Video yükleniyor...

Video Yüklenemedi

Ana Sayfaya Dön

Building an Agentic Search System Building an agentic system is not too hard. Loops, function calling, tool execution, and the model. That's it! I show in this video how to build a search agent from scratch. ~350 lines of code!

57,290 görüntüleme • 1 yıl önce •via X (Twitter)

11 Yorum

elvis profil fotoğrafı
elvis1 yıl önce

The best way to learn this stuff is to build it from scratch. You can then orchestrate advanced multi-agent, multi-tool systems for all kinds of things. This is one of many lessons I just published in my new AI Agents course. Great course for devs!

elvis profil fotoğrafı
elvis1 yıl önce

We have a good flash sale for the next couple of days. If you are interested, DM me for a discount code.

elvis profil fotoğrafı
elvis1 yıl önce

The fun part about building agentic systems from scratch is that you gain more intuition about what the agent can and cannot do. This helps to better iterate and improve the agentic systems compared to using an agent orchestrator framework. Course here:

Alexander Myasoedov profil fotoğrafı
Alexander Myasoedov1 yıl önce

INTRODUCING: Agentic Security - LLM Security Scanner! 🔍 🔑 Features: Scans for prompt injections, jailbreaking & more. Provides detailed reports & options to customize attack rules. 🔗access the GitHub Link ↓

Alex from OmniraAI profil fotoğrafı
Alex from OmniraAI1 yıl önce

Clean setup. Love how you boiled it down, straight to the point just agents doing work.

prabhu💢 profil fotoğrafı
prabhu💢1 yıl önce

Its really interesting, thanks for sharing the breakdown

Tsukuyomi profil fotoğrafı
Tsukuyomi1 yıl önce

350 lines for an agentic system? That's like a warm-up for me. But hey, loops and functions are the bread and butter of coding. Let’s see if your search agent can find the meaning of life while it's at it.

_youZeenITHOK_ profil fotoğrafı
_youZeenITHOK_1 yıl önce

Impressive!

Bianca Banks profil fotoğrafı
Bianca Banks1 yıl önce

It’s unreal watching @StevenFeric the trades are unbelievably accurate. Tried applying his methods, I'm sitting on a $160,000 gain.

VentureMind AI profil fotoğrafı
VentureMind AI1 yıl önce

WOW

Aaliya profil fotoğrafı
Aaliya1 yıl önce

Simple breakdown, powerful concept!

Benzer Videolar

New short course: Building Code Agents with Hugging Face smolagents! Learn how to build code agents in this course, created in collaboration with Hugging Face, and taught by Thomas Wolf, its co-founder and CSO, and m_ric, Hugging Face’s Project Lead on Agents. Tool-calling agents use LLMs to generate multiple function calls sequentially to complete a complex sequence of tasks. They generate one function call, execute it, observe, reason, and decide what to do next. Code agents take a different approach. They consolidate all these calls into a single block of code, letting the LLM lay out an entire action plan at once, which can be executed efficiently to provide more reliable results. You’ll learn how to code agents using smolagents, a lightweight agentic framework from Hugging Face. Along the way, you’ll learn how to run LLM-generated code safely and develop an evaluation system to optimize your code agent for production. In detail, you’ll learn: - How agentic systems have evolved, gaining greater levels of agency over time—and why code agents are a next step. - How code agents write their actions in code. - When code agents outperform function-calling agents. - How to run code agents safely in your system using a constrained Python interpreter and sandboxing using E2B. - To trace, debug, and assess the code agent to optimize its behaviours for complex requests. - How to build a research multi-agent system that can find information online and organize it into an interactive report. By the end of this course, you’ll know how to build and run code agents using smolagents, and deploy them safely with a structured evaluation system in your projects. Please sign up here!

Andrew Ng

124,382 görüntüleme • 1 yıl önce