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Wait...how do you know about my uncle!

Great Video!

Helped a lot ! Thanks :)

Hi, very nice tutorial, would you do a follow up to show can the data can be passed across agents ?

Nice shirt (and video too) ❤🎉

Big fan Would love to work with you Please give job 🙏🏻

Omg I am a huge fan of you 🎉🎉 ur whole videos are something else to define ...

acting acting acting so you communicate in real life like this?

if you do less acting and focus more on content.

Great breakdown of agent design patterns and yet its so fun to watch! 😀

Hey, Can you suggest some courses and resources to master the concept. I am in final year B. Tech and this is what I want to pursue further. Also tell what are the future career prospects in Agentic AI?

Absolutely LOVED the video! Super informative and had me hooked from start to finish. The visuals were on point-especially that planner agent giving some serious Optimus Prime vibes 😎. Oh, and FYI, already liked, shared, and hit that subscribe button! Can’t wait for the next one to dive even deeper into this awesomeness!

This is soo very intuitive!!

Amazing!

I need part 2!!

Can you share guide on how can we pass a excel file as input for this?

I am trying to run it in vscode and keep getting the following error: "AttributeError: 'tuple' object has no attribute 'encode'"

YOU ARE MY TECH BUD IN REAL LIFE great video

This channel would be big in coming years ❤

Hi, great video! Wanted to know how is this more reliable or resilient than using vanilla Prometheus query in keda, especially in case of spikes?

Worth to mention: "As 2023 winds down, we're also bidding goodbye to an important part of Dagger history: the Dagger CUE SDK." So no more CUE with Dagger. Which perhaps simplifies the things...

thanks, was good apart from cold jokes!

This video did what a week of reading didn't. Thank you, amazing, didactic, right to the point and simple.

As k8s follow declarative and it continuous monitor desired state. then if any pod goes down, k8s recreates pod again and it maintains the desired state, in this way, auto healing.

Hey man. Good videos. You should make one on Hashicorp Nomad. Seems everybody is running behind k8s and it is overkill for most cases. New and early stage startups would benefit from a Nomad tutorial.

Finally a good explanation that is well put together and not boring as hell

Simple and clear. That's what exactly i needed. Please do come up with short videos , with clear information. super helpful

Fantastic!!

I loved the enthusiasm! absolute amaaaazing video mate!!! Thanks for that!

Very clear.... And To the point... This was awesome... Loved it........ And To the point... This was awesome... Loved it....

damm this was really good explaination

I am trying to run this with lm studio instead of Ollama and the model just generates text instead of running the function. Maybe autogen changed something since this video got out?

Dude this is REALLY good. Well done & thank you 👏🏽

well done, very underrated content

Thanks for this video. It's readlly great. I would love to see a video about how to get the output from Autogen into a webapp, including the human input. Would great. Thanks

Is there a possibility to run an "Autogen Inference Server" with an API? I think that could be really powerful.

Great video and you should definetly do more please. I have a question! how good is mistral 7b at function calling? is it as accurate as openai function calling?

There are a LOT of channels offering ~10 minute videos diving into the most recent and powerful LLM frameworks... most offering far less impactful examples (often minimal transformations of tutorials published in the repositories themselves), with far less clear explanations, with far less fluency both in the code and their walkthroughs. Your presentation style is clear, concise, and dense, yet friendly and approachable :) And using Kubernetes as an example, built on top of local LLM (including explanations as to the how and why) are not only practical, but help illustrate the range of use cases beyond yet another sqlite+gpt-4 "research agent swarm!" video. Keep up the great work! You're going to rise to the top of these in no time!!!

y ouare the best you are the best you are the best. best autogen tutorial creator out there easily

Thanks for explaining AutoGen!

Do you have a specific requirements .yml file for the conda environment you say to setup in step 1 of you "Setup conda env" or can i just create a blank one?

🎯 Key Takeaways for quick navigation: 00:00 🤖 *[Introduction and Restrictions]* - Setting the stage for using Oren to create AI-powered applications. - Three self-imposed restrictions: Open-source models only, code explanation in detail, and ensuring replicability in viewers' projects. - Emphasizing the commitment to using open-source models contrary to common beliefs. 02:30 🛠️ *[Building External System Adapter]* - Creating an instance of an external system adapter for Kubernetes. - Explaining the structure of the adapter class and its get resources method. - Discussing the flexibility of the method parameters and the use of AI to determine values. 04:19 🌐 *[Configuring Autogen for Kubernetes]* - Configuring Autogen for AI-powered interaction with Kubernetes. - Setting up the llama CPP inference server for better performance. - Adjusting parameters like cache, response timeout, and temperature for optimal AI responses. 06:25 🤝 *[Agent Coordination and Workflow]* - Introducing the Kubernetes engineer agent responsible for calling the function. - Describing the role of the kubernetes expert agent in researching values. - Explaining the user proxy agent as a substitute for human input and the group chat manager for agent coordination. 07:35 🔄 *[Agent Coordination Workflow]* - Detailing the workflow of agents' coordination in Autogen. - Explaining how the group chat manager orchestrates the conversation between agents. - Highlighting the role-playing game analogy used for model decision-making. 09:36 🤔 *[Testing the Multi-Agent System]* - Demonstrating the interaction and coordination of agents in action. - Checking the logs for successful execution and agent collaboration. - Acknowledging the efficiency of the agents in working as a team for the intended task. Made with HARPA AI

this is legit the best video explaining how autogen works, and i also love that you use local models. keep on doing amazing things. I would like to see what other real world use cases are there for the different types of agents

i know this channel's gonna become huge so i wanna be some of the guys that started following from the start❤

Cc amazing video ❤, excited for series

This is very interesting!!

Great video subscribed to your channel for more great info. If im not misunderstanding this, we can actually write pipelines and call them write in the source code using the sdk. Which is a gamechanger. Maybe im wrong about it but if not, changes completely the way we do devops.

2023: npx prisma migrate dev / npx prisma migrate diff --from-url X

Amazing use case

Nice