gradex 0.1.1

Measurable code improvement — autonomous optimization loop

Gradex — autonomous code optimization. Measurable improvement, every run.

Gradex discovers performance targets, captures a baseline, runs autonomous optimization experiments, and ships the best verified patch.

Install

pip install gradex

60-Second Quickstart

pip install gradex
gradex install cursor          # one-time provider + model setup
gradex discover "make this repo faster"
gradex optimize
gradex dashboard

After install, GradeX walks you through provider, model, and API key setup (or skip and use CLI flags). Re-run anytime with gradex configure. Use gradex install cursor --no-setup in CI.

Providers

Provider	Best for	Notes
Groq	Free cloud runs	Default. Best for serious optimize runs
OpenRouter	Low-friction testing	Free-tier models; one API key, many models
Anthropic	High quality reasoning	Strong patch planning and code edits
OpenAI	General purpose	Broad model options
Ollama	Local/private	Runs fully on your machine

CLI Reference

Command	Description
gradex install <host>	Installs Gradex integration for a coding host (optional one-time model setup)
gradex configure	Set up or update LLM provider, model, and API key
gradex models	List recommended models for a provider
gradex doctor <host>	Checks host environment and setup health
gradex dashboard	Starts live optimization dashboard
gradex upgrade	Checks PyPI for newer Gradex versions
gradex discover [hint]	Discovers benchmark target and baseline
gradex optimize	Runs autonomous optimization loop
gradex stats	Shows run analytics and optional exports
gradex report	Exports a shareable HTML run report
gradex history	Lists recent optimization runs

How It Works

+-----------+     +-----------+     +----------------------+     +----------------+
| discover  | --> | baseline  | --> | optimize loop (N)    | --> | best patch out |
+-----------+     +-----------+     +----------------------+     +----------------+

1. discover analyzes your repo and creates a measurable benchmark target.
2. Gradex records a baseline score.
3. optimize runs parallel experiment rounds (patch -> benchmark -> gate checks).
4. Best validated patch and run analytics are surfaced in dashboard and CLI.

Dashboard

Dashboard screenshot:

License

MIT