Build AI Agents with Flowise
Build Visual AI Agents with Flowise and No-Code ToolsBy Cyrus Fontaine
Length8h 1m
About this audiobook
Build AI agents no-code Flowise visual blocks LLM chatbots automations. Create powerful AI workflows without writing a single line of code. This project-based guide teaches you to assemble working LLM agents, chatbots, and automations by connecting blocks visually. Starting from the basics, you'll learn to set up Flowise, design conversation flows, integrate APIs, and deploy production-ready AI solutions. Each chapter builds on the last, with hands-on projects that include a customer support chatbot, a document analysis agent, and a multi-step automation pipeline. You'll master prompt engineering, memory management, tool integration, and error handling—all through a visual interface. By the end, you'll be able to prototype and launch custom AI agents for any business need. Whether you're a beginner or an experienced developer, this book turns complex AI concepts into accessible, visual building blocks. [placeholder] and [placeholder] have written on similar topics, but this book focuses exclusively on the no-code, visual approach with Flowise.
What You'll Learn
Set up Flowise and navigate its visual interface
Design and deploy LLM agents for real-world tasks
Build chatbots with memory and context
Create automations that connect multiple AI models
Integrate external APIs and data sources
Optimize prompts and manage model outputs
Who This Book Is For
No-code enthusiasts, entrepreneurs, product managers, and developers who want to build AI agents without coding. Perfect for beginners and professionals seeking a visual, project-based learning path.
Audiobook details
GenreTechnology
Length8 hrs 1 min
Narrated byListen with 1,000+ voices
FormateBook with Audio
LanguageEnglish
Table of contents
1Build AI Agents with Flowise
2Preface
3Chapter 1 — Why AI Agents Matter (and Why You Can Build One Today)
4Chapter 2 — Your First Agent in 30 Minutes
5Chapter 3 — Flowise close look: The Visual Builder Unpacked
Show all chaptersShow less
6Chapter 4 — LLMs Unpacked: Choosing and Configuring the Brain
7Chapter 5 — Designing Conversations: Prompts, Context, and Tone
8Chapter 6 — Feeding Your Agent Knowledge: Data Sources and Chunking
9Chapter 7 — Building the FAQ Bot (Part 1): Core Logic and RAG
10Chapter 8 — Adding Memory: Making Your Agent Context-Aware
11Chapter 9 — Handling Errors and Edge Cases Gracefully
12Chapter 10 — Automating Business Tasks: From Answers to Actions
13Chapter 11 — Integrating with External Tools: APIs and Webhooks
14Chapter 12 — Building the Customer Support Agent (Part 2): Multi-Turn Conversations
15Chapter 13 — Advanced Agents: Decision Trees and Conditional Logic
16Chapter 14 — Deploying Your Agent: Web, Slack, Email, and More
17Chapter 15 — Monitoring and Improving Performance
18Chapter 16 — Testing and Quality Assurance for AI Agents
19Chapter 17 — Scaling and Collaboration
20Chapter 18 — Future-Proofing: Trends, Ethics, and Next Steps
21About the Author
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