CrewAI Tutorial - Next Generation AI Agent Teams (Fully Local)

CrewAI helps you build incredible AI agent teams with a focus on giving them tools, delegation powers, and more.

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Links:

Chapters
00:00 - Introduction to Crew AI and its Features
01:10 - Setting Up Crew AI with GP4 and a Local Model
02:05 - Importing and Configuring Crew AI Components
03:15 - Creating Agent Teams for Specific Tasks
04:23 - Assigning and Managing Tasks for Agents
06:02 - Instantiating and Running the Crew
07:08 - Demonstrating Crew AI in Action
08:04 - Integrating Local Models with Crew AI
09:12 - Advanced Configuration with Local Models
10:19 - Preview of Upcoming Features and Tutorials

Thanks to @warezit for the chapters!

[matthew_berman]

Part 2 coming soon, what should I cover in the intermediate/advanced video?

[chookady]

Was wondering when you were going to cover CrewAI. Seen a lot of unhelpful content around this and things that complicate it more than necessary so this was an absolute breath of fresh air! Love the content and the way you approach explaining these concepts!

[AncientSlugThrower]

A locally run autogpt framework is exactly what I was looking for. Great video!

[DavidApiddy]

By far the best crewai tutorial out there. Always love your tutorial vids man! Would love to see one that looks up information solely based on a file on a google drive and/or from a vector db that it creates from those files. Thanks Matt!

[NOTNOTJON]

Awesomesauce!

Would love to see in the advanced video a usecase where an agent creates a task list of 5 items to do surrounding a subject.

You mentioned tools so hoping to see how those are defined, instanciated, and executed. Particularly interested in web-scraping recent news so that the models aren't limited to just their pre-trained info.

I can certainly see how someone could use this to build, IN HOURS, a tool that scraps web content to create new training data for custom agents.

[GregoryMcCarthy]

Hey Matthew! I just wanted to say I love your channel and it’s been so helpful. I love the content you cover, especially how you always keep us up to date with these open source models and show us how to use them! Your tutorials are really easy to follow and your videos are always edited so well! Keep up the great work and wishing you the best start to the new year! 🎉🎉🎉

[johnt]

Your timing is perfect Matthew! THANK YOU!! 😍I was struggling with some AI coding and was looking for a new way to run AI agents locally. And the GPT4 API costs are painful. 😅

[danberm]

Totally up for watching you move forward here. What a great setup!

Would be interested in seeing you implement MemGPT in this framework.

[JohnLewis-old]

This is great! Thank you so much for doing this.

[MeinDeutschkurs]

I‘m excited as well. Can‘t wait for the next one!

[plumbo]

hello Matt... thanks for teaching me so much. God bless you man

[elleryleungnews]

This is actually informative and useful, and it is easy to use. Thank you and subscribed. Looking forward to the next one.

[renierdelacruz]

Thanks very much for such a great video Matt

[sv_c]

Great step by step tutorial Matthew! Already watched 1 and 2hr videos on this, but apparently only needed 10 mins 🚀

[saintsscholars]

Hi Matthew, maybe a research topic and use case in itself would be to rank or assess the various open source models that are available in a multi agent framework so that the user could know which models there are and the optimal settings needed to get the best ones for the task at hand.

[zzz_ttt_]

Create a software development team that can make a chess program based on the requirements ["a simple ASCII chess game in python for 2 players"]. You can create an Architect => create Design Spec => a Team Lead => create Developer Tasks => Developers solving Tasks => Validator reviewing code => Developer Who Fixes Review Findings => finished Python code ...

[adamgdev]

Great video! Stoked to see the next one on CrewAi. Would love to see a comparison video on CrewAi and AutoGen, Pros and Cons and use cases.

[Diego_UG]

It would be great to see an example of managing actions in the style of gpt pilot, something more controlled, that the agents take an idea, generate a user story, create a technical task, execute it by programming in a file, and if something goes wrong or changes these can ask the user for feedback information

[NightSpyderTech]

Great Video. Would love to see your take on a researcher that searches the web based on a topic/criteria, reviews the results, continues to searach if not enough quality infromation has been gathered and then returns a formated summary of the results. For example, researching local solar providers, market value of a product, comparing local or online services or even searching for the best current llm based on need, like local only agent, uncensored, coding, math, etc.

[armans]

Really nice, thank you. In addition, please consider diving deeper into the trade offs between this and AutoGen. I’m assuming it’s more than just being able to use local and different LLMs.