> ## Documentation Index
> Fetch the complete documentation index at: https://docs.orq.ai/llms.txt
> Use this file to discover all available pages before exploring further.
# Getting started with Control Tower
> Start monitoring your AI agents in Control Tower. Connect a supported framework, send traces, and watch your assets appear automatically.
Control Tower gives you real-time visibility into every AI agent running in your workspace: costs, token usage, errors, and performance, without manual instrumentation. You connect your framework once, send traces via OpenTelemetry, and Orq.ai does the rest.
**Orq.ai Agents, Deployments, and Models** used via the Orq Router, API or SDKs are monitored automatically—no additional setup required.
## Get Started
This guide uses **OpenAI Agents** to walk you through the setup. If you are using a different framework, see [Supported Agents](#supported-agents) below.
Your API key authenticates trace exports to Orq.ai. To find it:
1. Open the [Orq.ai dashboard](https://my.orq.ai)
2. Go to **Workspace Settings → API Keys**
3. Copy an existing key or create a new one
Store it as an environment variable:
```bash theme={"theme":{"light":"github-light","dark":"github-dark"}}
export ORQ_API_KEY=""
```
Never commit your API key to source control. Use environment variables or a secrets manager.
```bash theme={"theme":{"light":"github-light","dark":"github-dark"}}
pip install orq-ai-sdk openai-agents \
opentelemetry-sdk opentelemetry-instrumentation opentelemetry-exporter-otlp
```
Set up the OTLP exporter and instrument OpenAI Agents before running any code:
```python Python theme={"theme":{"light":"github-light","dark":"github-dark"}}
import os
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import BatchSpanProcessor
from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
from orq_ai_sdk.openai_agents_instrumentation import OpenAIAgentsInstrumentor
os.environ["OTEL_EXPORTER_OTLP_ENDPOINT"] = "https://api.orq.ai/v2/otel"
os.environ["OTEL_EXPORTER_OTLP_HEADERS"] = f"Authorization=Bearer {os.environ['ORQ_API_KEY']}"
tracer_provider = TracerProvider()
tracer_provider.add_span_processor(BatchSpanProcessor(OTLPSpanExporter()))
OpenAIAgentsInstrumentor().instrument(tracer_provider=tracer_provider)
```
Any OpenAI agent you run will now automatically send traces to Control Tower:
```python Python theme={"theme":{"light":"github-light","dark":"github-dark"}}
from agents import Agent, Runner, function_tool
@function_tool
def get_weather(location: str) -> str:
"""Get weather for a location."""
data = {"tokyo": "Sunny, 22°C", "paris": "Cloudy, 15°C"}
return data.get(location.lower(), f"No data for {location}")
agent = Agent(
name="Weather Assistant",
instructions="Use get_weather to answer weather questions.",
tools=[get_weather],
model="gpt-4o",
)
result = Runner.run_sync(agent, "What's the weather in Tokyo?")
print(result.final_output)
```
Orq.ai captures: `agent/Weather Assistant`, `tool/get_weather`, `model/gpt-4o`.
Open the [Assets page](/docs/control-tower/assets). Agents, tools, and models from your traces will appear automatically under their respective tabs.
## Next Steps
Monitor all agents at a glance with summary metrics and the agents performance table.
Manage and inspect every agent, tool, deployment, and model captured in your workspace.
## Supported Agents
Native Orq.ai Agents with automatic asset capture. Build agents in the AI Studio or via API—monitoring is built-in.
Build agents with the OpenAI Agents SDK and automatically capture them in Control Tower via OpenTelemetry.
Stateful, multi-actor agent framework with graph-based orchestration. Full asset capture support.
JavaScript/TypeScript SDK for AI-powered applications with streaming and multi-model support. Full asset capture support.