# 🚀 Deploying an Agent with Agentor

This example shows how to deploy a **scalable, production-ready Agent server** using `Agentor` ✴️.

We’ll integrate Agentor with [CelestoSDK tools](https://celesto.ai/toolhub) to create a weather-aware conversational agent.

## 🔧 Key Features

- ⚡️ Scalable inference powered by `Agentor`
- 🔄 Async streaming for real-time interaction
- 🧩 Custom tools via the `@function_tool` decorator (e.g., get_weather, search_docs, or your own functions)
- ☁️ Deploy on cloud

## Example

Here’s an example of deploying an Agentor instance with a simple weather tool in just three lines of code.

```python
from agentor import Agentor

agent = Agentor(
    name="Agentor",
    model="gpt-5-mini",
    tools=["get_weather"],
)

agent.serve(port=8000)
```

## Query the Agent server

Once the server is running, you can send chat requests using curl or any HTTP client:

```bash
curl -X 'POST' \
  'http://localhost:8000/chat' \
  -H 'accept: application/json' \
  -H 'Content-Type: application/json' \
  -d '{
  "input": "What is the weather in London?"
}'
```

The Agent server will respond asynchronously — ideal for streaming, scalable, and multi-agent applications.

## Deploy on cloud

```
# Deploy the Agent to cloud
agentor deploy --folder ./

# List the deployed API
agentor ls
```
