AutoGen RAG: How I Created AI Agents and gave them Second Brain?

🚀 Welcome to our deep dive into Retrieval-Augmented Generation (RAG) and its transformative impact on AI's ability to process and utilize vast amounts of data. In this video, we unveil the secrets behind equipping your AI with a "second brain," enabling it to retrieve and utilize context for more accurate responses. 🧠✨

*If you like this video:*

🔍 What you'll learn:
The basics of RAG and how it empowers AI with enhanced data handling.
Step-by-step guide to implementing RAG in your projects using PyAutogen, RetrieveChat, and Flaml AutoML.
Six essential examples demonstrating RAG's capabilities in generating code, answering questions with and without human feedback, and tackling complex queries using multihop questions.
Practical insights into setting up your environment, managing API keys, and configuring RAG components for optimal performance.

👩‍💻 Who this is for:
AI enthusiasts looking to elevate their projects with advanced data retrieval techniques.
Developers seeking to integrate sophisticated AI features into their applications.
Anyone curious about the future of AI and its evolving capabilities.

📌 Timestamps:
0:00 - Introduction to RAG and its Importance
0:25 - What is RAG? An Overview
1:00 - Setting Up Your RAG Environment
2:00 - Implementing RAG: First Steps
4:00 - Examples: Code Generation and Q&A with RAG
7:00 - Advanced Techniques: Human Feedback and Multihop Questions
11:00 - Conclusion and What's Next

🔗 Resources and Documentation:

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[theaiffice]

Wow. You explained everything so clearly, but I'll need to watch that again to understand it.

[jorgerios]

Nice video thanks, Would you show in the future how to create agents with multimodal RAG using both OpenAI and open source LLM's?

[walberc]

Very good video. This is really amazing

[ilianos]

🎯 Key Takeaways for quick navigation:

00:00 🤖 *Introduction to AutoGen RAG*
- Introduction to Retrieval-Augmented Generation (RAG).
00:55 🧠 *Understanding AutoGen RAG Concepts*
- Overview of AutoGen RAG and its components: RAG User Proxy, Retrieval-Augmented Assistant.
- Explanation of how AI agents utilize context retrieved from a second brain to enhance query responses.
02:03 🔧 *Implementation Steps for AutoGen RAG*
- Steps to implement AutoGen RAG in code, including installing required packages and setting up configuration files.
04:08 ⌨️ *Generating Code with and without Human Feedback*
- Generating code based on documentation both with and without human intervention for feedback.
- Initiating chat interactions between the RAG user proxy agent and the assistant agent.
05:40 🔄 *Utilizing Human Feedback in AutoGen RAG*
- Demonstrating the process of generating code and answering questions with human intervention for feedback.
07:31 📚 *Implementing Question-Answering with Natural Language Processing*
- Loading natural language question-answer data and storing it in embeddings for retrieval.
- Running queries on the stored data to demonstrate question-answering functionality.
09:33 📚 *Advanced Application of AutoGen RAG: Multihop Question Answering*
- Implementing multihop question-answering functionality using a large dataset.
- Demonstrating how AutoGen RAG can handle complex, multistep queries.

Made with HARPA AI

[rakesh]

can we use gpt-3.5 model ?? will it get desired output?

[NotesandPens-rowx]

Would you also please make a video how to deploy these models on any website or make a package for it ?

[ruxunwagn]

what if I am retrieving based on a SQL database or search engine? longchain: : embedding_vector =
docs =
print(docs[0].page_content) but your cannot serch like this

[trsd]

Very cool video! But I've to admit, that I it was a little bit to difficult for me as a beginner.

[erikwan]

Do u mind something similar using local model like mistral? Thanks

[mannya]

Going to start a new project, which framework do you recommend? CrewAI or Autogen

[nexuslux]

Feels a little like how PHI data project has implemented their version of Autonomous RAG

[bdjblng]

How much compute is required to create a vector database locally? Is a GPU required or can it be done on the CPU. How long would it take for let's say a 100 page document?

[svb]

what if I am retrieving based on a SQL database or search engine?

[mrd]

A pretty GUI on this would be amazing.

[shaktirajsinhzala]

Nice, I am using this RAG but with local model, but it is not getting that model and uses another model (maybe default one, named cl100k_base). I want to use my locally deployed Mistral-7b in using RAG assistant.

can you please help me through this one.

[planplay]

What will be the performance in financial multi-table data?

[adamchan]

Is it possible to have a tutorial for crewai too ?

[HPSCH]

Very nice and interesting, is there a place where I can download the code

[fintech]

How to do this for video editing/generation

[MarkSze]

I believe this is using a very old version of autogen, well before 2024. It won't run as is.