E2B Cookbook is an open-source collection of example projects, guides, and reference implementations demonstrating how to build applications using the E2B platform. The repository acts as a practical learning resource for developers who want to integrate AI agents with secure cloud execution environments that allow large language models to run code and interact with tools. The examples illustrate how developers can build AI workflows capable of performing tasks such as data analysis, code execution, and application generation inside isolated sandbox environments. E2B itself provides secure Linux-based sandboxes that enable AI systems to safely run generated code and interact with real computing resources without compromising the host environment. The cookbook organizes examples across multiple frameworks and model providers, allowing developers to experiment with integrations involving models from OpenAI, Anthropic, and other ecosystems.

Features

  • Example projects demonstrating AI agent workflows using E2B sandbox environments
  • Code samples in multiple languages including Python and TypeScript
  • Integrations with large language model providers and AI frameworks
  • Tutorials for building data analysis, research, and coding agents
  • Examples showing secure execution of AI-generated code in sandboxed environments
  • Reference implementations for connecting external tools and APIs to AI agents

Project Samples

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License

MIT License

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Additional Project Details

Programming Language

Python

Related Categories

Python Large Language Models (LLM)

Registered

2026-03-09