Developers Handbook on Vector Databases for AI Agents: From Embeddings to Intelligent Agents (Building Production-Ready AI Agents)

By Todd Chandler

Ever wondered how AI agents recall facts, sift through millions of documents, and deliver precise answers in milliseconds? Summary Developers Handbook on Vector Databases for AI Agents: From Embeddings to Intelligent Agents equips you with everything you need to build that "memory layer." Explore how to turn text, images, and audio into highdimensional embeddings, organize them in FAISS, Milvus, Pinecone, Qdrant, or pgvector, and integrate with large language models for realtime, contextaware responses. What Sets This Book Apart? EndtoEnd Pipeline : Walk through each stage--from data cleaning and embedding generation to indexing and RetrievalAugmented Generation (RAG). HandsOn Code : Run uptodate Python examples that work out of the box with Sentence Transformers, FAISS, Milvus, Pinecone, and more. Architectural Blueprints : Visual diagrams guide you through singleagent workflows, hybrid search systems, and scalable cloud deployments. Expert Best Practices : Learn modular design, continuous testing, secure configuration, performance monitoring, and data governance. RealWorld Case Studies : See how top companies apply vector search to power chatbots, recommendation engines, and enterprise search platforms. Ready to give your AI agents realtime memory and reasoning power? Grab your copy of Developers Handbook on Vector Databases for AI Agents and start building smarter, faster, and more adaptive systems today!

• Format: Paperback
• Language: English
• ISBN: B0F5LXJ3HH
• ISBN13: 9798280410534
• Release Date: April 2025
• Publisher: Independently published
• Length: 162 Pages
• Dimensions: 10.0" x 0.4" x 7.0"