Action Agents
Empowering agents to take actions during conversations.
Note: Support for actions is currently limited to ChatGPTAgent
.
What are actions?
Actions refer to specific tools an agent can execute during the conversation. These actions can encompass various activities like writing an email,
scheduling an appointment, and so forth. They are implemented as classes derived from the BaseAction
class.
The BaseAction
class is defined as follows:
Every action class derived from BaseAction must implement the run method, which is called to execute the action. Importantly, each action class should include a docstring for this method that explains the expected parameters. This docstring is critical as it provides the information that the AI will consume in its prompt when instructing the execution of the action.
Agent Actions
The agent is responsible for managing and executing actions within a conversation. The agent consumes a configuration object at instantiation, which specifies the actions that the agent can perform.
The agent configuration lists the actions available to the agent:
ActionsWorker
: how actions are executed and consumed
The ActionsWorker
class plays a crucial role in the async processing of actions within the system. It’s a specialized form of the InterruptibleWorker
class,
designed to handle the execution of actions and passing results back to the agent.
The ActionsWorker
is initialized with an input queue and an output queue. It uses an ActionFactory
instance to create and execute actions based on the inputs it receives.
The flow of actions is as follows:
- Agent sends action requests to the
ActionsWorker
through the worker’s input queue. ActionsWorker
reads the action request from the input queue. It then creates an instance of the appropriate action using theActionFactory
, and executes it using the provided parameters.- The executed action returns an
ActionOutput
object which encapsulates the result of the action. ActionsWorker
creates anActionResultAgentInput
from theActionOutput
, and puts it in its output queue.- The agent then consumes the
ActionResultAgentInput
from the queue in its process method. This result is added to the transcript of the conversation, and can influence the behavior of the agent in subsequent interactions.
Implementing your own action: Nylas email example
In this section, we provide an example of an action, NylasSendEmail
, which extends the BaseAction
class. It implements the run method to send an email using the Nylas API.
See Agent Factory for more information on how to register your action with the agent factory.