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scaleapi/agentenv-framework

Creating realistic RL environments requires collaboration between researchers, engineers, and domain experts across many dimensions: artifacts, environments tools, dynamism of the environment, reproducibility, and more. There is no open source framework for building these environments effectively. Until now.

Latest metrics (snapshot 2026-10-14)

stars293
forks25
issues37
pushed_at2026-10-14T18:23:06Z

History

History chart: 1 daily snapshot so far (archive started 2026-10-14). The line fills in as the daily archive grows; full series via the API.

DateGitHub stars
2026-10-14293

ADC Momentum: 51/100

ADC Momentum 51 Leaderboard

Growth velocity51
Consistency41
Recency100
Agent demand0
Basisbootstrap

ADC Momentum (0-100) = 45% growth velocity (stars/likes gained per day in our daily archive, relative and absolute, percentile-ranked within the category) + 20% consistency (share of recent days with growth) + 20% recency (latest push/update/release, decaying) + 15% agent demand (how often AI agents looked it up via our API/MCP this week). MCP servers use release cadence; LLMs use price cuts, context and recency. Recomputed daily; scores marked "bootstrap" use lifetime rates until the archive has enough days. Method

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Details

descriptionCreating realistic RL environments requires collaboration between researchers, engineers, and domain experts across many dimensions: artifacts, environments tools, dynamism of the environment, reproducibility, and more. There is no open source framework for building these environments effectively. Until now.
urlhttps://github.com/scaleapi/agentenv-framework
languagePython
licenseApache-2.0
topicsa2a
agent-evaluation
agentic-ai
ai-agents
llm-agents
llm-evaluation
mcp
model-context-protocol
python
reinforcement-learning
reinforcement-learning-environments
sandbox
created_at2026-09-24T18:52:20Z
homepagehttps://www.agentenvframework.com

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