AgentIndex icon
AgentIndex
E2B logo
E2B
★ 14.6k
vs
on-policy logo
on-policy
★ 2.1k

E2B vs on-policy

E2B: E2B is an open-source infrastructure that enables running AI-generated code securely in isolated cloud sandboxes. It provides JavaScript and Python SDKs to start and control these sandboxes for AI applications.; on-policy: This repository implements MAPPO, a multi-agent variant of PPO, widely used in cooperative multi-agent games and research. It provides robust implementations for various multi-agent environments like StarCraft II, Hanabi, and Google Research Football, along with detailed training scripts and hyperparameter guidance.

01

TL;DR

E2B logo
E2BLLM Infra · ★ 14.6k

Executing code generated by large language models (LLMs)

Read E2B full review →
on-policy logo
on-policyLLM Infra · ★ 2.1k

Research and experimentation in cooperative multi-agent reinforcement learning

Read on-policy full review →
02

Side-by-Side Comparison

Field
E2B logoE2B
on-policy logoon-policy
Category
LLM Infra
LLM Infra
Stars
★ 14.6k
★ 2.1k
License
Apache-2.0
MIT
Install Command
pip install e2b
pip install -e .
Updated
1d ago
2y ago
Open Source
Yes
Yes
Website
↗ Visit
↗ Visit
GitHub
↗ GitHub
↗ GitHub
Tags
AI Code Generation, Sandboxing, SDK
Multi-Agent Reinforcement Learning, PPO, MAPPO
03

Features

E2B logoE2B
01Open-source infrastructure for AI code execution
02Secure isolated cloud sandboxes
03Execute AI-generated code safely
04Available with JavaScript and Python SDKs
05Self-hosting capabilities on major cloud providers
on-policy logoon-policy
01Implementation of MAPPO (Multi-Agent PPO)
02Support for diverse multi-agent environments (e.g., StarCraft II, Hanabi)
03Ready-to-use training scripts for various scenarios
04Detailed hyperparameter guidance and updated results
05Default support for shared policy among agents
04

Use Cases

E2B logoE2B
↳Executing code generated by large language models (LLMs)
↳Integrating secure code execution into AI applications
↳Developing AI agents that require isolated runtime environments
on-policy logoon-policy
↳Research and experimentation in cooperative multi-agent reinforcement learning
↳Benchmarking and evaluating PPO's effectiveness in MARL scenarios
↳Training AI agents for popular multi-agent games like StarCraft II and Hanabi
05

Best For

E2B logoE2B
Most PopularEssentialTrending
on-policy logoon-policy
—
FAQ

FAQ

What is the difference between E2B and on-policy?
Both E2B and on-policy are in the LLM Infra category. E2B has 14.6k stars, while on-policy has 2.1k stars.
Which is better, E2B or on-policy?
The best choice depends on your use case. Choose E2B if Executing code generated by large language models (LLMs), and on-policy if Research and experimentation in cooperative multi-agent reinforcement learning.
Is E2B free or open source?
Yes, E2B is open source on GitHub (Apache-2.0).
Is on-policy free or open source?
Yes, on-policy is open source on GitHub (MIT).
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Related

Alternatives to E2B →Alternatives to on-policy →E2B details →on-policy details →