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:
CrewAI - github.com/joaomdmoura/crewAI
Ollama Guide - • Using Ollama To Build ...
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?

[@leandrogoethals6599]

Some ideas: 1.webscraper for news and putting all output in a nice html 2.like u said for stock data would be cool but are u gonna process any sentiment of that data to give a rapport? 3.a coding team for a full-stack application 4.a coding team where one will analyze an existing codebase and one for migration/new features 5.a frontend team to make beautyfull websites where one will focus on html/css and the other more for javascript maybe? 6.An accountancy team where one is for checking state rules/taxes and the other for handling incoming receipts(ok maybe a bit to advanced) Matthew are u planning to make a course of this? i would give money for that

[@theh1ve]

It would be fantastic to see it do a literature review, and even better if it can pull it off using local models. I really think this would be an awesome use case!

[@ronaldbrinkerink7862]

Hi Matthew, thanks for the intro. I would like you to show how to integrate the tools (via langchain) using llamaindex so we can integrate a RAG tool. Furthermore is there an option to save a Crew and/or the execution? The progress and the result should be communicated to the user, so would langchains callback functionality be the way to go? Furthermore the new Builder functionality in autogen seems promising. All new developments are really promising but at some point in time we need to make a decision on what opensource platform to use... Thank you

[@jtjames79]

Can you make an ancient that will make and delete agents as necessary. Basically a human resources agent. And also a headhunter agent to find the best AI models for the human resources agent to choose from. Etc. etc. etc. Now I'm wondering how hard it would be to implement a full corporation.

[@sirrobinofloxley7156]

Advanced: Translate video speech to text from at least 3 different language sources to compare news reports about same story from different countries. Then, set up a dedicated webpage to blog about the findings as to whether the reports tally, contradict and an estimation as to which report is more true and correct. Keep updating the blog as the story unfolds.

[@zzz_ttt_0091]

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 ...

[@chookady222]

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!

[@matthew_berman]

Thanks!

[@danielsotelo5281]

Please make another video on this. Your videos are great

[@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!

[@GregoryMcCarthy123]

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! 🎉🎉🎉

[@matthew_berman]

Much appreciated!

[@AncientSlugThrower]

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

[@warezit]

🎯 Key Takeaways for quick navigation: 00:00 🖥️ *Introduction to Crew AI and its Features* - Overview of Crew AI as an open-source alternative to Autogen. - Highlights of native support for Lang chain and ease of installation. 01:10 💻 *Setting Up Crew AI with GP4 and a Local Model* - Demonstrating installation and setup of Crew AI. - Introduction to role-based agent design and task delegation features. 02:05 🔑 *Importing and Configuring Crew AI Components* - Step-by-step guide to import necessary libraries and set API keys. - Instructions on setting up agents with specific roles and tasks. 03:15 🤖 *Creating Agent Teams for Specific Tasks* - Creating a team of agents for research and blogging about AI trends. - Explanation of assigning roles, goals, and allowing delegation. 04:23 ✍️ *Assigning and Managing Tasks for Agents* - Process of assigning specific tasks to researcher and writer agents. - Details on creating compelling content based on AI trends. 06:02 🧩 *Instantiating and Running the Crew* - Steps to instantiate the crew with agents and tasks. - Execution process using sequential task completion. 07:08 🚀 *Demonstrating Crew AI in Action* - Live demonstration of Crew AI performing assigned tasks. - Observations on the efficiency of the task execution process. 08:04 🌐 *Integrating Local Models with Crew AI* - How to use local models like Open Hermes with Crew AI. - Guidance on downloading and setting up alternative models. 09:12 ⚙️ *Advanced Configuration with Local Models* - Detailed instructions for configuring agents with local models. - Tips for optimizing settings for best performance. 10:19 📅 *Preview of Upcoming Features and Tutorials* - Tease of future sophisticated use cases and tutorials. - Invitation for audience engagement and suggestions for follow-up content. Made with HARPA AI

[@danberm1755]

Totally up for watching you move forward here. What a great setup! Would be interested in seeing you implement MemGPT in this framework.

[@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.

[@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!

[@elleryleungnews]

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

[@plumbo624]

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

[@johnt2491]

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. 😅

[@renierdelacruz4652]

Thanks very much for such a great video Matt

[@SkyJensen]

I wish you would do two video types, one for the masses for the scope of the field and deeper, more challenging setups. I’d pay a decent amount for in depth tutorials

[@matthew_berman]

More advanced video is coming soon. I’m launching paid courses soon.

[@ajarivas72]

@@matthew_berman I too look forward to those courses

[@saintsscholars8231]

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.

[@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.

[@successahead5598]

your the first one to talk sense this year

[@kokoabassplayer]

Simply awesome, I love your content.

[@HistoryIsAbsurd]

Thanks for your help got it up and working now on my windows machine and now im eagerly waiting for the next !

[@aladinmovies]

You are helping in trying AI. Thanks Matthew!

[@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

[@sucharandomusername]

It's like DJ Khaled is in the house. Another one!

[@JamesLee-lf4fr]

Pls make part 2, looking forward to it. Thanks for the good work.

[@armans4494]

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.

[@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.

[@streetcrypto1218]

man this is crisp! great videos

[@jobautomation]

Best content creator so far

[@vishnunallani]

Liked, subscribed and sent a Thanks contribution. You are amazing. Thank you!

[@user-sx8sv5yv4i]

Something cool to see is how CrewAI can help overcome some of the issues RAG pipelines run into. For example, I've been creating various apps that heavily leverage the a RAG pipeline using many different embedding models (cohere, OpenAI, Google), many different vector stores (local and cloud), and many LLMs. The issue I have constantly is successfully getting the LLM to answer with information that is passed to it, which would be Context if you're using LangChain as-well-as making sure the embeddings are being queried correctly. Hard to get into the weeds over a comment. Looking forward to more content!

[@user-hg7pv7ol4l]

can you give any examples of the LLM hallucinating even with text context in the prompt? I've had different RAG pipelines, but the issue that I think you're describing sounds fixable through prompt updates like "only use the information given above"

[@youri655]

Great video again🙌

[@electiangelus]

I like it, getting closer.

[@jorcelangelo]

I cannot wait for the part 2 video

[@aimademerich]

Would love to see some use cases with Stable Diffusion or any generative art!! Graphic designers need love too haha

[@sirrobinofloxley7156]

30 seconds in and I'm already blown away.... Look out of the window rn, that's me orbiting the stratosphere

[@Christopher_Tron]

So excited for part 2!!!!!! Maybe do a intermediate and then an advance video PT2 and PT3 given that new features will probably come up between the uploads

[@nexuslux]

So excited for the v2 advanced video with Langchain!

[@tribat68]

Excellent video. I’m very interested in a trip planner one so I can convince my travel planner wife that AI isn’t just hype.

[@fabriai]

It would be great to achieve the task of copywriting conversational experience text for non autonomous agents (old fashioned chat bots). That task is usually labor intensive and done by copywriters who implement specific personality traits for the chat bot, which are defined by the Conversational Designer based on client’s business goals.

[@lovelyn7324]

great video, good information density

[@dsamh]

By making this information available and accessible, you are doing so much more for humanity than we realize. The people making these models and advancing the tech IN THE OPEN are heroes. We need to be HYPER aware of control and regulation and scary stories they'll use to achieve it.

[@somebody-anonymous]

They are definitely going to produce some scary stories, be wary of the blog posts the machines will be writing as they take control

[@cheyno237]

Yeah, sorry, disagree. They'll put half the population out of work in the next 10 years

[@RomalPecciaAudioSoftware]

@@somebody-anonymous lol every article that comes up on google these days is some AI-SEO-optimized garbage. They've taken control before they've even gained sentience

[@spars2425]

Hey Mathew, once again thanks for these cool updates. I have one suggestion. I believe in general, it would be helpful if we would have an extra level deeper on the new tools you mention, especially when they are open source and we can look into their codes. For instance, for me who started coding as hobby 2 months ago, I see now the question is about limitations, control, ease/possibility of migration. So when you introduce a tool like this one, and not a Botexpress category, someone like me who cant easily grasp the code behind, could really benefit from a brief insight from a senior developer with great teaching skills like you! 😍

[@Ak_Seeker]

So exited to try this

[@josephboomtv7811]

Thanks for your work, it seems extremely complicated for something as simple as a blog post.. man

[@ylazerson]

Great video - thanks!

[@DonGatoGuzman]

Hey! I would love to see data processing and analysis. It would also be nice to undersand if there can also be user input, like autogen.

[@thelalomorales]

just answered my own question with this video, matt you rule.

[@rio_rio]

Matthew, thanks for the informative video! I would love to see one about creating a team of agents for generating automation tests. One agent analyzes a target website and summarizes its specifications. The second agent creates automation test source code using Selenium, for instance. The third agent reviews the code and provides feedback to agent #2.

[@metonoma]

a helpful tool could be using another model to format your goals into this prompt format. As a non programmer it's easy to forget details and sequence. A simple version could be a Google form where you fill in the steps in the right order and then add syntax with pre-filled questions

[@sausage4mash]

just got this working i created a front end html guy to output a html ready page , i was quite shocked it worked !

[@restrollar8548]

Great video as usual! Using Google search integrated within this and using memory (e.g. ChromDB) would be great to see.

[@__--JY-Moe--__]

thanks Matthew!! U'r like the geeky older Brother I never had!!

[@subx0ne]

I would love to see use cases for this being new to the concept. The development seems straight forward but it would be good to get examples.

[@WenRolland]

Great video! I'd love for you to show other ways to use local models like through LM Studio or GPT4all.

[@blackswann9555]

Excellent!

[@Videos-xf2vf]

Thank you for the tutorial. It would help to get detailed explanation on most frequently used options. I got it somewhat working (using the tutorial and local LLM). Here is the output I got when using nous-hermes-llama2-13b.Q4_0. Indeed it required some finetuning of the parameters. "The rise of AI technology has brought about major changes in the way we live and work. From chatbots that help us find information to autonomous vehicles that transport us safely, AI has become an essential part of our daily lives. As the technology continues to evolve, we can expect even more innovations that will change the way we interact with the world around us."

[@dasistdiewahrheit9585]

7:28 I don't get it. Where exactly does the pass happen? Just by writing the tasks in that specific order into an array? How would we specify to which agent to pass results if there are more agents?

[@lasagnadipalude8939]

I really want to see a project for really scraping the internet discerning truthful information, understanding bias, ecc. to create a repository of classified information. I imagine something like that used by future models to make their own mental representation of the world, but for less long term i'd love something like that in my phone/pc, part of a loop in my personal local ai assistant

[@ThuggishworldgangMusic]

Great stuff

[@user-pw1bn1yn9i]

Google Gemini embedded your video link in its response. That's how I discovered you. Great video

[@150nitrodude]

Would really love to see more on the 'tools' agents can use. For instance, what it would look like to integrate the twilio api and send a text, or even coordinate a text conversation that would gather several points of info from the agent texting a person; and bring that back to another agent.

[@RoniBliss]

Yes +1 on this, any way we can intergrate API for input and response for app production!

[@greatsarmad5147]

THis is a great video! For next time I hope you would show us how to make a finance crew looking at stocks and if they can also sentiment analysis. The cream dela cream would be also to make a crew that can do market research. Thank you again for all you work! Cheers!

[@user-ln5is8ig7i]

00:02 CrewAI is an open source alternative to autogen for setting up agent teams. 01:23 Tutorial on using CrewAI and Monster API for complex AI tasks 02:45 Get OpenAI API key and define AI agents 03:58 Crew AI allows control over delegation, unlike Autogen 05:21 Defining agents for specific tasks is easier with CrewAI than Autogen 06:50 Crew AI allows easy chaining of tasks and agent delegation. 08:09 Using a local model with CrewAI 09:32 Using local models for AI agents Crafted by Merlin AI.

[@letsplaionline]

Thank you!

[@CyberSQUID9000]

App tools will be very useful

[@EduardsRuzga]

I would love to see it solving more complex cases. Finding contacts at companies in some industry related to product description. Like I have a company witht product and want yo expand in to new area and want to see whos who.

[@gregkostello2028]

Thanks!

[@sperazza]

I havent wanted to see a followup you tube video so badly :)

[@artur50]

Fantastic! 🎉

[@luka1790]

Book writing would be cool!

[@missoats8731]

I second that!

[@user-pf5fo1xs1q]

yes more like this

[@dorothyban5102]

Thanks Matt this is awesome! it has more clear role to set for each agent. I am wondering how to set up an agent-like what we did as proxy agent in AutoGen-that can ask human input/confirm? hope you can show how to do this in next clip. can't wait to see! Cheers

[@PhumlaniMahlangu]

One of the most exciting videos. I would like to know if this tools can write files locally.

[@harisjaved1379]

Hi Matt this is great! Can we use this with RAG and our own documents? Thanks man!

[@Meta-Gnome]

I would love to see something with Image/Videos being Prompted and Generated after the Script is Created, Streamline a Content Creation Agent! Seems like were getting Close to it!

[@cirencesterful]

It would be great to see a specialized webscraping agent example. I use Appify for things like that, but I can see an agent delegating the gathering of data for analysis in another task. For example, a car research agent can delegate collecting ratings on new cars coming out from a specific website. Separation of research and data gathering would allow more reusability.

[@Paul_Marek]

Great overview and quick examples. Exciting stuff. Could this be used with memGPT to create a persistent personal assistant for an individual, on mobile?

[@EitanbAi]

Thanks dude

[@brentpope1497]

Would be very helpful to have a guide to your setup on your machine to run this. I didn't have vs code, c++, python, or any of the other requirements installed. I used to program in VS but it's been years and python is a new thing for me so a short tutorial on setting up your environment would have been great. Maybe you could do a separate video on just that and mention it with a link at the beginning of your instructional videos.

[@GeobotPY]

Would love to see financial use cases - stock analysis or something like that

[@zainzafar3131]

Would appreciate if we can create a meeting crew. One for taking notes, one for researching attendees, one for summarising etc

[@brianhansen6481]

I already got as far as you did here on my own. I am struggling getting the team to write meaningful code to files in the workdir. If i task it to generate a rest API in python / C#. It would be neat if i could test it afterwards. And maybe task it to review and correct its mistakes... aka do my job for me x) love your channel btw, appreciate what you do.

[@frankbradford2869]

Other then that I am can't wait to see this run.

[@SwiftyGifts]

I'd love to see a tutorial on how to use with mistral locally ( I'm on Windows, so no Ollama).

[@aimademerich]

Phenomenal

[@user-en4ek6xt6w]

Actually you can define the crew and then make gpt define the task and the agent dedicate for each task automaticly, i don't know if that would be helpfull but i think you can make some cool thing with this

[@davidapk323]

amazing 😍😍

[@metonoma]

what would be awesome is a crew that researches github and builds local pipelines from different code bases

[@dannyvfilms]

This seems really neat! I’ve had an idea for an email/calendar app I’ve wanted to make and this seems like it could be approachable. I’d love to see how you can structure more complex org charts: Director - 3 Supervisors - 1 or more Coordinators each -- 1 or more agents supervised by the coordinator My example might be too much for a video but this gives you an idea where I’m going if you want to play with a different complex org for your own demo: 1. Director of Email and Calendar Management gpt4 1. Schedule Supervisor gpt3.5 1. Calendar Coordinator gpt3.5 2. Communications Supervisor gpt4 1. Analysis Coordinator gpt3.5 1. Lead Analyst gpt3.5 2. Lead Summarizer gpt3.5 2. Editing Coordinator gpt3.5 1. Lead Copywriter gpt3.5 3. Research Coordinator gpt4 1. Lead Researcher gpt3.5 3. Development Supervisor gpt4 1. Development Coordinator gpt3.5 2. Documentation Coordinator gpt3.5

[@thenext9537]

You can do it. Use gpt and break out the starting points and be specific. One first one works, move on. I do a lot of api calls, and brought gpt4all locally with all the datasets (commercial, non commercial). Build out front ends in python (which ai can build), etc. Yea, it’s a deeeeeeeeep hole but you must start at the tippy top to get it going and build out. Might have to restart several times too as things get to a “I didn’t see the consequences of this earlier action”. Fun!

[@Piotr_Sikora]

Greate job! BTW, what is best open source model to run local with langchain tools?

[@vishnunallani]

Thanks

[@matthew_berman]

Thank you!!

[@yex666]

Yes!! 🎉🎉

[@jrpc0]

Like many, finding the connection between the theoretical blogs and the practical seems harder that it should be, but you are a clear bridge across that gap. Thank you for sharing your knowledge in such an engaging and accessible way. One question I have is why do you have agent and I need to put specifically openhermes as the model name? Is it due to multiple models being installed with Ollama?

[@PrometheusLux]

Thank you so much for this tutorial, it helped me to find an entry into this topic. If I can just remark one change to consider: The os.environ should be used with an .env file (created in the project folder) which contains your API_KEY. The key should not be typed directly into the code.

[@matthew_berman]

Thanks! Check out my latest video where I build something at length with crewAI

[@PIOT23]

@matthewberman what’s your take on crew ai performance vs prompt chaining performance via openai assistant APIs? I’m building a solution changing a few asstapi agents together, but this crew ai looks very interesting!

[@DanInVirtualReality]

Would love to see if and how a teachable agent (like the one in autogen) could be implemented

[@vbywrde]

This is great. Thanks! Just wondering... I'm on windows and using LM Studio instead of Ollama (I could use ollama with WSL, I know, but I'm tring to keep the number of components involved to the minimum I can at this point, though maybe Ollama has enough benefits to make it worth using WSL for). Wondering... do you happen to know, though, if there's a way to use LM Studio to host multiple local models? My first thought was... run multiple instances of LM Studio and just use two different ports. But ... maybe there's a better way, or does that not even work? Anyway, thanks Matthew! Great video series!

[@limeraghu579]

This is great , how about one agent reading csv file and other agent reading a pdf file etc , is it doable??

[@cesarromero936]

Awesome! It would be great to use Langchain with agents that are using specific datasets and searching the internet. Keep up with the great work! e/acc