LangFlow in Action: Building Agentic Workflows & Retrieval-Augmented Generation (RAG) Applications: Visual Workflow Engineering, LangChain Patterns, R - Paperback

by Yuan Zhu (Author)

LangFlow in Action teaches engineers and product teams how to design, prototype, and deploy visual, agentic AI workflows using LangFlow and LangChain patterns. The book walks through building modular workflow blocks, connectors to vector stores and external APIs, chaining LLM calls, and composing agent behaviors for decisioning and automation. Learn to implement robust RAG systems indexing, embedding pipelines, chunking, vector DB choice (FAISS, Milvus, Pinecone), retrieval strategies, and prompt templates that maximize factuality and relevance. Advanced chapters show how to build multimodal pipelines (text + images + APIs), agent orchestration, debugging and observability for workflows, and deployment strategies (serverless, containerized, hybrid). Each chapter includes LangFlow flow examples, LangChain recipes, prompt engineering best practices, and production deployment guides.
Key topics: LangFlow visual design, LangChain integration patterns, RAG indexing & retrieval, vector stores, prompt engineering, agentic controllers, connectors & tool use, multimodal workflows, testing & debugging, deployment & scaling.