browser-use/rl-env-use

选用指南

AI 根据 README 整理 · 2026/10/21 22:07:01

使用方式

通过命令行使用，例如 `rl-env-use create` 和 `rl-env-use climb`，也可在代码中通过 `Env` 类使用。

查看 README 依据

- **Exports** the dataset for an RL trainer, or serves it in code with `Env` ## Setup prompt For Claude Code / Codex / OpenCode: ```text Set up https://github.com/browser-use/rl-env-use for me. Read install.md first to install this repo, register the skill, and set up the Browser Use and OpenRouter API keys - ask me to paste them when you need them. Then read SKILL.md for daily usage. After install, don't build anything on your own - just tell me it's ready and wait for me to name a skill. ``` Then ask:

> build me an RL environment for predicting whether a clinical trial met its primary endpoint, from its ClinicalTrials.gov registration For humans: ```bash rl-env-use create "predict whether a completed trial met its primary endpoint from its registered protocol; ClinicalTrials.gov" --budget 40 rl-env-use climb envs/<name> --model qwen-35b ``` ## Results The shipped example, [`envs/trial-forecast`](envs/trial-forecast): 35 forecasts from 29 ClinicalTrials.gov trials whose results were posted since July 2026, after the models' training data. Built for $72, $17 of it Browser Use.

部署要求

需要 Python 3.11+，可选 Node.js 18+ 用于 HTML 报告，并需要 Browser Use 和 OpenRouter API 密钥。

查看 README 依据

Get a Browser Use API key at [Browser Use Cloud](https://cloud.browser-use.com/?utm_campaign=rl-env-use&utm_source=github). ## What it does - **Mines real cases**: Browser Use agents find the materials (a trial protocol, a 10-Q) and the outcome published later - **Writes hard tasks**: gold answers computed by code, anything a frontier panel solves gets rewritten harder - **Rejects bad tasks**: leaked answers, memorized outcomes, ambiguous prompts - **Hillclimbs** a model's system prompt with a train/test split, a noise floor and paired confidence intervals

Python 3.11+, optionally Node.js 18+ for the HTML reports. ```bash git clone https://github.com/browser-use/rl-env-use ~/Developer/rl-env-use cd ~/Developer/rl-env-use uv venv && uv pip install -e '.[test]' cp .env.example .env && $EDITOR .env # BROWSER_USE_API_KEY, OPENROUTER_API_KEY .venv/bin/python -m pytest -q # offline, ~10 s ``` See [`SKILL.md`](./SKILL.md) for the full workflow and where every file is saved. ## License MIT, see [LICENSE](LICENSE).