vndee/llm-sandbox

Features

• Code Interpreter Libraries - A Python library for executing untrusted code within isolated, secure container environments to support LLM-driven data analysis and agentic workflows.
• Code Execution Sandboxes - Provides secure, isolated code execution environments for running snippets across multiple programming languages.
• Coding Agents - Enables autonomous agents to safely run code snippets and process data within isolated containerized environments.
• AI Code Interpreters - Integrates secure, on-demand code execution into applications to handle dynamic tasks and generate visual artifacts.
• Containerized Sandbox Runtimes - Manages isolated environments for running code snippets with configurable resource limits, security policies, and dependency management.
• Sandboxed Code Execution Environments - Provides isolated runtime environments for securely executing user-submitted code or scripts with restricted system access.
• Sandboxed Execution Platforms - A flexible execution platform supporting multiple programming languages with persistent state, artifact extraction, and pre-warmed container pools for low-latency performance.
• Isolated Code Execution - Provides secure, containerized execution environments for running untrusted code while protecting the host system.
• Agent Execution Environments - Provides a secure runtime that enables autonomous agents to perform data processing, file manipulation, and visualization generation within sandboxed containers.
• Container-Based Sandboxes - Executes untrusted code within restricted, ephemeral container environments to prevent unauthorized host access.
• AI Agent Integrations - Provides connectors for integrating autonomous agents into secure code execution workflows.
• MCP Protocol Integrations - Implements the Model Context Protocol to connect isolated execution environments to AI assistants.
• Container Pool Managers - Maintains pre-initialized execution environments to minimize startup latency.
• LLM Integration Frameworks - Provides connectors for model-driven workflows to perform secure code processing and data visualization.
• Runtime Abstraction Layers - Provides a unified interface to manage diverse container runtimes and infrastructure providers.
• Remote Target Artifact Extraction - Automatically captures and retrieves files and visualizations generated during code execution.
• Execution Artifact Extractors - Automatically captures and serializes visual plots and generated files from the isolated environment.
• Execution State Persistence - Maintains interpreter variables and file system state across multiple execution steps for interactive workflows.
• Container State Persistence - Saves environment configurations and installed dependencies after execution to allow for faster reuse of containers in subsequent tasks.
• Execution Middleware - Supports wrapping code execution with custom middleware logic for logging, caching, and automatic retries to improve workflow reliability.
• Package Dependency Managers - Dynamically installs required libraries and packages within the sandbox environment to support complex workflows relying on third-party software.
• Real-Time Output Streaming - Invokes callbacks in real-time as code produces output, allowing for immediate processing of logs or results during long-running tasks.
• Execution Timeouts - Enables setting total duration limits for code execution to prevent runaway processes from consuming excessive system resources.
• Containerized Infrastructure Managers - Deploys and scales secure code execution backends across various container runtimes with policy enforcement.
• Execution Backend Failover - The project supports configuring multiple execution backends in sequence, automatically switching to secondary providers if the primary backend fails to respond.
• Multi-Language Runtime Support - Supports execution across various programming languages with automatic dependency management and specialized container image usage.
• Custom Execution Environment Definitions - The project allows tailoring execution environments by specifying language versions, custom container images, or pre-built configurations for specific project requirements.
• Exploratory Data Analysis Workflows - Maintains persistent interpreter sessions to support multi-step data processing and visualization tasks.
• Execution Policy Enforcers - Validates code against defined security rules and patterns to block dangerous operations before they are executed.
• Module Access Restrictions - Prevents unauthorized access to sensitive system or network libraries by restricting module imports within the execution environment.
• Sandbox Policy Configurations - Allows customizing sandbox behavior by defining security policies and resource limits.
• Policy-Driven Execution Guardrails - Wraps code execution with validation logic to enforce security constraints and resource limits.
• Execution Resource Constraints - Provides granular control over CPU and memory usage for code execution tasks to ensure system stability and prevent resource exhaustion.

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