CodeAssist
CodeAssist is an AI assistant that learns from every edit, keystroke, and solution, adapting to your style and training itself to become the perfect coding partner for you.
What is CodeAssist?
CodeAssist opens locally in your browser and turns everyday coding into a learning experiment.
You solve short programming challenges based on LeetCode-style problems, while an on-device model observes your approach, refactors, and final solutions. Over time, the model begins to imitate your reasoning: how you structure loops, name variables, debug logic, and refine solutions.
Each coding session becomes a training “episode,” producing data the app uses to adapt its next set of suggestions.
Why It Exists
Most AI coding tools are pre-trained on large static datasets. They either autocomplete or autosuggest code based on the context available to them, but they don't learn from you.
CodeAssist is an interactive product that explores a new paradigm, being a code assistant that evolves from your own problem-solving style. It's built to demonstrate "assistance learning", a branch of RL where the user becomes the teacher.
Much like BlockAssist, which learns Minecraft gameplay by mimicking user actions and receiving feedback through user intervention, CodeAssist models are trained to reinforce programming concepts and principles through editing, deleting, or retaining the assistant's output.
By grounding this in a lightweight, browser-based environment, CodeAssist provides a simple, auditable example of decentralized training and coordination in action.
How It Works
CodeAssist gives you a hands-on way to contribute to and experiment with decentralized AI training while improving your LeetCode skills.
Start Locally: Launch CodeAssist in your browser. Each sessions spins up a contained coding environment.
Choose a Problem:
Code and Test: CodeAssist tracks your edits and cursor movements, suggesting code additions like new lines, comments, and functions. It may also edit your code.
Learn and Adapt: After recording your "episode," the model reviews data from your coding session to learn your preferences and patterns.
Iterate: In the following sessions, CodeAssist continues fine-tuning the local model to seed new suggestions, like completions, refactors, and hints, based on the patterns it learned. The model will improve to code more like you over time.
(Optional) Upload to Hugging Face: Once you’re happy with your personal CodeAssist model, you can share it on Hugging Face and track your contribution to a decentralized, verifiable ledger of model improvements on the Gensyn Testnet.
Why LeetCode?
All CodeAssist coding prompts are drawn from LeetCode-style problems.
We use them as a lightweight, well-understood medium for training because they strike a balance between simplicity and structure.
They are:
Self-contained: These single-file challenges that run directly in your browser with no dependencies or setup.
Familiar: Many developers already understand the format, which reduces friction when learning a new tool.
Measured and gradable: Each problem has clear test cases and difficulty levels, which provides a natural way to track model progress.
Accessible: CodeAssist leverages an existing public dataset of problems and test suites to ensure consistency across users.
Using LeetCode as the sandbox keeps CodeAssist lightweight, fair, and approachable, so the focus stays on how you solve problems, not on configuring an environment.
Get Started
Ready to spin up CodeAssist and start training a local machine learning model (ML) to code like you today? Choose one of the installation guides below, or head directly to this walkthrough guide.
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