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Free Download Advanced RAG with AI Agents: A Practical Guide to Building Retrieval-Augmented Agents with LangChain, Python, and ReAct for Context-Aware AI Workflows by Juno Darian
English | July 6, 2025 | ISBN: N/A | ASIN: B0FGY49YMK | 300 pages | EPUB | 0.87 Mb
Advanced RAG with AI Agents: A Practical Guide to Building Retrieval-Augmented Agents with LangChain, Python, and ReAct for Context-Aware AI Workflows
Unlock the Future of AI Development with Retrieval-Augmented Generation and Agentic Workflows
Are you ready to build next-generation AI agents that think, reason, and retrieve with precision? Whether you're an ML engineer, backend developer, or AI enthusiast, this hands-on guide will equip you with everything you need to build production-ready, context-aware AI agents using cutting-edge tools like LangChain, ReAct, FAISS, and Python.
Inside this groundbreaking guide, you'll learn how to:
- Master Retrieval-Augmented Generation (RAG) from first principles
- Implement intelligent agents using LangChain and the ReAct framework
- Build scalable vector stores with Chroma and FAISS
- Create multi-agent systems that collaborate and reason across documents
- Add memory, personalization, and multimodal inputs using CLIP and Hugging Face
- Deploy real-world applications including code search agents, chatbots, and research assistants
- Containerize and scale your AI agents using FastAPI, Docker, AWS, and GCP
- Building a document Q&A chatbot with retrieval + reasoning
- Automating literature reviews with arXiv and LangChain
- Deploying scalable RAG APIs using cloud platforms
- 100% project-based with runnable Python examples
- SEO-aligned for 2025 AI trends: Agentic RAG, Multimodal Retrieval, LangChain, and ReAct
- No fluff, no theory dumps-just real tools, real agents, real results
- Text-based diagrams, flowcharts, and code walkthroughs
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