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Our library for RL environments + evals
4,158 starsPython
I built an integration for RL training of browser agents for everyone
by filtr12·Mar 25, 2026·7 points·1 comment
AI Analysis
●●SolidNiche GemBig Brain
Browserbase integration enables scalable RL evals when most tools only support static environments.
Strengths
- •Part of verifiers repo with 3.9k stars showing real community adoption and maintenance.
- •Headless browser infrastructure on Browserbase enables realistic web interaction training.
- •LoRA support allows fine-tuning browser agents without full model retraining overhead.
Weaknesses
- •Extremely narrow audience - only matters if you're doing RL for browser agents specifically.
- •Tied to Prime Intellect's ecosystem which limits adoption outside their infrastructure.
Category
Target Audience
ML researchers training browser automation agents with reinforcement learning
Similar To
OpenEnv · Gymnasium · BrowserGym
Post Description
This integration allows for scalable evals and training of browser agents with hosted Prime Intellect eval + training pipelines and headless browser infrastructure on Browserbase to RL train browser agents with LoRA.
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