> ## Documentation Index
> Fetch the complete documentation index at: https://docs.orkestration.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Agents

Agents are LLM-powered workers with a name, description, and bound LLM client.

## Parameters

* **name**: Human-friendly label.
* **description**: What the agent does.
* **model\_provider**: LLM vendor (e.g., `openai`).
* **model\_name**: Model ID (e.g., `gpt-4o`, `gpt-3.5-turbo`).
* **api\_secret**: Provider API key (distinct from Orkestra `api_key`).

## Attributes

* **config.name**: Agent name
* **config.description**: Agent description
* **llm**: Underlying LLM abstraction

## Create an agent

```python theme={null}
from orkestra import Orkestra, LLMProvider
client = Orkestra()
agent = client.Agent(
  name="Summarizer",
  description="Summarizes text",
  model_provider="openai",
  model_name="gpt-3.5-turbo",
  api_secret="YOUR_OPENAI_API_KEY",
)
```

## Generate: plain text

```python theme={null}
response = agent.generate("Write a bedtime story about a friendly unicorn.")
print(response)
```

## Generate: structured output (Pydantic)

```python theme={null}
from pydantic import BaseModel

class CalendarEvent(BaseModel):
  name: str
  date: str
  participants: list[str]

event = agent.generate(
  "Alice and Bob are going to a science fair on Friday.",
  response_model=CalendarEvent,
)
print(event)
```