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# 🤖 Agents
Agent is composed of [🧩 Components](./components.md) and responsible for executing pipelines and some additional logic. The base class for all agents is `BaseAgent`, it has the necessary logic to collect components and execute protocols.
## Important methods
`BaseAgent` provides two abstract methods needed for any agent to work properly:
1. `propose_action`: This method is responsible for proposing an action based on the current state of the agent, it returns `ThoughtProcessOutput`.
2. `execute`: This method is responsible for executing the proposed action, returns `ActionResult`.
## AutoGPT Agent
`Agent` is the main agent provided by AutoGPT. It's a subclass of `BaseAgent`. It has all the [Built-in Components](./built-in-components.md). `Agent` implements the essential abstract methods from `BaseAgent`: `propose_action` and `execute`.
## Building your own Agent
The easiest way to build your own agent is to extend the `Agent` class and add additional components. By doing this you can reuse the existing components and the default logic for executing [⚙️ Protocols](./protocols.md).
```py
class MyComponent(AgentComponent):
pass
class MyAgent(Agent):
def __init__(
self,
settings: AgentSettings,
llm_provider: ChatModelProvider,
file_storage: FileStorage,
legacy_config: Config,
):
# Call the parent constructor to bring in the default components
super().__init__(settings, llm_provider, file_storage, legacy_config)
# Add your custom component
self.my_component = MyComponent()
```
For more customization, you can override the `propose_action` and `execute` or even subclass `BaseAgent` directly. This way you can have full control over the agent's components and behavior. Have a look at the [implementation of Agent](https://github.com/Significant-Gravitas/AutoGPT/tree/master/autogpts/autogpt/autogpt/agents/agent.py) for more details.
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