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LangGraph AI Orchestration: Build Durable Agent Workflows, Adaptive RAG Systems, and Multi-Agent Applications with Python
Paperback
Publisher: Independently Published
Published: Jul 26 2026
Pages: 344
Weight: 1.32
Height: 0.72 Width: 7.00 Depth: 10.00
Language: English
LangGraph AI Orchestration is a practical guide to designing intelligent systems that can reason, use tools, preserve memory, retrieve knowledge, collaborate with other agents, pause for human approval, and recover from failures.
You will learn how to:
Design workflows with state, nodes, edges, routing, loops, and reducers
Connect language models, messages, prompts, and external tools
Add checkpoints, short-term memory, long-term memory, and streaming
Build durable workflows that can pause, resume, retry, and recover
Create human-in-the-loop approval and editing processes
Develop grounded Retrieval-Augmented Generation applications
Build Adaptive RAG systems that rewrite queries and evaluate evidence
Coordinate supervisors, specialist agents, handoffs, and subgraphs
Test agent routes, tools, state updates, and complete trajectories
Trace, evaluate, monitor, and secure LangGraph applications
Expose workflows through APIs and prepare them for deployment
The book includes progressive hands-on projects, including a customer-support routing graph, persistent personal assistant, human-approved transaction agent, document knowledge assistant, Adaptive Research Assistant, multi-agent research workspace, and final Production AI Operations Assistant.
Whether you are a Python developer, AI engineer, LangChain user, backend developer, or technical learner, this book will help you move beyond basic prompts and build dependable AI systems with clear workflow control.
Start building durable agent workflows, intelligent RAG systems, and production-focused multi-agent applications with LangGraph and Python.
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