swarms/docs/examples/worker.md

The Ultimate Guide to Mastering the Worker Class from Swarms

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Table of Contents

1. Introduction: Welcome to the World of the Worker
2. The Basics: What Does the Worker Do?
3. Installation: Setting the Stage
4. Dive Deep: Understanding the Architecture
5. Practical Usage: Let's Get Rolling!
6. Advanced Tips and Tricks
7. Handling Errors: Because We All Slip Up Sometimes
8. Beyond the Basics: Advanced Features and Customization
9. Conclusion: Taking Your Knowledge Forward

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1. Introduction: Welcome to the World of the Worker

Greetings, future master of the Worker! Step into a universe where you can command an AI worker to perform intricate tasks, be it searching the vast expanse of the internet or crafting multi-modality masterpieces. Ready to embark on this thrilling journey? Let’s go!

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2. The Basics: What Does the Worker Do?

The Worker is your personal AI assistant. Think of it as a diligent bee in a swarm, ready to handle complex tasks across various modalities, from text and images to audio and beyond.

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3. Installation: Setting the Stage

Before we can call upon our Worker, we need to set the stage:

pip install swarms

Voila! You’re now ready to summon your Worker.

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4. Dive Deep: Understanding the Architecture

• Language Model (LLM): The brain of our Worker. It understands and crafts intricate language-based responses.
• Tools: Think of these as the Worker's toolkit. They range from file tools, website querying, to even complex tasks like image captioning.
• Memory: No, our Worker doesn’t forget. It employs a sophisticated memory mechanism to remember past interactions and learn from them.

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5. Practical Usage: Let's Get Rolling!

Here’s a simple way to invoke the Worker and give it a task:

from swarms.models import OpenAIChat
from swarms import Worker

llm = OpenAIChat(
    #enter your api key
    openai_api_key="",
    temperature=0.5,
)

node = Worker(
    llm=llm,
    ai_name="Optimus Prime",
    openai_api_key="",
    ai_role="Worker in a swarm",
    external_tools=None,
    human_in_the_loop=False,
    temperature=0.5,
)

task = "What were the winning boston marathon times for the past 5 years (ending in 2022)? Generate a table of the year, name, country of origin, and times."
response = node.run(task)
print(response)

The result? An agent with elegantly integrated tools and long term memories

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6. Advanced Tips and Tricks

• Streaming Responses: Want your Worker to respond in a more dynamic fashion? Use the _stream_response method to get results token by token.
• Human-in-the-Loop: By setting human_in_the_loop to True, you can involve a human in the decision-making process, ensuring the best results.

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7. Handling Errors: Because We All Slip Up Sometimes

Your Worker is designed to be robust. But if it ever encounters a hiccup, it's equipped to let you know. Error messages are crafted to be informative, guiding you on the next steps.

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8. Beyond the Basics: Advanced Features and Customization

• Custom Tools: Want to expand the Worker's toolkit? Use the external_tools parameter to integrate your custom tools.
• Memory Customization: You can tweak the Worker's memory settings, ensuring it remembers what's crucial for your tasks.

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9. Conclusion: Taking Your Knowledge Forward

Congratulations! You’re now well-equipped to harness the power of the Worker from Swarms. As you venture further, remember: the possibilities are endless, and with the Worker by your side, there’s no task too big!

Happy Coding and Exploring! 🚀🎉

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Note: This guide provides a stepping stone to the vast capabilities of the Worker. Dive into the official documentation for a deeper understanding and stay updated with the latest features.

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