Build a local AI co-pilot using IBM Granite Code, Ollama, and Continue

This article provides a comprehensive guide on building a local AI co-pilot using IBM's Granite Code, Ollama, and Continue, specifically tailored for enterprise environments. The tutorial addresses common challenges such as data privacy, licensing issues, and costs associated with using third-party AI tools. It emphasizes the importance of running AI models locally to comply with corporate data regulations and to avoid licensing complications. The setup involves installing Ollama to serve large language models (LLMs) on a developer's workstation, fetching the Granite Code models, and integrating them with Visual Studio Code through the Continue extension. The author outlines the installation steps, configuration settings, and provides a quick setup script for users. The article concludes by highlighting the benefits of this local AI co-pilot setup, which allows developers to leverage AI capabilities while maintaining control over their code and data security. A follow-up tutorial is promised for further exploration of the topic.

- The tutorial focuses on building a local AI co-pilot for enterprise use using open-source tools.

- Key challenges addressed include data privacy, licensing, and cost of third-party AI tools.

- The setup involves using IBM's Granite Code models and Ollama to run LLMs locally.

- Integration with Visual Studio Code is facilitated through the Continue extension.

- A quick setup script is provided for ease of installation and configuration.