How to build AI Agents with smolagents - FULL Course

About this Video

• Video Title: How to build AI Agents with smolagents - FULL Course
• Channel: J-HAYER
• Speakers: Johannes
• Duration: 01:23:09

Introduction

This course provides a comprehensive guide to building AI agents using the smolagents framework. It covers theoretical concepts of AI agents, their architecture, different workflow types, multi-agent collaboration, and best practices. The course also includes hands-on experience building agents, creating custom tools, implementing UIs with GradioUI, sharing agents on Hugging Face Spaces, and advanced monitoring with OpenTelemetry and LangFuse.

Key Takeaways

• AI Agents Defined: An AI agent is an AI model capable of interacting with its environment to achieve a specific goal, unlike passive LLMs. It comprises a "brain" (LLM for reasoning) and a "body" (tools for interaction).
• Workflows vs. Agents: The course distinguishes between agentic workflows (predefined steps) and true AI agents (dynamic decision-making). Workflows are suitable for predictable tasks, while agents excel in creative problem-solving.
• Smolagents Framework: Smolagents is a lightweight, flexible library for building AI agents. Key features include simple yet powerful architecture, flexible model integration, a code-first approach, built-in tooling, and easy multi-agent system creation.
• Code Agents vs. Tool-Calling Agents: The course compares code agents (generating and executing code) and tool-calling agents (using pre-defined tools). Code agents offer greater flexibility and composability.
• Multi-Agent Systems: The course demonstrates building a multi-agent system using a manager-worker architecture, where a manager agent delegates tasks to specialized agents for improved efficiency and complexity handling.
• Monitoring with OpenTelemetry and LangFuse: The course integrates OpenTelemetry and LangFuse for monitoring AI agents, providing essential visibility into their performance and identifying issues.