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LangGraph - managing AI Agents: A Beginner's Guide
Paperback
Publisher: Independently Published
Published: Nov 18 2024
Pages: 154
Weight: 0.61
Height: 0.33 Width: 7.50 Depth: 9.25
Language: English
Get to grips with the LangGraph framework from theory to production-ready applications. Code examples are regularly updated to keep you abreast of the latest LangGraph and LangChain changes.
Purchase of the print or Kindle book includes a free PDF eBook and all code samples.
AI Agents can solve very complex situations and that's why clear communication is essential to achieve the desired results.
This is where LangGraph excels. Communicating with LLMs via code leads to far more reliable results than using only natural language (prompt engineering).
AI Agents are LLMs on steroids. The anatomy of an agent consists of:AI_AGENT = LLM + MEMORY + TOOLS + PLANNING + DO_WHILE_LOOP The LangGraph framework is an excellent tool for implementing and orchestrating all of these components. Simply put, AI agents are LLMs with tools, that operate in a loop to accomplish specific goals. You can assign them tasks such as:
- a calendar manager to schedule and manage appointments, send reminders, and suggest optimal meeting times
- a personal AI Agent assistant to organize trips, book hotels and plane tickets for a destination in a given budget.
- AI Agents Introduction
- LangGraph Fundamentals
- Nodes, Edges, and Graphs in LangGraph
- Building Your First AI Agent
- Tool Calling and Functions
- AI Agents and Tools
- Using Stateful Graphs
- Threads in LangGraph
- ReACT Agents
- Human in the Loop
- Adding Interruptions
- Managing Permissions in the Graph State
- Multi Agent Systems
- Multimodal Agents (using video and audio)
- 24 Mar 2025: added 2 brand new chapters one on Multi Modal AI Agents (text and audio) and the other one on ReAct AI agents
- 15 Jan 2025: various typos and extra code samples
- 04 Dec 2024: added the Multi AI Agent Orchestration chapter
Let's start learning!
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