Project

Building a PR Review Agent

Medium

53 completions

~ 7 hours

4.5

You will explore agent design patterns—state maintenance, tool calls, and handoffs— and gain hands-on Python practice interacting with GitHub repositories programmatically. This will equip you with the knowledge needed to design agent systems that collaborate to accomplish a shared goal.

Provided by

JetBrains Academy

About

In this project, you’ll build a multi-agent AI system that taps into GitHub’s API to pull code diffs, test outcomes, and dependency data. It then uses this information to catch obvious mistakes—lint violations, missing tests, and vulnerability flags—and produces a short, clear comment for each pull request. Finally, it posts the review back to GitHub, so reviewers can dedicate their effort to the deeper review tasks.

Graduate project

This project covers the core topics of the Introduction to AI Engineering with Python course, making it sufficiently challenging to be a proud addition to your portfolio.

At least one graduate project is required to complete the course.

What you'll learn

Once you choose a project, we'll provide you with a study plan that includes all the necessary topics from your course to get it built. Here’s what awaits you:

Build an agent to prepare the needed context.

Use the retrieved contexts to generate draft comments.

Analyze the draft review, refine it, generate a final review, and post the final comment.

Wrap it all up in a GitHub Actions workflow to create review comments automatically.

Reviews

Dan Burton

4 weeks ago

4.3

This was a great project teaching CI/CD principles, as well as creating a multi-agent workflow.

Sebastian Müller

3 months ago

5.0

Great experience to learn how to write agents and orchestrate them with LlamaIndex. Building up from a single FunctionAgent to a multi-agent workflow with handoffs and shared Context, then wiring it into GitHub Actions for real PR reviews, made the concepts click in a very practical way. Thanks!

John Doe

4 months ago

3.7

I learned basics of making agents. There were some difficulties but i liked them because it forced me to think a little.

4.5

Learners who completed this project within the Introduction to AI Engineering with Python course rated it as follows:

Usefulness

4.8

Fun

4.6

Clarity

4.1