# Overview - Documentation

> For the complete documentation index, see [llms.txt](/llms.txt). Markdown is available with `Accept: text/markdown` and `.md` URL variants.

Source: /docs/guides/sandbox-agent-runtime-introduction

# Overview

##

[​](#what-is-novita-agent-runtime)

What is Novita Agent Runtime?

Novita Agent Runtime is a lightweight framework for deploying AI Agents that enables you to deploy AI Agents quickly and cost-effectively.
No need to worry about infrastructure configuration, container orchestration, service exposure, or other complex details—just focus on developing your Agent’s business logic.

##

[​](#core-components)

Core Components

Novita Agent Runtime is included in the Novita Sandbox SDK and CLI tools:

ComponentDescriptionNovita Sandbox SDKProvides decorator-based APIs to expose your Agent as a standard HTTP service, and methods to invoke AgentsNovita Sandbox CLIOne-click configuration and deployment of Agents to the Novita Agent Sandbox ecosystem

##

[​](#deployment-workflow)

Deployment Workflow

The complete deployment and usage workflow consists of three steps:

###

[​](#step-1-develop-and-integrate-your-agent)

Step 1: Develop and Integrate Your Agent

Integrate the SDK into your Agent code by adding decorators:

```
from novita_sandbox.agent_runtime import AgentRuntimeApp

app = AgentRuntimeApp()

@app.entrypoint
def my_agent(request: dict):
# Agent business logic
return {"result": "..."}
```

###

[​](#step-2-configure-and-deploy)

Step 2: Configure and Deploy

Use the CLI tool to configure and deploy to the cloud:

```
# Configure Agent
novita-sandbox-cli agent configure

# Deploy to cloud
novita-sandbox-cli agent launch
```

- Generates `Dockerfile` and `.novita-agent.yaml` configuration files

- Builds sandbox template and uploads it

- Generates Agent ID (format: `agent_<name>_v<version>`)

###

[​](#step-3-invoke-agent)

Step 3: Invoke Agent

After successful deployment, you can invoke your Agent via CLI or SDK:
Option 1: Quick test with CLI

```
novita-sandbox-cli agent invoke "Hello, Agent!"
```

Option 2: Invoke via SDK in your application

```
import json
from novita_sandbox.agent_runtime import AgentRuntimeClient

client = AgentRuntimeClient(api_key="your-api-key")

# Prepare request data (converted to a JSON string and encoded as bytes)
payload = json.dumps({"prompt": "Hello, Agent!"}).encode()

response = await client.invoke_agent_runtime(
agentId="agent-xxxxx",
payload=payload
)
```

Agent invocation execution flow:

- Creates an isolated sandbox instance from the sandbox template

- Executes the Agent in an isolated environment

- Returns the processed result

##

[​](#key-benefits)

Key Benefits

SDK:

- ✅ Minimal Changes: Just modify a few lines of code with decorators

- ✅ Framework Agnostic: Supports LangChain, LangGraph, CrewAI, and other popular AI frameworks

- ✅ Streaming Support: Native streaming responses for real-time LLM generation scenarios

- ✅ Health Checks: Built-in health check endpoint with customizable health status

CLI:

- ✅ Smart Detection: Auto-detects project structure, entry files, and dependency management files

- ✅ Auto Build: Automatically generates Dockerfile and project configuration

- ✅ Version Management: Supports multiple versions coexisting with independent deployments

- ✅ Quick Testing: Built-in invoke command for rapid deployment verification

Runtime:

- ✅ Environment Isolation: Each sandbox instance runs independently without interference

- ✅ Session Persistence: Multiple invocations to the same sandbox instance, supporting multi-turn interactive Agents

- ✅ Secure Sandbox: Securely isolated sandbox environment with restricted filesystem access

Last modified on November 27, 2025