8/27/2024

Setting Up Ollama with Ansible for Automation

Are you curious about deploying artificial intelligence models locally using Ollama and automating the process with Ansible? If the answer is yes, you’re in the right place. This guide is designed to help you streamline the orchestration of Ollama, a powerful local LLM (Large Language Model) framework with Ansible, a robust tool for automating IT infrastructure. Let’s dive right in!

What is Ollama?

Ollama is a user-friendly framework that lets you run large language models directly on your local machine. Unlike cloud-based solutions that can complicate setups and run into additional costs, Ollama empowers you to harness sophisticated machine learning models with ease. For example, you can deploy various models like Llama 3.1, Mistral, and Gemma 2—without requiring deep technical knowledge or dealing with complex cloud environments. To begin your journey with Ollama, check out the Ollama GitHub repository.

Why Use Ansible?

Ansible is an open-source automation platform that simplifies the management of IT tasks such as configuration management, application deployment, and orchestration. The benefits of using Ansible include:

Agentless Operation: Ansible doesn’t require agents to be installed on target machines. Instead, it utilizes SSH for seamless interactions with your infrastructure.
Human-Readable Automation Scripts: It uses YAML, which is easy to read and write, even for those who are not professional developers.
Modular Structure: Ansible’s modules allow you to customize automation tasks according to your specific needs. If you want to learn more about Ansible, feel free to explore this tutorial.

Preparing Your Environment

To set up Ollama with Ansible, you'll need a few prerequisites:

Docker: Ensure that Docker is installed on your machine to manage containerized applications effectively. You can download it from the official Docker website.
Ansible: You can install it via pip. Run the command:
1 2bash pip install ansible
Ollama: Download Ollama and install it based on your OS. For macOS, you can download the package from Ollama's official site. Windows users can find the setup at Ollama's Windows preview.
Python: Make sure Python is installed since Ansible relies on it for functionality.

Step 1: Setting Up Ansible Playbook

An Ansible Playbook is simply a list of tasks you want to automate, written in YAML format. The first task will be to pull the Ollama model and set it up. Here’s an example playbook you can use:

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---
- name: Setup Ollama
  hosts: localhost
  tasks:
    - name: Ensure Ollama is installed
      command: curl -fsSL https://ollama.com/install.sh | sh
      args:
        creates: /usr/local/bin/ollama

    - name: Pull the Llama 3.1 model
      command: ollama pull llama3.1

    - name: Serve the Ollama model
      command: ollama serve

Step 2: Running Your Playbook

Once your playbook is set up, execute it with Ansible to automatically pull and serve the desired Ollama model:

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ansible-playbook setup_ollama.yml

This will automate the installation and setup process, allowing you to sit back while everything is handled for you!

Step 3: Customizing the Configuration

You may want to configure additional options, such as environment variables or networking settings specific to your needs. You can configure your Ollama instance by modifying its config file. Ansible allows you to manage these configurations through roles, providing a structured way to maintain your scripts and settings.

You can leverage Ansible's built-in variable system to customize deployment paths, model versions, and other configurations.

Integrating Ollama with Ansible for Deployment

Integrating Ollama with Ansible not only helps automate the setup process but also facilitates continuous integration and deployment (CI/CD). With a solid CI/CD strategy in place, you can get new models, updates, or configurations deployed seamlessly. What does a sample CI/CD pipeline look like?

Source Control: Store your Ansible playbooks in a GitHub repository to track changes.
CI/CD Tool: Use a service like Jenkins or GitHub Actions to monitor your repository and trigger deployments automatically upon new commits.
Docker: Each deployment pulls the latest version of your models and containers as specified in your playbooks.
Monitoring: Utilize tools like Prometheus for tracking the performance of your setups.

Bonus: Dockerizing the Ansible Playbook

One effective way to ensure consistent deployment across environments is to Dockerize your Ansible playbook. Here’s how you can do that:

Create a
1Dockerfile
: Here’s an example Dockerfile that sets up Ansible within a container:
1 2 3 4 5 6 7Dockerfile FROM ubuntu:20.04 RUN apt-get update && \ apt-get install -y ansible curl WORKDIR /app COPY . . CMD ["ansible-playbook", "setup_ollama.yml"]
Build your Docker image:
1 2bash docker build -t ollama-ansible .
Run the container:
1 2bash docker run --rm ollama-ansible

Conclusion

By integrating Ollama with Ansible, you take your automation game to a whole new level. Whether you’re deploying a single model or a full orchestration of models, this combination offers a HOLISTIC solution that’s efficient and effective. You are using leading technologies that help you not only deploy AI models but improve your DevOps practices as well.

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If you have any questions or experiences to share while setting up an Ollama instance with Ansible, don’t hesitate to leave a comment!