E2B
e2b.dev
Run your AI code and agents safely in isolated cloud environments.
Description
AI Sandboxes for · Built for AI Agents, LLM Training, and MCPs · IN YOUR CODEWITH A FEW LINES · Features youragents will love · GET INSPIRed BYOUR COOKBOOK
E2B.dev offers a secure, sandboxed cloud environment designed for AI agents and applications, enabling them to execute code safely and efficiently. With its Code Interpreter SDK, developers can integrate code interpreting functionalities into their AI apps, allowing for dynamic code execution and long-running processes. E2B.dev supports multiple programming languages, including Python and JavaScript, and provides robust tools for coding, debugging, and integrating with large language models.
Features
Secure sandboxed environments
Code Interpreter SDK
Support for Python and JavaScript
Long-running cloud processes
Integration with large language models.
Use cases
AI-driven code execution
Secure testing environments
Long-running AI tasks
Dynamic code interpretation in AI apps
Integration with cloud-based AI tools.
FAQ
E2B AI is an open-source, secure cloud platform that provides isolated sandboxed virtual machines (VMs) for running AI-generated code. It is designed for AI agents, LLMs, and developers who need a safe environment to execute code, analyze data, and build advanced AI applications.
E2B AI is for AI developers, companies and enterprises, research groups, startups, and anyone building AI agents, integrating AI into business workflows, or creating AI-powered products.
E2B AI offers secure, isolated cloud sandboxes for running AI-generated code, fast sandbox startup (typically ~150ms), support for multiple programming languages (Python, JavaScript, Java, C++, etc.), real-time interactions and seamless integration with various large language models (LLMs), file upload/download capabilities for data portability, customizable environments with support for installing third-party packages, and virtual desktop environments for more complex agent workflows.
E2B runs AI-generated code inside isolated virtual machines called sandboxes. Each sandbox is a small, secure VM that can be started quickly and managed via simple SDKs (Python or JavaScript). Developers can run multiple sandboxes simultaneously, each for a different user, agent, or session. The platform supports real-time code execution, data analysis, and visualization.
E2B AI supports deep research agents (for analyzing large datasets), AI data analysis & visualization agents (for exploring data and generating charts), coding agents (for executing code, using I/O, accessing the internet, or running terminal commands), reinforcement learning agents (for running and evaluating reward functions), and computer use agents (for providing secure virtual computers in the cloud for LLMs).
Yes, E2B AI is LLM-agnostic and compatible with any model, including OpenAI, Llama, Anthropic, Mistral, and custom models.
The key features include secure cloud sandboxes for safe code execution, multi-language SDKs (Python, JavaScript, Java, C++), real-time interactions and immediate feedback, integration with various LLMs and AI frameworks, support for file upload/download and data portability, customizable environments with package installation, and virtual desktop environments for advanced agent workflows.
To get started with E2B AI, first install the E2B SDK (Python or JavaScript), then set up your API keys (E2B API key and any LLM API keys you plan to use). After that, start and manage sandboxes using the SDK, and finally, upload files, run code, and download results as needed.
The use cases for E2B AI include AI data analysis and visualization, code interpretation and execution, deep research on large datasets, reinforcement learning, computer use agents, and app generation and evaluation.
Yes, E2B is open-source and available on GitHub. Developers can contribute to the project and customize it for their needs.
Documentation and support can be found in the official documentation, the GitHub repository, and through community forums and tutorials available on the official website and GitHub.
Potential limitations include issues with very large datasets or complex AI models that require extensive computational resources. Users should check the documentation for specific compatibility guidelines.
Specs
| Type | Agent |
| Section | Infrastructure & MLOps |
| Pricing | paid (от $150/mo) |
| Platform | Command line |
| Systems | cli, web |
| Hosting | self-hosted |
| Who for | Business |
| Site language | en |
| Rating | 0.00 (0 reviews) |
| Views | 215 366 |
| Launched | 2024-07-24 |
