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Developers Handbook on Vector Databases for AI Agents: From Embeddings to Intelligent Agents
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 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 high‑dimensional embeddings, organize them in FAISS, Milvus, Pinecone, Qdrant, or pgvector, and integrate with large language models for real‑time, context‑aware responses.
What Sets This Book Apart?
End‑to‑End Pipeline: Walk through each stage—from data cleaning and embedding generation to indexing and Retrieval‑Augmented Generation (RAG).
Hands‑On Code: Run up‑to‑date Python examples that work out of the box with Sentence Transformers, FAISS, Milvus, Pinecone, and more.
Architectural Blueprints: Visual diagrams guide you through single‑agent workflows, hybrid search systems, and scalable cloud deployments.
Expert Best Practices: Learn modular design, continuous testing, secure configuration, performance monitoring, and data governance.
Real‑World Case Studies: See how top companies apply vector search to power chatbots, recommendation engines, and enterprise search platforms.
Ready to give your AI agents real‑time 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!
Summary
Developers Handbook on Vector Databases for AI 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 high‑dimensional embeddings, organize them in FAISS, Milvus, Pinecone, Qdrant, or pgvector, and integrate with large language models for real‑time, context‑aware responses.
What Sets This Book Apart?
End‑to‑End Pipeline: Walk through each stage—from data cleaning and embedding generation to indexing and Retrieval‑Augmented Generation (RAG).
Hands‑On Code: Run up‑to‑date Python examples that work out of the box with Sentence Transformers, FAISS, Milvus, Pinecone, and more.
Architectural Blueprints: Visual diagrams guide you through single‑agent workflows, hybrid search systems, and scalable cloud deployments.
Expert Best Practices: Learn modular design, continuous testing, secure configuration, performance monitoring, and data governance.
Real‑World Case Studies: See how top companies apply vector search to power chatbots, recommendation engines, and enterprise search platforms.
Ready to give your AI agents real‑time 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!
208 pages, Kindle Edition
Published April 17, 2025
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