue.

Conclusion & Promotion for Arsturn

Integrating Ollama with GitHub Actions can streamline your development process, making AI tasks seamless & efficient. Whether you're deploying models, automating tests, or enhancing your workflows, this integration opens up a realm of possibilities!

And speaking of integrations, if you’re looking to take your engagement to the next level without any hassle, check out Arsturn! 🎉 With Arsturn, you can create custom interactive chatbots in no time. Boost conversions & engage your audience before they even step foot on your website!

Head on over to Arsturn now & start engaging your audience with Conversational AI, or sign up for FREE! 🌟 No credit card needed! Watch as your interactions become more meaningful & your brand grows.

Summary

To wrap it up, we covered:

Setting up Ollama locally.
Integrating Ollama with GitHub Actions for automated workflows.
Best practices for smooth operation.
Troubleshooting common issues you might encounter.

So roll up your sleeves & start automating your AI tasks today! You’ll thank yourself later!