What are the main features of e2b-dev/code-interpreter?

The main features of e2b-dev/code-interpreter are: Code Execution Environments, Sandbox Provisioning Services, MicroVM, Code Execution Runtimes, Code Execution Sandboxes, MicroVM Sandboxes, Persistent Sandbox Creations, Secure Sandboxing.

What are some open-source alternatives to e2b-dev/code-interpreter?

Open-source alternatives to e2b-dev/code-interpreter include: e2b-dev/open-computer-use — Open-computer-use is a framework designed to connect vision-capable language models to isolated cloud-based desktop… zerocore-ai/microsandbox — microsandbox is a platform that runs untrusted code inside hardware-isolated microVMs, each with its own kernel,… alexzhang13/rlm — rlm is an LLM code execution engine and orchestration framework designed to coordinate multiple language model calls… superradcompany/microsandbox — Microsandbox is a runtime for creating and managing lightweight, hardware-isolated virtual machines — called sandboxes… daytonaio/daytona — Daytona is a cloud-native development environment platform designed to orchestrate ephemeral, containerized… opensandbox-group/opensandbox — OpenSandbox is a secure execution environment and runtime designed for running untrusted code and scripts generated by…

Code Interpreter | Awesome Repos

This project is an infrastructure platform designed to provide secure, isolated, and ephemeral cloud-based Linux environments for AI agents and automated code execution. It functions as an orchestrator that provisions on-demand virtual machines, allowing developers to run arbitrary code generated by large language models within hardware-level security boundaries.

The platform distinguishes itself through its ability to manage stateful, long-lived sessions that persist across multiple execution calls, enabling complex, multi-step workflows. It supports high-concurrency scaling, allowing for the simultaneous operation of thousands of isolated instances for parallel data processing, reinforcement learning, and large-scale model evaluation. Additionally, the system provides specialized capabilities for virtual desktop automation, enabling agents to interact directly with graphical Linux interfaces and visual software applications.

Beyond core execution, the platform offers tools for data analysis, visualization, and the extraction of structured information from data frames and plots. It includes support for custom environment configurations, system observability through log access, and deployment options that allow for integration into continuous integration pipelines or hosting within private cloud infrastructure.

The platform is accessible via a software development kit that provides programmatic control over the lifecycle, customization, and management of these sandboxed environments.

Features

Code Execution Environments - Provides secure, isolated cloud environments specifically for executing code generated by artificial intelligence models.
Sandbox Provisioning Services - Automates the creation and management of secure, on-demand Linux virtual machines for code execution.
MicroVM - Orchestrates the provisioning and management of secure, on-demand virtual machine environments for parallel computation.
Code Execution Runtimes - Provides a secure infrastructure platform for running arbitrary code produced by large language models in ephemeral containers.
Code Execution Sandboxes - Executes arbitrary or AI-generated code within secure, isolated microVM environments to protect host systems.
MicroVM Sandboxes - Executes untrusted code within hardware-isolated microVMs to ensure secure boundaries between user sessions.
Persistent Sandbox Creations - Boots named microVMs that remain available for continuous state retention across multiple execution calls.
Secure Sandboxing - Provisions secure, on-demand virtual machine environments to allow agents to perform computation without risking host system security.
MicroVM Agent Sandboxes - Offers a development kit for executing AI-generated code within secure, isolated microVM environments.
Data Processing and Analysis - Connects datasets to isolated runtimes to perform complex computations and data processing through programmatic control.
Large-Scale Data Computation - Facilitates large-scale parallel computing by spawning thousands of concurrent isolated sandbox instances.
Execution State Persistence - Maintains runtime memory and file system state across sequential execution calls to support complex, multi-step workflows.
Containerized Execution Environments - Provides isolated containerized environments for executing code with custom software dependencies and system configurations.
Workflow Execution Scaling - Distributes task processing across thousands of isolated instances to scale data operations and model evaluation.
Compute Resource Provisioning - Dynamically provisions and manages compute resources and virtual machines on-demand for ephemeral execution environments.
Virtual Desktop Infrastructures - Delivers scalable, cloud-based remote desktop instances for agent interaction with graphical interfaces.
Distributed Data Workload Scaling - Scales data processing tasks across clusters to handle large-scale parallel computation and model evaluation workflows.
Virtualized Desktop Environments - Creates cloud-based graphical Linux environments that allow agents to interact directly with desktop interfaces and software.
Cloud Workspace Management - Provides administrative interfaces for managing cloud-hosted sandboxed environments and their lifecycle.

e2b-dev/open-computer-use

2,084View on GitHub

Open-computer-use is a framework designed to connect vision-capable language models to isolated cloud-based desktop environments. It functions as an agentic interface that enables autonomous systems to interact with graphical user interfaces by simulating mouse movements, keyboard keystrokes, and shell commands. By bridging language models with remote workspaces, the platform facilitates the execution of complex, long-running tasks within secure, sandboxed environments. The platform distinguishes itself through its ability to orchestrate thousands of concurrent, isolated instances, making it

zerocore-ai/microsandbox

4,802View on GitHub

microsandbox is a platform that runs untrusted code inside hardware-isolated microVMs, each with its own kernel, filesystem, and network stack. It boots directly from standard OCI container images, supports copy-on-write filesystem layers, and integrates with AI agents to execute tool calls and generated code in isolated environments with secret protection. What sets microsandbox apart is its host-side network proxy that enforces firewall rules, intercepts DNS, inspects TLS traffic, and injects secrets at the network boundary without exposing them inside the VM. It provides SSH access to micr

alexzhang13/rlm

2,609View on GitHub

rlm is an LLM code execution engine and orchestration framework designed to coordinate multiple language model calls and recursive sub-tasks through a programmable environment. It provides a sandboxed REPL environment and a recursive context processor to handle inputs that exceed standard token limits by programmatically decomposing prompts. The project differentiates itself through a reinforcement learning training harness used to teach models how to utilize recursive calls and code execution. It includes a reasoning visualization system that records and renders execution trajectories to ana

superradcompany/microsandbox

6,570View on GitHub

Microsandbox is a runtime for creating and managing lightweight, hardware-isolated virtual machines — called sandboxes — that boot directly from standard OCI container images. Each sandbox runs as its own host process with a separate kernel, filesystem, and network stack, providing process-per-sandbox isolation. The project includes a command-line tool and multi-language SDKs (Rust, TypeScript, Python, Go) for programmatic lifecycle control, and it communicates with sandbox agents over Unix sockets using a CBOR-encoded protocol. What distinguishes Microsandbox is its combination of host-manag

e2b-devcode-interpreter

Code Interpreter

Features