Yggagentscope-ai/agentscope-runtime
↗ GitHubA production-ready runtime framework for agent apps with secure tool sandboxing, Agent-as-a-Service APIs, scalable deployment, full-stack observability, and broad framework compatibility.
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Safety Rating A
No hardcoded secrets, malicious code patterns, suspicious dependencies, or prompt injection attempts were detected. The repository is a legitimate open-source production runtime framework from Alibaba's Tongyi Lab, released under Apache 2.0. Code examples reference environment variables for API keys (e.g., os.getenv("DASHSCOPE_API_KEY")), which is best practice. The project's sandbox isolation focus actually improves security posture for agent tool execution.
ℹAI-assisted review, not a professional security audit.
AI Analysis
AgentScope Runtime is a production-grade Python framework for deploying AI agent applications as scalable, observable APIs. It provides secure sandboxed tool execution (via Docker, gVisor, or Kubernetes), Agent-as-a-Service (AaaS) streaming APIs built on FastAPI, state management with session persistence, and multi-framework compatibility (AgentScope, LangGraph, Agno, AutoGen, Microsoft Agent Framework). Key features include sync/async sandbox environments (Base, GUI, Browser, Filesystem, Mobile), A2A and OpenAI-compatible API protocols, serverless deployment to Kubernetes or Alibaba Cloud Function Compute, full-stack observability, and a distributed interrupt service for manual task preemption.
Use Cases
- Deploying AI agents as production-ready streaming REST APIs (Agent-as-a-Service)
- Executing untrusted tool calls in isolated sandboxed environments (Python, shell, browser, GUI, mobile)
- Building scalable multi-framework agent backends deployable to Kubernetes or serverless platforms
- Adding persistent session state and conversation memory to agent applications
- Integrating agent services with OpenAI SDK-compatible clients via a compatibility layer
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Project Connections
agentscope-ai/agentscope
AgentScope Runtime is the production deployment and runtime layer purpose-built for the AgentScope multi-agent framework. It provides the Agent-as-a-Service infrastructure, sandboxed tool execution, and scalable deployment capabilities that complement AgentScope's core agent abstractions.
agentscope-ai/CoPaw
CoPaw is a personal AI assistant framework built on AgentScope with multi-channel support. AgentScope Runtime provides the production deployment infrastructure (sandboxed tools, AaaS APIs, Kubernetes deployment) that CoPaw applications could leverage for scalable production use.
judge0/judge0
Both projects provide sandboxed code execution environments accessible via HTTP APIs. Judge0 focuses on competitive programming and multi-language code evaluation, while AgentScope Runtime's sandbox is specifically designed for AI agent tool execution with GUI, browser, mobile, and filesystem capabilities.
builderz-labs/mission-control
Mission Control provides a monitoring and orchestration dashboard for AI agent fleets. AgentScope Runtime provides the deployment infrastructure and AaaS APIs that Mission Control could monitor and manage, together forming a complete agent operations stack.
inngest/inngest
Both provide durable, scalable execution infrastructure for running workflows and agents in production. Inngest focuses on general-purpose step functions and workflow orchestration, while AgentScope Runtime is purpose-built for AI agent deployment with sandboxed tool execution and agent-specific protocols (A2A, AaaS).