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- Building Agentic AI with Python: A Practical ...
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271573281
Building Agentic AI with Python: A Practical Guide to AI Agents, LangGraph, LangChain, RAG, Tools, Memory, and Production Deployment (Learn AI &
Item #:
271573281
AUD 23
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- LLM models can generate impressive responses, but a production AI system needs much more than an LLM. It needs tools, memory, planning, state, workflows, retrieval, human feedback, and reliable control logic.It takes you from the fundamentals of AI agents to building complete, production-ready agentic AI systems.Learn how to turn an LLM into an intelligent system that can reason, use tools, maintain context, retrieve information, make decisions, and execute multi-step workflows.What You Will LearnAI Agent Fundamentals — Understand AI agents and how agentic behavior works.Agent Architecture — Learn about prompts, system instructions, tools, memory etc.Async Python — Master async, await, event loops, API calls, streaming, and asynchronous tool execution.LangChain and LangGraph — Build LLM applications and stateful agent workflows.Memory and Persistence — Implement conversation history, persistent state, database-backed conversations.Tool-Using Agents — Build agents that can search the web, perform calculations, call APIs, and interact.Agentic RAG — Combine AI agents with retrieval-augmented generation and ChromaDB to build assistants.Human-in-the-Loop — Design workflows where humans can review, approve, or interrupt agent actions.Monitoring and Debugging — Use LangSmith to trace agent execution, identify failures, monitor tool calls, and improve agent behavior.Production Engineering — Build FastAPI backends, PostgreSQL databases, Docker containers, CI/CD pipelines, and production-ready project structures.Cloud Deployment — Deploy agentic AI applications using platforms such as Render and AWS.Multi-Agent Systems — Learn how specialized agents can collaborate, delegate tasks, and execute complex workflows.Build Real-World ProjectsThis is a hands-on, project-based book. Instead of learning Agentic AI only through theory, you will build practical applications that progressively increase in complexity.Projects include:Production Agentic Chatbot with LangGraph, tools, RAG, PostgreSQL, LangSmith, and human-in-the-loop workflows.ChatGPT-Style AI Assistant with LLMs, LangGraph, FastAPI, ChromaDB, SQLAlchemy, memory, and production infrastructure.End-to-End Multi-Agent Research & Report Generator using multiple specialized agents working together to research and plan trips.Tool-using AI agentsRAG-powered assistantsStateful conversational agentsMulti-agent workflowsProduction-ready agent APIsEach project builds on concepts introduced earlier, helping you move from simple LLM applications to sophisticated autonomous systems.From Prototype to ProductionYou will also learn the engineering practices required to take an agent beyond a simple notebook or demo.The book covers:FastAPI backend developmentPostgreSQL and SQLAlchemyDocker and Docker ComposeEnvironment configurationGitHub Actions CI/CDLangSmith observabilityLogging and monitoringSecurity and tool permissionsError handling and retriesCloud deployment with AWS and RenderWho This Book Is ForThis book is designed for Python developers, software engineers, and programmers who want to build real-world AI agents.Learn how AI assistants are designed, orchestrated, connected to tools and data, monitored, and deployed, this book provides a practical path from fundamentals to production.Learn the architecture. Write the code. Build the agents. Deploy them to the real world.
| Publication date | September 7, 2026 |
| Language | English |
| File size | 9.3 MB |
| Screen Reader | Supported |
| Enhanced typesetting | Enabled |
| X-Ray | Not Enabled |
| Word Wise | Not Enabled |
| Print length | 1689 pages |
| Page Flip | Enabled |
| Book 4 of 4 | Learn AI & Machine Learning in Python |
| Item Weight | 1 lbs (450 grams) |
Product Description
Building Agentic AI with Python: A Practical Guide to AI Agents, LangGraph, LangChain, RAG, Tools, Memory, and Production Deployment (Learn AI & Machine Learning in Python Book 4)
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