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Excellent video. Gonna experiment with this for other document types..

Can you please tell what to change in deeplake path as it is showing InvalidTokenException: Token is invalid. Make sure the full token string is included and try again.

I'm getting this error InvalidTokenException: Token is invalid. Make sure the full token string is included and try again. please help to solve this

but how to make a bot which will review all sort of codes after taking this as input?

Thanks for walking us through a useful multi-agent scenario in a way that is easy to follow. More CrewAI and AutoGen content please.

This is awesome Priya, exactly what I want to build next. Ive been interested in CrewAI but I didnt realize it had this pipelining capability, some of the other multi-agent frameworks can only handle the control flow for moderately complex tasks and need for the dev to define the overarching control flow across tasks, this looks like just what Ive been looking for, but there are so many tools out there not enough time in the day to try them all so I am grateful to you for putting this together, will like/share/subscribe!

Let's go!! this is amazing~ thank you!

This stopped running and all the codes and blogs related to understanding codebases with langchain have been removed, what's going on?

Legit information thanks for sharing I’m going to play around with your repo I was literally thinking of building this exact application and it looks like you’ve built it better than I could. I’ve subscribed looking forward to more of your content.

Great content Priya. Thanks for your efforts!

🤣 P R O M O S M

Good Priya...please do go on creating multi agents...

Great video! A quick question - Noticed that the number of tokens was about 30k after removing the refrences. However the size of the tokens used in the langchain call was about 10k. How did it go from 30k to 10k? Thank you!

Keep up the good videos:) Subscribed

🎯 Key Takeaways for quick navigation: 00:14 🤖 MetaGPT is a recent development that uses chatbots to create a multi-agent environment for collaborative tasks, including building software and forecasting models. 02:04 🧠 Clear personas, standardized outputs, and a shared messaging platform are used in MetaGPT to prevent agents from producing incorrect or erratic results. 03:00 ⚙️ Setting up MetaGPT involves installing a JavaScript package and configuring a YAML file with OpenAI and server API keys. 05:03 🎮 MetaGPT can be instructed to build complex applications, such as a tic-tac-toe game controlled via a command-line interface. 06:27 📝 MetaGPT not only generates code but also provides detailed documentation, making it useful for both designing and implementing software. 08:03 ⏲️ MetaGPT can be used for machine learning tasks, such as building time series forecasting models, with generated code as a starting point. 10:01 📈 While MetaGPT provides a good starting point, users may need to make small adjustments to the generated code for specific requirements. Made with HARPA AI

the same/similar examples given by AI RUclips content creators - you could have done differently by at least taking simple student-level projects.

This is helpful, Thanks Priya!

Thanks for sharing!

That's a wonderful demo @priya-dwivedi👏. It is interesting and exciting to see how Gen AI is evolving so rapidly. Apparently, the research into Gen AI is also seeing a large growth nowadays, even expanding on the multi-modalities front. It makes me wonder how soon we are going to see a model or architecture powerful and accessible as stable-diffusion that can generate films or videos fluidly based on a script or a series of prompts 😄.