8/27/2024

Setting Up Ollama with CircleCI

Setting up your projects for Continuous Integration (CI) can sometimes feel like wading through molasses. You know what you want to do, but the configurations can seem like a tangled web of text files and endless options. Fear not, dear reader! With this handy guide, we will simplify the process of integrating Ollama with CircleCI, plus sprinkle in some cool tips along the way.

What’s CircleCI?

Before jumping into the how-tos, let's set the stage by chatting about what CircleCI actually is. CircleCI is a CONTINUOUS INTEGRATION platform that helps automate your development process. Whether you're running tests or building your code, CircleCI can help streamline the entire process, making it easier to deploy your projects to production.

Why CircleCI?

CircleCI supports many programming languages, including Node, Python, and Go, which makes it a versatile tool for all kinds of developers.
Helps in getting feedback on your builds faster, allowing you to catch issues before they escalate.
Integrates seamlessly with GitHub and Bitbucket, thus making collaboration and version control a breeze.

What’s Ollama?

Moving onto Ollama: This nifty tool enables you to run large language models like Llama 2 LOCALLY, providing a fast, responsive AI experience. By using Ollama, you can interact with your own models without relying on cloud services, which can be slower and more costly.

Why Use Ollama?

Cost-Effective: Running models locally saves you money that would be spent on cloud-computing resources.
Secure Deployment: Your data remains on-premises, which is essential for companies dealing with sensitive information.
Fast Responses: Running models locally yields faster interactions, leading to a BETTER user experience.

Setting Up CircleCI Configuration for Ollama

To run Ollama smoothly within CircleCI, you’ll need to configure your

.circleci/config.yml

file. This file is the brain behind how CircleCI runs your tests and builds code, so let’s make it sing! Let's kick things off by creating a sample configuration.

Sample config.yml Structure

Here’s a simple YML configuration to get you started: ```yaml version: 2.1

jobs: build: docker:

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- image: cimg/python:3.8  # Choosing Python as base image
steps:
  - checkout  # Retrieve your source code
  - run:
      name: Install Ollama
      command: |
        curl -sS https://ollama.ai/install.sh | sh  # Installing Ollama locally
  - run:
      name: Run a Sample Ollama Model
      command: |
        ollama run llama-2 --language en  # Running a demo model

workflows: version: 2 build_and_test: jobs:

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- build

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This configuration does a few things for you:
* It retrieves your source code with the `checkout` command.
* It installs **Ollama** via a shell command.
* Finally, it executes a demo Llama 2 model locally.

### Step-by-Step Breakdown
1. **Define the Version**: `version: 2.1` tells CircleCI what version of their configuration syntax you’re using.
2. **Jobs Section**: Here, we define our primary task, which includes using a Docker image for a Python environment. Based on your specific requirements, you might want to replace this image with others capable of running your desired models.
3. **Steps Detail**: This part gets into the nitty-gritty—you check out your source code, install Ollama, and execute a model!

### Adding Services for Database Interactions
Suppose you need to add a database, such as MongoDB, to test interactions or manage state while running your models. You could easily modify the `config.yml` to include a secondary service.

yaml jobs: test: docker:

image: cimg/node:current
image: mongo:4.4 # Added MongoDB service steps:
checkout
run: name: Test Ollama Interaction with MongoDB command: | npm install npm test # Running tests to check interactions ```

odification allows your jobs to run against both Node and MongoDB. Just make sure to manage the databases correctly based on your interaction logic!

Using Tools to Edit Configuration Files

Making sense of YAML files can be daunting. Thankfully, CircleCI provides a VS Code extension that reduces context switches by offering real-time syntax validation and autocomplete suggestions for configuration files. Using this tool can SAVE you loads of time while writing and modifying your configurations!

Testing Locally

Running the models locally before deploying is a wise strategy. It helps you catch issues and understand how your CI/CD processes are functioning:

First, you can test locally within your IDE or command line.
If everything checks out, push your changes to your version control.
Watch the build process kick off in CircleCI and verify that it automatically runs your tests successfully.

Troubleshooting Common Issues

Even with the best-laid plans, hiccups will occur. Here are a few common issues you might run into:

Operation Not Permitted: If you encounter issues like
1runtime/cgo: pthread_create failed: Operation not permitted
, it often relates to misconfigured security settings in Docker. Consider upgrading to a more recent Docker version or tweaking your security options, such as using
1--security-opt seccomp=unconfined
.
Manifest Errors: Sometimes you can’t pull Docker images due to manifest errors. Ensure you're referencing the correct image name and tag in your configuration.

Why Choose Arsturn for Your AI Needs?

While navigating through CircleCI setups and Ollama configurations, don’t forget that you can effortlessly create CUSTOM ChatGPT chatbots with Arsturn! Here's why you should check it out:

Instant Customization: Create your chatbot instantly without any coding experience. It’s fully adaptable to your requirements!
One-Stop Solution: Use your data effectively to engage your audience, providing them with detailed responses and saving time on customer queries.
Analytics & Insights: With Arsturn, you can gain valuable insights about what your audience cares about and refine your brand accordingly.
Stats Don't Lie: Thousands are already using Arsturn to build meaningful connections with their audiences—why not join them?

Wrapping Up

To sum up, setting up Ollama with CircleCI isn’t rocket science, but it does require carefully crafted configurations and sometimes a bit of troubleshooting. Utilize the power of CI/CD to ensure top-notch quality in your applications while enhancing your workflow.

And of course, don’t miss out on the power of conversational AI—check out Arsturn today!

Happy coding, Ollama fans!