You don't need another chatbot tutorial. You need to build systems. If you're tired of LLM playground demos that break in the real world, this book is your answer. Building Scalable LLM Systems for Production is not about playing with GPT-it's about deploying intelligent applications that actually work, scale, and survive under load. Built for software engineers, ML practitioners, and technical product teams, this book teaches you how to go beyond prompts and actually engineer production-grade solutions using LangChain ...
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You don't need another chatbot tutorial. You need to build systems. If you're tired of LLM playground demos that break in the real world, this book is your answer. Building Scalable LLM Systems for Production is not about playing with GPT-it's about deploying intelligent applications that actually work, scale, and survive under load. Built for software engineers, ML practitioners, and technical product teams, this book teaches you how to go beyond prompts and actually engineer production-grade solutions using LangChain, RAG architectures, vector databases, custom APIs, and open-weight models like Mistral and LLaMA. Whether you're building a RAG-powered search engine, a tool-using AI agent, or a multi-tenant SaaS with OpenAI or Claude-this book gives you real-world architectures, cost-saving deployment patterns, monitoring blueprints, and scalable design principles tested under real traffic, not just theory. Inside, you'll learn how to: Design retrieval-augmented generation (RAG) workflows that are accurate, fast, and resistant to hallucination Choose and configure vector databases like Pinecone, Weaviate, Chroma, and Qdrant Build multi-step LangChain workflows with tools, memory, and tracing Deploy LLM apps using FastAPI, Docker, Vercel, and serverless infrastructure Monitor token usage, latency, and model behavior using LangSmith and OpenTelemetry Automate failover, fallback, and error recovery in real-time Scale with confidence using quantization, async inference, CI/CD, and cost control techniques Audit, red-team, and safeguard your applications with ethical best practices at scale And most importantly: you'll walk away with production templates, full-stack architecture blueprints, and ready-to-use Colab/GitHub links that help you ship faster and smarter-without hallucinating your infrastructure. If you're building with GPT, Claude, Mistral, or open-source LLMs-and your app needs to run on more than just your laptop-this book is your operations manual. From prompt engineer to LLM systems architect. This book makes that leap possible.
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Add this copy of Building Scalable LLM Systems for Production: Deploy to cart. $28.18, new condition, Sold by Ingram Customer Returns Center rated 5.0 out of 5 stars, ships from NV, USA, published 2025 by Independently Published.
