- Видео 19
- Просмотров 11 757
Zahiruddin Tavargere
Индия
Добавлен 17 дек 2022
Welcome to your go-to destination for everything AI Agents!
This channel dives deep into the world of autonomous AI systems, from hands-on tutorials and powerful agent-building techniques to exploring cutting-edge applications across industries.
Here, you’ll learn how to create, deploy, and optimize AI agents for real-world use cases.
Whether you're a developer eager to level up your skills or an enthusiast curious about the latest in AI, we break down complex topics into engaging, accessible content.
Join us as we explore the frontier of AI-driven automation, Retrieval-Augmented Generation (RAG), OpenAI Swarm, and more - and build the future of intelligent agents together!
Twitter: zahiruddin_t
Email: zahiruddin.tavargere@gmail.com
Website: adaptiveengineer.com
This channel dives deep into the world of autonomous AI systems, from hands-on tutorials and powerful agent-building techniques to exploring cutting-edge applications across industries.
Here, you’ll learn how to create, deploy, and optimize AI agents for real-world use cases.
Whether you're a developer eager to level up your skills or an enthusiast curious about the latest in AI, we break down complex topics into engaging, accessible content.
Join us as we explore the frontier of AI-driven automation, Retrieval-Augmented Generation (RAG), OpenAI Swarm, and more - and build the future of intelligent agents together!
Twitter: zahiruddin_t
Email: zahiruddin.tavargere@gmail.com
Website: adaptiveengineer.com
Essential Skills for Full Stack Engineers in 2025: Future-Proof Your Career
"Are you ready to stay ahead in the AI revolution? In this video, we break down the essential skills every AI engineer needs in 2025. Whether you're an experienced engineer, a developer transitioning into AI, or just starting your career, this guide is for you.
We’ll explore:
1️⃣ Core AI and ML engineering skills, including LLMs, RAG, and prompt engineering.
2️⃣ The must-know technical stack, from Python frameworks to vector databases.
3️⃣ Professional and project skills like domain expertise, collaboration, and leadership.
Start building your roadmap for success in AI today.
🎯 What are your learning goals for 2025? Share them in the comments!
💡 Like, share, and subscribe for more insights on AI...
We’ll explore:
1️⃣ Core AI and ML engineering skills, including LLMs, RAG, and prompt engineering.
2️⃣ The must-know technical stack, from Python frameworks to vector databases.
3️⃣ Professional and project skills like domain expertise, collaboration, and leadership.
Start building your roadmap for success in AI today.
🎯 What are your learning goals for 2025? Share them in the comments!
💡 Like, share, and subscribe for more insights on AI...
Просмотров: 1
Видео
Mastering Jinja2 Templates is the KEY to Dynamic AI Workflows! | Step-by-step Tutorial
Просмотров 17319 часов назад
Unlock the full potential of Jinja2 templates in your projects! In this tutorial, we dive deep into how to create dynamic templates using Jinja2 for AI workflows, personalized emails, and travel itineraries. Learn the basics, explore practical examples, and see how Jinja2 compares to other tools like LangChain and string interpolation. Perfect for developers, data scientists, and anyone working...
How to Build Price Monitoring Agent with Pydantic AI | Part 2 | Full Tutorial
Просмотров 239День назад
This is a part 2 of the 2-part Pydantic AI-based Price Monitoring System Part 1: ruclips.net/video/hlropi13fO8/видео.html Newsletter: newsletter.adaptiveengineer.com/ Blog: zahere.com/ Connect with me Linkedin: / zahiruddin-tavargere In this step-by-step tutorial, we demonstrate how to create an AI-driven agent that takes a product page URL and extracts product and price information in a struct...
How to Build a Price Monitoring Agent with Pydantic AI | Works with any eCommerce product URL
Просмотров 80014 дней назад
Full Code: github.com/zahere-dev/pydanticai-price-monitoring-agent 🚀 Learn how to build a powerful price monitoring agent using the Pydantic AI framework! This is a part 1 of the 2-part Pydantic AI-based Price Monitoring system Newsletter: newsletter.adaptiveengineer.com/ Blog: zahere.com/ Connect with me Linkedin: / zahiruddin-tavargere In this step-by-step tutorial, we demonstrate how to crea...
You Won't Believe How EASY Coding a Multi-Agent Orchestrator Can Be!
Просмотров 16821 день назад
Code: github.com/zahere-dev/augmate In this comprehensive tutorial, I break down how to build a custom multi-agent orchestration framework from scratch. Learn the complete process of designing, implementing, and scaling your own AI agent system without relying on existing black-box frameworks. Topics covered: - Custom agent framework architecture - Inter-agent communication protocols - Dynamic ...
Why You Need Amazon’s Multi-Agent Orchestrator Now!
Просмотров 1,1 тыс.Месяц назад
Repo: github.com/awslabs/multi-agent-orchestrator Dive into the world of advanced AI interactions with Amazon's Multi-Agent Orchestrator! This powerful framework is designed to effectively manage multiple AI agents, enabling complex and coherent conversations. In this video, we explore the key features of the Multi-Agent Orchestrator, including intelligent intent classification, dual language s...
CrewAI Automation Code Walkthrough | Step-by-Step Email Workflow Tutorial
Просмотров 343Месяц назад
Code: github.com/zahere-dev/email-workflow-automation-using-crewai Asana API: developers.asana.com/docs/overview Gmail API Setup: developers.google.com/gmail/postmaster/quickstart/python Take a deep dive into the code behind CrewAI automation in this detailed walkthrough. In this tutorial, we break down every line of code used to build the AI-powered email workflow. Learn how to set up the Emai...
CrewAI Demo: Automate Gmail, Asana and Database Operations
Просмотров 281Месяц назад
In this video, we dive into an innovative way to manage email workflows using CrewAI agents. Learn how the Email Reader, Parse and Triage, Asana Ops, and DB Ops agents work together to read incoming emails, categorize leads, create tasks, and store information in a database. Whether you're a project manager or business owner, discover how AI-driven task automation can streamline your workflow, ...
Turn Web Scraping Into a Natural Conversation in 12 Minutes | OpenAI Swarm Tutorial
Просмотров 1,4 тыс.Месяц назад
Want to automate data scraping with a twist? In this tutorial, I show you how to use OpenAI's Swarm multi-agent framework to create an intelligent web scraper that you can interact with using natural language. Learn how to set up a conversational scraper agent that can fetch specific data from any website with ease. Whether you're new to agents or looking to expand your AI project toolkit, this...
Can Claude Really Use Computers? We Put It to the Test 😱
Просмотров 1082 месяца назад
Watch as we challenge Anthropic's Claude 3.5 Sonnet with 5 real-world computer tasks in this exclusive test! Claude can now control computers just like humans - moving the cursor, clicking, and typing. While it's currently at 14.9% performance (compared to human's 70-75%), this marks a major milestone in AI development. See how this groundbreaking AI model handles everyday computing challenges ...
How to Create a Blogging Agent Using OpenAI's Swarm in 5 minutes | A Step-by-Step Tutorial
Просмотров 2,4 тыс.2 месяца назад
Code: colab.research.google.com/drive/1phDFUasrZxjChabWo_oWwWuNKwfjuJ_B?usp=sharing GPT Researcher: github.com/assafelovic/gpt-researcher Discover the power of OpenAI Swarm, an innovative open-source framework designed for orchestrating multi-agent systems! Released in October 2024, Swarm allows developers to create and manage networks of AI agents that collaborate seamlessly to tackle complex ...
How Video Games Shaped the Future of AI: The Demis Hassabis Story
Просмотров 4082 месяца назад
Discover the incredible journey of Demis Hassabis, the visionary behind AlphaFold, who drew inspiration from his early passion for video games to revolutionize the world of artificial intelligence. From co-creating the legendary game "Theme Park" to founding DeepMind, Hassabis' love for games fueled his approach to solving the complex problem of protein folding. Learn how his background as a ch...
Precision vs. Context in RAG Query Responses | Parent Document Retrieval (PDR) | Advanced RAG
Просмотров 522 месяца назад
Are you struggling to optimize your Retrieval-Augmented Generation (RAG) system? In this video, we dive deep into the key factors that make or break a successful RAG implementation. Learn how to choose the right chunk size, balance precision with context, and ensure high accuracy in responses for complex, multifaceted queries. We’ll also explore the power of Parent Document Retrieval (PDR) to e...
How This OpenSource Contributor Saved React From Dying | Incredible Story of Sophie Alpert
Просмотров 2,7 тыс.3 месяца назад
In this video, we dive deep into the inspiring story of Sophie Alpert, the engineer who played a critical role in saving ReactJS. From her early days coding in high school to joining the React core team at Facebook, Sophie’s journey is nothing short of remarkable. Learn how her open-source contributions reshaped the future of web development, making React the world’s most popular framework toda...
This Pre-retrieval Optimization Technique in RAG is Awesome | Advanced RAG Tutorials
Просмотров 1893 месяца назад
Chapters: 0:00 - 0:41 Introduction 0:42 - 01:04 What is multi-representation indexing? 01:05 - 01:51 What is multi-representation indexing used? 01:52 - 02:24 When? 02:25 - 03:00 Where? 03:01 - 03:27 Who benefits from multi-representation indexing? 03:27 - 20:09 How does multi-representation indexing works and it is implemented in LangChain? Discover how multi-representation indexing is transfo...
MASTER Chunking in Just 18 Minutes with These 3 Techniques
Просмотров 4153 месяца назад
MASTER Chunking in Just 18 Minutes with These 3 Techniques
Retrieval Augmented Generation - Simplified Explanation!
Просмотров 1223 месяца назад
Retrieval Augmented Generation - Simplified Explanation!
Coders Want to Know This Secret to Success!
Просмотров 2853 месяца назад
Coders Want to Know This Secret to Success!
How To Build Custom AI Agent From Scratch | Step-by-Step Tutorial | No Libraries
Просмотров 6474 месяца назад
How To Build Custom AI Agent From Scratch | Step-by-Step Tutorial | No Libraries
Nice use case for Pydantic ai
Thanks for taking the time to watch the video.
With AI, the sky isn’t the limit-it’s just the beginning 💫
Notebook: colab.research.google.com/drive/1wEFO0_W13J_DBtjd55vNK7vQa_UGo7Hm#scrollTo=3O2V5Jth2Q8F
Here's the code: github.com/zahere-dev/augmate
What are you thoughts about this framework?
What agent automation would you like to see next?
This is quite useful,can you make a video on how this works for multiagent maybe some integration like livekit and all
That's a good idea. Thank you. Will plan a video soon.
Thanks for the video. May I get the slides?
Thank you for sharing! It is good for basic scraping. However, I think we cannot scrape complex web sites.
Thanks for taking the time to watch the video Syed bhai. By complex if you mean JS-heavy dynamic websites, then playwright based scraper can help. You can write your own or use firecrawl (opensource) docs.firecrawl.dev/introduction#powerful-capabilities
How could we connect this agent with another that decides which URL to take based on a search and a criterion to give it to the scraper agent?
Thanks for taking the time to watch the video. Not sure I understand the question fully - but - that could be a task for the interface agent or another agent - let's call it Search Agent Search Agent Input Query: "Get the best offer price of IPhone X" Task 1: Use SERP API or Tavily Search to get the top ranking results Task 2: Pass the best result (links) to Scraper Agent I hope that answered your question.
I instantly hit like when I opened the video. Looking forward to the next one.
Thanks Pedro 🙏
Would you still build scrapers sans-LLMs?
Love the agents side of the video series!!
Computer Use repo - github.com/anthropics/anthropic-quickstarts/tree/main/computer-use-demo
I encountered an error while the program was running: ... ... INFO: [13:49:24] 🤔 Researching for relevant information across multiple sources... INFO: [13:49:24] 🌐 Scraping content from 5 URLs... ERROR:root:Error in get_relevant_images: invalid literal for int() with base 10: 'Auto' INFO: [13:49:26] 📄 Scraped 5 pages of content ... ... ... Despite this error, the program continued to run and produced results.
That's the gpt-researcher library. It's an opensource library - you can tweak how to handle errors. Thanks for taking the time to watch the video and execute the code as well, appreciate it. :)
Suscribed and like 😊
how is compared to crewai? ty
Thanks for taking the time to watch the video.CrewAI is great as well - has a lot of 'config' before you can get things working. Swarm is more simple and lightweight. This will be a video in the coming weeks. Thanks.
@@adaptiveengineer thanks to you my friend for your kind answer
Sick video man. Here before your channel blows up 🚀
Thank you so much @erikfiala🙏
Now we have full circle. Bots creating Blog Posts only other Bots will read ;)
@@micbln8967 Hahaha. Good observation. Thanks for taking the time to watch the video.
@@adaptiveengineerplottwist all these comments are ai too
Great stuff, keep it coming!
Thank you so much, Pedro
What are your thoughts about this new framework?
Visit the DeepMind channel for detailed content on AlphaGo and AlphaFold.
An exceptionally clear introduction to the basic concepts for creating your own agent. Thanks for sharing the code as well.
Thank you for taking the time to watch the video. Glad it was helpful!
She’s the blame for this
What should we learn
@@srupanthreddy9933 Continue to learn coding, but master the domain you are in so you can articulate problems well.
React lived but Facebook died because of it😂,
more like an introduction to the story instead of the story itself
Thanks for sharing feedback.
thanks for saving time. closing the video.
@@la-dev Thank you for the response. The information is condensed from all the interviews she is given. Most of her talks are obviously very technical. There is personal aspect of her life which is beyond the scope of this channel. I still hope you watch this once.
@@adaptiveengineer for sure, I'll watch it. Thanks for the clarity.
Don't forget to watch the documentary by @Honepot.
Awesome video about pdf extraction with colab code walkthrough. Thanks for sharing!
Thanks Pedro!!!
If you are not interested in the theory - skip to the implementation here 03:27 - 20:09 How does multi-representation indexing works and it is implemented in LangChain?
this 4 mins video is way better and comprehensive than a AI book's chapter on RAG. Thanks brother. Keep going on. Complete the RAG series.
Thank you so much for the encouragement, @papansarkar876 🙏. This will be a detailed series with several video in pre-retrieval and post-retreival processes. Humble request - please share it with your network. Thanks again!
Great insights of future!!!
Thank you so much, Deepa 🙏