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The OpenHands Agent SDK provides a unified, type-safe framework for building and deploying AI agents—from local experiments to full production systems, focused on statelessness, composability, and clear boundaries between research and deployment. Check this document for the core design principles that guided its architecture.

Relationship with OpenHands Applications

The Agent SDK serves as the source of truth for agents in OpenHands. The OpenHands repository provides interfaces—web app, CLI, and cloud—that consume the SDK APIs. This architecture ensures consistency and enables flexible integration patterns.
  • Agent SDK = foundation. The SDK defines all core components: agents, LLMs, conversations, tools, workspaces, events, and security policies.
  • Interfaces reuse SDK objects. The OpenHands GUI or CLI hydrate SDK components from persisted settings and orchestrate execution through SDK APIs.
  • Consistent configuration. Whether you launch an agent programmatically or via the OpenHands GUI, the supported parameters and defaults come from the SDK.

Four-Package Architecture

The agent-sdk is organized into four distinct Python packages:
PackageWhat It DoesWhen You Need It
openhands.sdkCore agent framework + base workspace classesAlways (required)
openhands.toolsPre-built tools (bash, file editing, etc.)Optional - provides common tools
openhands.workspaceExtended workspace implementations (Docker, remote)Optional - extends SDK’s base classes
openhands.agent_serverMulti-user API serverOptional - used by workspace implementations

Two Deployment Modes

The SDK supports two deployment architectures depending on your needs:

Mode 1: Local Development

Installation: Just install openhands-sdk + openhands-tools
pip install openhands-sdk openhands-tools
Architecture:
  • LocalWorkspace included in SDK (no extra install)
  • Everything runs in one process
  • Perfect for prototyping and simple use cases
  • Quick setup, no Docker required

Mode 2: Production / Sandboxed

Installation: Install all 4 packages
pip install openhands-sdk openhands-tools openhands-workspace openhands-agent-server
Architecture:
  • RemoteWorkspace auto-spawns agent-server in containers
  • Sandboxed execution for security
  • Multi-user deployments
  • Distributed systems (e.g., Kubernetes) support
Key Point: Same agent code works in both modes—just swap the workspace type (LocalWorkspaceDockerWorkspaceRemoteAPIWorkspace).

SDK Package (openhands.sdk)

Purpose: Core components and base classes for OpenHands agent. Key Components:
  • Agent: Implements the reasoning-action loop
  • Conversation: Manages conversation state and lifecycle
  • LLM: Provider-agnostic language model interface with retry and telemetry
  • Tool System: Typed base class definitions for action, observation, tool, and executor; includes MCP integration
  • Events: Typed event framework (e.g., action, observation, user messages, state update, etc.)
  • Workspace: Base classes (Workspace, LocalWorkspace, RemoteWorkspace)
  • Skill: Reusable user-defined prompts with trigger-based activation
  • Condenser: Conversation history compression for token management
  • Security: Action risk assessment and validation before execution
Design: Stateless, immutable components with type-safe Pydantic models. Self-Contained: Build and run agents with just openhands-sdk using LocalWorkspace. Source: openhands-sdk/

Tools Package (openhands.tools)

Tool Independence: Tools run alongside the agent in whatever environment workspace configures (local/container/remote). They don’t run “through” workspace APIs.
Purpose: Pre-built tools following consistent patterns. Design: All tools follow Action/Observation/Executor pattern with built-in validation, error handling, and security.
For full list of tools, see the source code as the source of truth.

Workspace Package (openhands.workspace)

Purpose: Workspace implementations extending SDK base classes. Key Components: Docker Workspace, Remote API Workspace, and more. Design: All workspace implementations extend RemoteWorkspace from SDK, adding container lifecycle or API client functionality. Use Cases: Sandboxed execution, multi-user deployments, production environments.
For full list of implemented workspaces, see the source code.

Agent Server Package (openhands.agent_server)

Purpose: FastAPI-based HTTP/WebSocket server for remote agent execution. Features:
  • REST API & WebSocket endpoints for conversations, bash, files, events, desktop, and VSCode
  • Service management with isolated per-user sessions
  • API key authentication and health checking
Deployment: Runs inside containers (via DockerWorkspace) or as standalone process (connected via RemoteWorkspace). Use Cases: Multi-user web apps, SaaS products, distributed systems.
For implementation details, see the source code.

How Components Work Together

Basic Execution Flow (Local)

When you send a message to an agent, here’s what happens: Key takeaway: The agent orchestrates the reasoning-action loop—calling the LLM for decisions and executing tools to perform actions.

Deployment Flexibility

The same agent code runs in different environments by swapping workspace configuration:

Next Steps

Get Started

Explore Components

SDK Package:
  • Agent – Core reasoning-action loop
  • Conversation – State management and lifecycle
  • LLM – Language model integration
  • Tool System – Action/Observation/Executor pattern
  • Events – Typed event framework
  • Workspace – Base workspace architecture
Tools Package: Workspace Package: Agent Server:

Deploy

Source Code