WorkerClass Documentation

Overview

The Worker class represents an autonomous agent that can perform tasks through function calls or by running a chat. It can be used to create applications that demand effective user interactions like search engines, human-like conversational bots, or digital assistants.

The Worker class is part of the swarms.agents codebase. This module is largely used in Natural Language Processing (NLP) projects where the agent undertakes conversations and other language-specific operations.

Class Definition

The class Worker has the following arguments:

Argument	Type	Default Value	Description
name	str	"Worker"	Name of the agent.
role	str	"Worker in a swarm"	Role of the agent.
external_tools	list	None	List of external tools available to the agent.
human_in_the_loop	bool	False	Determines whether human interaction is required.
temperature	float	0.5	Temperature for the autonomous agent.
llm	None	None	Language model.
openai_api_key	str	None	OpenAI API key.
tools	List[Any]	None	List of tools available to the agent.
embedding_size	int	1536	Size of the word embeddings.
search_kwargs	dict	{"k": 8}	Search parameters.
args	Multiple		Additional arguments that can be passed.
kwargs	Multiple		Additional keyword arguments that can be passed.
## Usage

Example 1: Creating and Running an Agent

from swarms import Worker

worker = Worker(
    name="My Worker",
    role="Worker",
    external_tools=[MyTool1(), MyTool2()],
    human_in_the_loop=False,
    temperature=0.5,
    llm=some_language_model,
    openai_api_key="my_key",
)
worker.run("What's the weather in Miami?")

Example 2: Receiving and Sending Messages

worker.receieve("User", "Hello there!")
worker.receieve("User", "Can you tell me something about history?")
worker.send()

Example 3: Setting up Tools

external_tools = [MyTool1(), MyTool2()]
worker = Worker(
    name="My Worker",
    role="Worker",
    external_tools=external_tools,
    human_in_the_loop=False,
    temperature=0.5,
)

Additional Information and Tips

The class allows the setting up of tools for the worker to operate effectively. It provides setup facilities for essential computing infrastructure, such as the agent's memory and language model.
By setting the human_in_the_loop parameter to True, interactions with the worker can be made more user-centric.
The openai_api_key argument can be provided for leveraging the OpenAI infrastructure and services.
A qualified language model can be passed as an instance of the llm object, which can be useful when integrating with state-of-the-art text generation engines.