Deterministic evaluation environment for AI code reviewers covering bugs, security (OWASP), and architecture via FastAPI + OpenEnv.
OpenEnv Hackathon SF
RunbookOps: Deterministic OpenEnv environment for SaaS incident triage, runbook-driven resolution, and agent evaluation.
AI-powered system for low-exposure route optimization using AQI, simulation, and intelligent decision-making
An agent must triage incoming support/compliance emails using respond, escalate, or archive while minimizing risk and maximizing completion quality.
OpenEnv benchmark for broken ELT/ETL pipeline repair, online recovery, and temporal orchestration.
CNN based PPO agent and LLM based GRPO agent to play SMB on openenv wrapper using Leirbag-gabrieL's gym-super-mario-bros fork
OpenEnv-compliant RL environment simulating a customer support agent workflow with 3 graded tasks
Adaptive RL Reliability is an OpenEnv-compatible reinforcement learning environment for live-system autoscaling. It trains agents to make production capacity control decisions (scale down/hold/up) while protecting SLOs for latency, error rates, and CPU usage.
🐛 Real-world GitHub issue triage environment for AI agent training — built on the OpenEnv spec with 3 difficulty-graded tasks, shaped rewards, and FastAPI server deployable to HuggingFace Spaces.
A realistic OpenEnv environment for training AI agents to perform enterprise email triage across multi-email inbox workflows, with structured actions, tool usage, and reward shaping, built for the Scaler x Meta PyTorch Hackathon.
Agentic Reinforcement Learning Loop to make Scientific Discoveries on Mars
OpenEnv-based RL environment for smart waste sorting with reward shaping and adaptive difficulty.
A production-grade OpenEnv benchmark for AI code reviewers. Features multi-file reasoning, shaped rewards, and security-focused tasks (SQL Injection, O(n²) complexity).
Recursive Language Model Demo
Production-grade OpenEnv environment for training AI agents on real-world customer support tasks — triage, response drafting, and multi-step resolution.
AI environment for training agents to clean messy tabular data — FastAPI + Gradio, 3 difficulty tiers, multi-dimensional grading (Scaler x Meta Hackathon)
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