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  • Book Overview & Buying AI Agents in Practice
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AI Agents in Practice

AI Agents in Practice

By : Valentina Alto
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AI Agents in Practice

AI Agents in Practice

5 (1)
By: Valentina Alto

Overview of this book

As AI agents evolve to take on complex tasks and operate autonomously, you need to learn how to build these next-generation systems. Author Valentina Alto brings practical, industry-grounded expertise in AI Agents in Practice to help you go beyond simple chatbots and create AI agents that plan, reason, collaborate, and solve real-world problems using large language models (LLMs) and the latest open-source frameworks. In this book, you'll get a comparative tour of leading AI agent frameworks such as LangChain and LangGraph, covering each tool's strengths, ideal use cases, and how to apply them in real-world projects. Through step-by-step examples, you’ll learn how to construct single-agent and multi-agent architectures using proven design patterns to orchestrate AI agents working together. Case studies across industries will show you how AI agents drive value in real-world scenarios, while guidance on responsible AI will help you implement ethical guardrails from day one. The chapters also set the stage with a brief history of AI agents, from early rule-based systems to today's LLM-driven autonomous agents, so you understand how we got here and where the field is headed. By the end of this book, you'll have the practical skills, design insights, and ethical foresight to build and deploy AI agents that truly make an impact.
Table of Contents (15 chapters)
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1
Part 1: Foundations of AI Workflows and the Rise of AI Agents
4
Part 2: Designing, Building, and Scaling AI Agents
10
Part 3: Road to an Open, Agentic Ecosystem
14
Index

Introduction to the LangChain ecosystem

LangChain was introduced in October 2022 as an open source framework aimed at simplifying the development of applications powered by large language models (LLMs). Initially, it provided developers with tools to connect LLMs to external data sources and utilities, facilitating the creation of more dynamic and context-aware applications.

Over time, LangChain evolved beyond its original framework into a comprehensive ecosystem. This transformation was driven by the growing complexity of AI applications and the need for more robust tools to manage the entire lifecycle of LLM-powered solutions. Today, LangChain encompasses a suite of components and integrations designed to support developers from the initial prototyping phase through to deployment and ongoing management.

Figure 6.1: LangChain ecosystem

Figure 6.1: LangChain ecosystem

According to the official documentation, the entire LangChain ecosystem allows you to build, run, and deploy your AI-powered solutions...

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AI Agents in Practice
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