Llama Tutor

The platform was created as a demonstration of what developers can build with the Llama ecosystem and Together AI's inference infrastructure, and the entire project is released under the MIT licensemaking both the application and its underlying codebase freely available for use and modification.

The tutoring experience begins with two simple inputs: the topic the user wants to learn and the education level at which they want the content explained.

This level-aware personalization allows Llama Tutor to serve the same subject at dramatically different depthsexplaining machine learning to a curious middle schooler using intuitive analogies while covering the same topic with technical precision for a graduate-level computer science student.

The resulting session adapts its vocabulary, complexity, and examples to match the specified educational context.

Real-time web search integration via the Exa search API distinguishes Llama Tutor from AI assistants that rely solely on training data.

When a tutoring session begins, the system pulls current and relevant sources from across the web, using that live information to ground the tutoring session in up-to-date content rather than knowledge that may be months or years out of date.

This is particularly valuable for fast-moving fields like technology, science, and current events where information currency matters.