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Time for Boot.dev to cash in on the AI hype.
If you've ever used Cursor or Claude Code as an "agentic" AI editor, you'll understand what we're building in this project.
We're building a toy version of Claude Code using Google's free Gemini API! As long as you have an LLM at your disposal, its actually surprisingly simple to build a (somewhat) effective custom agent.
The program we're building is a CLI tool that:
For example, I have a buggy calculator app, so I used my agent to fix the code:
> uv run main.py "fix my calculator app, its not starting correctly"
# Calling function: get_files_info
# Calling function: get_file_content
# Calling function: write_file
# Calling function: run_python_file
# Calling function: write_file
# Calling function: run_python_file
# Final response:
# Great! The calculator app now seems to be working correctly. The output shows the expression and the result in a formatted way.
The learning goals of this project are:
The goal is not to build an LLM from scratch, but to instead use a pre-trained LLM to build an agent from scratch.
To get started, make sure you have Python and the Boot.dev CLI installed and working.
Run and submit the CLI tests.
The Boot.dev CLI requires you to be signed in to submit your solution!
Copy/paste one of the following commands into your terminal:
Run
bootdev run 44e182d7-c2c6-4c7e-9313-1b078e301344
Submit
bootdev run 44e182d7-c2c6-4c7e-9313-1b078e301344 -s
Run the CLI commands to test your solution.
Using the Bootdev CLI
The Bootdev CLI is the only way to submit your solution for this type of lesson. We need to be able to run commands in your environment to verify your solution.
You can install it here. It's a Go program hosted on GitHub, so you'll need Go installed as well. Instructions are on the GitHub page.