AI Autonomous Agents with Python Programming Master LangGraph, CrewAI, and RAG to Build Self-Correcting Swarms

Free Download AI Autonomous Agents with Python Programming: Master LangGraph, CrewAI, and RAG to Build Self-Correcting Swarms and Autonomous Digital Workers
English | December 9, 2025 | ASIN: B0G5Z4XM74 | 1335 pages | EPUB (True) | 5.29 MB
Stop Building Chatbots. Start Building Digital Workers. The era of static "prompt-and-response" AI is over. The future belongs to Autonomous Agents -systems that don't just talk, but act , plan, debug, and collaborate to solve complex problems without human intervention. Book 6 of The Guide to Python Programming is the definitive handbook for senior developers ready to master the most advanced frontier of Generative AI. This is not a theoretical overview; it is a deep-dive architectural guide to building resilient, self-healing, and collaborative multi-agent systems (MAS). From the OODA loop to production deployment, you will learn how to transform an LLM from a text generator into a reasoning engine capable of controlling web browsers, writing software, and managing financial portfolios. What You Will Master: The Cognitive Architecture: Move beyond simple Chains. Master the OODA Loop (Observe, Orient, Decide, Act) and build agents that can plan and re-plan dynamically. Multi-Agent Orchestration: Use CrewAI to build teams of specialized agents (Researchers, Writers, Analysts) that collaborate, delegate tasks, and review each other's work. Cyclic Graphs with LangGraph: Break free from linear workflows. Build complex, stateful loops that allow agents to self-correct errors, refine code, and iterate until success. Memory & RAG: Equip your agents with a "Hippocampus." Implement Vector Stores and Retrieval-Augmented Generation so your agents remember facts and learn from past interactions. Tool Use & Browser Automation: Give your agents hands. Teach them to browse the live web using Selenium, interact with APIs, and scrape real-time data. Production-Grade Security: Protect your swarm from Prompt Injection and "Rogue Loops" (infinite resource consumption) with strict execution budgets and input sanitization. Observability & Economics: Use LangSmith to trace complex debugging chains and master Token Economics to keep your AI costs under control. The Capstone Project Tie it all together by building a fully autonomous Software Development Agency Swarm . You will architect a Product Owner agent, a Developer agent, and a QA agent that work in a closed loop to write, test, and fix code automatically.