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7 Repos

Awesome GitHub RepositoriesIsolated Evaluation Environments

Ephemeral execution environments for running agent tests in isolation.

Distinct from Isolated Execution Environments: Distinct from general isolated execution: focuses on creating fresh agent instances for reproducible evaluation samples.

Explore 7 awesome GitHub repositories matching development tools & productivity · Isolated Evaluation Environments. Refine with filters or upvote what's useful.

Awesome Isolated Evaluation Environments GitHub Repositories

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  • letta-ai/lettaAvatar von letta-ai

    letta-ai/letta

    21,168Auf GitHub ansehen↗

    Letta is a framework for building, deploying, and managing autonomous AI agents that maintain persistent state across long-term interactions. It provides a comprehensive suite of primitives for defining agents with configurable personas, modular memory blocks, and tool-use capabilities, enabling them to retain user preferences and conversation history over extended sessions. The platform distinguishes itself through its advanced memory management and orchestration capabilities. It allows agents to autonomously update their own memory, perform retrieval-augmented generation, and coordinate com

    Creates fresh, independent agent instances for each test sample to ensure reproducible results without state cross-contamination.

    Pythonaiai-agentsllm
    Auf GitHub ansehen↗21,168
  • claude-code-best/claude-codeAvatar von claude-code-best

    claude-code-best/claude-code

    20,272Auf GitHub ansehen↗

    Claude Code is a command-line interface and multi-agent orchestration framework designed for autonomous software engineering. It enables AI agents to perform codebase modifications, debugging, and Git workflow management while coordinating multiple specialized agents to decompose and execute complex engineering tasks in parallel. The system distinguishes itself through a high degree of isolation and safety, utilizing Git worktrees to create independent working directories for concurrent agents and implementing a tiered permission system that combines user rules, project policies, and OS-level

    Runs sub-agents in isolated Git worktrees or remote environments to prevent side effects on the primary codebase.

    TypeScript
    Auf GitHub ansehen↗20,272
  • rllm-org/rllmAvatar von rllm-org

    rllm-org/rllm

    5,641Auf GitHub ansehen↗

    rllm is an asynchronous reinforcement learning framework for training language agents. It provides a unified pipeline that runs the same agent code for both evaluation and training, automatically capturing traces for gradient computation. The framework supports distributed reinforcement learning across multiple GPUs and nodes using pluggable backends, and executes agents in isolated sandboxes—either locally or in the cloud—for safe and scalable rollout collection. It trains agents built with LangGraph, SmolAgents, OpenAI Agents SDK, or custom frameworks without requiring core logic changes. T

    Executes agents in isolated ephemeral sandboxes, either locally or in the cloud, for safe and scalable rollout collection.

    Pythonagent-frameworkagentic-workflowcoding-agent
    Auf GitHub ansehen↗5,641
  • klavis-ai/klavisAvatar von Klavis-AI

    Klavis-AI/klavis

    5,640Auf GitHub ansehen↗

    Klavis is a platform for managing Model Context Protocol (MCP) servers and providing sandboxed environments where AI agents can safely interact with external tools and services. It functions as an integration framework that orchestrates MCP server instances, exposes tools and resources for AI agents, and isolates agent interactions from production data through horizontally scalable sandbox environments. The platform distinguishes itself through its ability to generate long-horizon agentic tasks that simulate realistic tool-use workflows with live SaaS applications and production MCP servers.

    Provisions dedicated, horizontally scalable sandbox environments that isolate agent interactions from production data.

    Pythonagentsaiai-agents
    Auf GitHub ansehen↗5,640
  • erikbjare/gptmeAvatar von ErikBjare

    ErikBjare/gptme

    4,334Auf GitHub ansehen↗

    gptme is a multi-agent orchestration platform designed for autonomous software engineering, terminal-based AI integration, and RAG-enhanced code navigation. It enables the deployment of persistent agents and specialized subagents to decompose complex tasks and execute parallel technical workflows. The system distinguishes itself through a combination of vision-based GUI automation for controlling desktop applications and surgical patching mechanisms for targeted source code modifications. It utilizes git-based memory management to maintain a versioned history of agent identities, lessons, and

    Protects the primary codebase by running validation processes in isolated version control worktrees.

    Python
    Auf GitHub ansehen↗4,334
  • octelium/octeliumAvatar von octelium

    octelium/octelium

    3,371Auf GitHub ansehen↗

    Octelium is a zero-trust network access platform and identity-aware proxy designed to secure private HTTP, SSH, and SQL resources. It functions as a secure gateway that validates human and workload identities using OIDC, SAML, and FIDO2 passkeys before granting access to internal applications and SaaS APIs. The system is distinguished by its secretless access broker, which injects credentials—such as API keys, passwords, and AWS Sigv4 signatures—at the gateway level so users can access databases and cloud resources without managing secrets. It further specializes in AI gateway administration,

    Provides isolated Kubernetes-based environments for developers and AI agents to access services.

    Goabacai-gatewayapi-gateway
    Auf GitHub ansehen↗3,371
  • xlang-ai/osworldAvatar von xlang-ai

    xlang-ai/OSWorld

    2,584Auf GitHub ansehen↗

    OSWorld is an evaluation framework and multimodal agent benchmark designed to test the ability of large language models to complete complex tasks within virtualized operating system environments. It provides a virtualized desktop sandbox and a virtual machine orchestrator to deploy, snapshot, and reset cloud-based desktops, ensuring reproducible test states for AI agent interactions. The system distinguishes itself by providing an OS-level action space that translates model decisions into mouse clicks, keyboard inputs, and system commands. It employs a standardized interface to integrate vari

    Secures the environment by running agent instances within a dedicated virtual private cloud and subnet.

    Pythonagentartificial-intelligencebenchmark
    Auf GitHub ansehen↗2,584
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Unter-Tags erkunden

  • Agent Sandbox ProvisionersProvisions dedicated, horizontally scalable environments for AI agents to interact with external services without affecting real data. **Distinct from Isolated Evaluation Environments:** Distinct from Isolated Evaluation Environments: focuses on provisioning sandboxes for agent testing with external services, not just ephemeral evaluation runs.
  • Worktree IsolationIsolation of agent execution using version control worktrees or remote environments to prevent side effects on the primary codebase. **Distinct from Isolated Evaluation Environments:** Distinct from evaluation environments: focuses on protecting the primary codebase during active development tasks.