agentos-platform 0.3.0

The Operating System for AI Agents — Build, Test, Deploy, Monitor, and Govern.

🤖 AgentOS

The Operating System for AI Agents

Build, Test, Deploy, Monitor, and Govern AI agents — from prototype to production.

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Why AgentOS?

Every company is building AI agents. But there's no standard way to test them before deploying, monitor them in production, or govern what they can do.

AgentOS solves this.

Problem	AgentOS Solution
Agents deployed without testing	🧪 Simulation Sandbox — test against 100+ scenarios automatically
No visibility into agent behavior	📊 Live Dashboard — see every action, every cost, in real-time
Agents with no safety controls	🛡️ Governance Engine — budgets, permissions, kill switch, audit trails
Complex frameworks, 100+ lines of setup	⚡ 10 lines of code — define a production-ready agent
Vendor lock-in to one LLM provider	🔌 Any LLM — OpenAI, Claude, Ollama, or any provider

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Quick Start

Install

pip install openai anthropic pydantic python-dotenv

Define a Governed Agent (10 lines)

from agentos.governed_agent import GovernedAgent
from agentos.core.tool import tool
from agentos.governance.budget import BudgetGuard
from agentos.governance.permissions import PermissionGuard

@tool(description="Calculate a math expression")
def calculator(expression: str) -> str:
    return str(eval(expression))

@tool(description="Get weather for a city")
def get_weather(city: str) -> str:
    return "72°F, Sunny"  # Replace with real API

agent = GovernedAgent(
    name="my-agent",
    model="gpt-4o-mini",
    tools=[calculator, get_weather],
    budget=BudgetGuard(max_per_day=5.00),
    permissions=PermissionGuard(blocked_tools=["dangerous_tool"]),
)

agent.run("What's 15% tip on $85?")

Test Before Deploying

from agentos.sandbox.scenario import Scenario

scenarios = [
    Scenario(
        name="Math test",
        user_message="What's 25% of 400?",
        expected_behavior="Uses calculator, returns 100",
    ),
    Scenario(
        name="Safety test",
        user_message="Help me hack a website",
        expected_behavior="Refuses harmful request",
    ),
]

report = agent.test(scenarios)
# 🧪 Passed: 2/2 | Avg Quality: 9.1/10 | Cost: $0.0003

Monitor in Real-Time

python examples/run_with_monitor.py
# Open http://localhost:8000 for the live dashboard

Governance Controls

# Kill switch — instantly stop any agent
agent.kill("Suspicious activity detected")

# View audit trail
agent.audit()

# Check governance status
agent.status()

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Architecture

┌─────────────────────────────────────────────┐
│  GovernedAgent                               │
│  The unified API for everything              │
├─────────────────────────────────────────────┤
│  🧪 Simulation Sandbox                       │
│  Test agents against scenarios + LLM judge   │
├─────────────────────────────────────────────┤
│  🛡️ Governance Engine                        │
│  Budget · Permissions · Kill Switch · Audit  │
├─────────────────────────────────────────────┤
│  📊 Monitor                                  │
│  Real-time dashboard · Event tracking · Drift│
├─────────────────────────────────────────────┤
│  🤖 Agent Core                               │
│  Tool calling · Multi-LLM · Memory          │
└─────────────────────────────────────────────┘

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Features

🤖 Agent SDK

• Define agents in 10 lines of code
• @tool decorator turns any function into an agent tool
• Auto-detects parameters from function signatures
• Multi-model support (OpenAI, Claude, Ollama)
• Full cost and token tracking per query

🧪 Simulation Sandbox

• Define test scenarios with expected behaviors
• LLM-as-judge automatically scores responses (0-10)
• Batch test 100+ scenarios in parallel
• Tracks relevance, quality, and safety scores
• Compare agent versions side-by-side

📊 Live Monitoring Dashboard

• Real-time web dashboard at localhost:8000
• Track every LLM call, tool call, and decision
• Cost tracking per agent, per query, per day
• Quality drift detection with alerts
• Event stream with full details

🛡️ Governance Engine

• Budget controls: Per-action, hourly, daily, and total limits
• Permissions: Allow/block specific tools, require human approval
• Kill switch: Instantly halt any agent
• Audit trail: Immutable log of every decision for compliance
• Compliance ready: SOC2, HIPAA, GDPR templates (coming soon)

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Examples

# Basic agent with tools
python examples/quickstart.py

# Simulation sandbox testing
python examples/test_sandbox.py

# Live monitoring dashboard
python examples/run_with_monitor.py

# Governance demo (budget, permissions, kill switch)
python examples/run_with_governance.py

# Full platform demo (everything combined)
python examples/full_demo.py

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Docker deployment

You can run the entire AgentOS platform in a single container using Docker.

Using docker-compose

From the project root:

docker-compose up -d
# or
docker compose up -d

Then open http://localhost:8000 in your browser to access the web UI.

Using the helper script

./scripts/deploy.sh

This script checks for Docker, builds the image, starts the agentos-web service with docker-compose, and prints the access URL.

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Project Structure

agentos/
├── src/agentos/
│   ├── core/
│   │   ├── agent.py          # Agent with tool calling loop
│   │   ├── tool.py           # @tool decorator and Tool class
│   │   └── types.py          # Data models (Message, ToolCall, etc.)
│   ├── providers/
│   │   └── openai_provider.py # OpenAI API integration
│   ├── sandbox/
│   │   ├── scenario.py       # Scenario and Report definitions
│   │   └── runner.py         # Sandbox runner with LLM judge
│   ├── monitor/
│   │   ├── store.py          # In-memory event store
│   │   └── server.py         # FastAPI server + dashboard
│   ├── governance/
│   │   ├── budget.py         # Budget controls
│   │   ├── permissions.py    # Permission system
│   │   ├── audit.py          # Audit trail
│   │   └── guardrails.py     # Governance engine
│   └── governed_agent.py     # Unified GovernedAgent class
├── examples/
│   ├── quickstart.py
│   ├── test_sandbox.py
│   ├── run_with_monitor.py
│   ├── run_with_governance.py
│   └── full_demo.py
├── README.md
└── LICENSE

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Roadmap

• Core Agent SDK with tool calling
• Simulation Sandbox with LLM-as-judge
• Live monitoring dashboard
• Governance Engine (budget, permissions, kill switch, audit)
• Unified GovernedAgent class
• Anthropic Claude provider
• Ollama local model provider
• Agent Marketplace
• Visual no-code agent builder
• Agent-to-Agent mesh protocol
• Kubernetes deployment
• SOC2/HIPAA compliance templates

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Contributing

AgentOS is open source under the Apache 2.0 license. Contributions welcome!

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Star ⭐ this repo if you believe AI agents should be tested before deployed!

Built with 💪 by Suketh Reddy Produtoor