🆓 Local & Open Source AI: a kind ollama & LlamaIndex intro

❔ About

Sometimes, you may need a convenient yet powerful way to run many LLMs locally with:

• Only CPU ( i5 like)
• Little RAM (eg <= 8Go)
• Being able to plug third party frameworks (Langchain, LlamaIndex) so you can build complex projects
• Ease of use (few lines of code, powerful results)

👉 This is all what this post is about.

🎯 What you'll learn

In this short demo, you'll see how to:

• Run on Kaggle (CPU)
• Use ollama to run open source models
• Play with a first LlamaIndex example

💡 Benefits & opportunities

Get rid of weekly GPU usage limits on free plan:

With this CPU approach, you are then able to schedule AI based workflow for free (as long as it does not exceed the 12h window limit).

• Scheduling notebook execution with cron and Kaggle API

🍿 Demo

Enough teasing, let's jump in the demo:

📜 Notebook

🔭 Further, stronger

To go further (48GB of RAM required, as well as GPU ), a full example around mixtral, see Running Mixtral 8x7 locally with LlamaIndex.