The RIGHT WAY To Build AI Agents with CrewAI (BONUS - 100% Local)

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AI Summary

Video Summary: Optimal Crew AI Team Setup

Introduction

• The video demonstrates setting up a Crew AI team using Lightning AI.
• The setup is based on guidance from the Crew AI founder.
• The video is sponsored by Lightning AI.

Lightning AI Features

• Cloud-based code editor for collaboration.
• Can power open-source models.
• Provides a fresh Python environment each time.

Setting Up Crew AI

1. Create a new studio in Lightning AI.
2. Sign up for Lightning AI and receive free credits.
3. Build the Crew AI code framework:
   • Create a source folder.
   • Name the new crew (e.g., Financial Analyst Crew).
   • Create a config folder for task and agent definitions using YAML.
   • Define tasks and agents in separate YAML files.
   • Structure the crew to be modular, with a short main.py file.

Task and Agent Definitions

• Define tasks such as researching a company and analyzing financial data.
• Create agent definitions with roles, goals, and backstories.
• Set up agents to not delegate tasks and to be verbose in output.

Main File and Environment

• Import necessary libraries and create a crew base class.
• Define agents and tasks within the class.
• Set up the main.py file to run the crew.
• Use poetry to manage dependencies and run the project.

Using Open-Source Models

• The video shows how to power the crew with an open-source model using Lightning AI GPUs.
• Demonstrates setting up an API endpoint with Lightning AI to use with the crew.

Conclusion

• The video concludes with a successful demonstration of the crew running tasks powered by an open-source model.
• The setup is confirmed to work with the model running on Lightning AI GPUs.
• The video encourages likes and subscriptions for more content.