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LangChain in Action: Architecting multi-modal and context-aware agents (English Edition)
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By the end of this book, readers will be equipped to design and deploy production-grade AI agents that handle real-world complexity, agents that see, hear, remember, reason, and act with intelligence and precision.
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- Artificial intelligence has evolved beyond chatbots and static decision trees. Enterprise agents today need to be able to see images, understand spoken language, remember context over sessions, and reason through multi-step tasks without human intervention. LangChain has emerged as the leading open-source framework for combining these capabilities into production-ready systems.This book is a hands-on guide to building multi-modal, context-aware AI agents. Readers start by designing reusable LangChain workflows and selecting the right language models, then move into building multimodal pipelines that handle text, images, and audio together. From there, the book covers vision-enabled agents powered by GPT-4o and CLIP, voice assistants built with Whisper and Azure Speech, and agents with persistent memory that maintain context across sessions. Later chapters tackle emotion-aware interactions, retrieval-augmented generation with hybrid search, and knowledge graph fusion for advanced multi-hop reasoning. The book also explores autonomous agents that execute real-world tasks and provides a practical guide to multi-agent planning, collaboration, and evaluation.By the end of this book, readers will be equipped to design and deploy production-grade AI agents that handle real-world complexity, agents that see, hear, remember, reason, and act with intelligence and precision.What you will learn● Build modular LangChain workflows with reusable components.● Architect multimodal pipelines for text, image, and audio.● Implement speech recognition and TTS for voice-enabled agents.● Design agents with persistent memory and cross-session context.● Build RAG systems grounded in domain-specific knowledge bases.● Deploy and evaluate autonomous agents for real-world tasks.Who this book is forThis book is for software engineers, solution architects, and AI practitioners building production-grade agents. Python proficiency and basic familiarity with LLMs or REST APIs are required, as you will transition from simple setups to complex, multi-modal, and autonomous multi-agent systems.Table of Contents1. Building Your First LangChain Agent2. Designing Modular and Reusable LangChain Workflows3. LLM Reasoning and Agent Intelligence4. Building Multimodal LangChain Pipelines5. Building Vision-enabled Agents with Visual Intelligence6. Building Conversational Agents with Voice Intelligence7. Developing Context-aware Agents with Persistent Memory8. Designing Emotion-aware Agents9. Building Retrieval-enhanced Agents10. Fusing Knowledge Networks for Advanced Reasoning11. Creating Autonomous Agents that Perform Real-world Tasks12. Planning, Collaboration, and Evaluating Autonomous Agents
| Publisher | BPB Publications |
| Publication date | 27 July 2026 |
| Language | English |
| Print length | 432 pages |
| ISBN-10 | 9378544207 |
| ISBN-13 | 978-9378544200 |
| Item weight | 739 g |
| Dimensions | 19.05 x 2.49 x 23.5 cm |
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Paperback Generative AI Editorial Review
LangChain in Action: Architecting multi-modal and context-aware agents English Edition is a comprehensive guide published by BPB Publications, slated for release on 27 July 2026. With a print length of 432 pages, it delves into the complex field of architecture for multi-modal agents capable of handling context-aware tasks. This book is particularly relevant for developers and researchers interested in artificial intelligence and its application in natural language processing. The detailed exploration aims to equip readers with the necessary skills to navigate the intricacies of architecting intelligent systems. It ensures a thorough understanding of the underlying principles with practical insights, making it an essential addition to any tech enthusiast's library.
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Pros
- Comprehensive guide to multi-modal agents
- In-depth exploration of context-aware tasks
- Useful for developers and researchers in AI
- Provides practical insights and methodologies
- Clearly outlines principles of intelligent systems
Cons
- Publication date is in the future, yet to be released
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Features & Benefits
- Learn to build modular LangChain workflows with reusable components.
- Architect multimodal pipelines for text, image, and audio processing.
- Implement voice recognition for creating voice-enabled agents.
- Design agents with persistent memory for cross-session context retention.
- Develop retrieval-augmented systems grounded in knowledge bases.
- Deploy and evaluate autonomous agents capable of real-world tasks.
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