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Reliable Generative AI Systems: Architecting Secure, Scalable, and Ethical LLM Systems with LangChain, LangGraph & Open Frameworks
Paperback
Publisher: Independently Published
Published: Aug 14 2025
Pages: 416
Weight: 2.11
Height: 0.85 Width: 8.50 Depth: 11.00
Language: English
Reliable Generative AI Systems
Architecting Secure, Scalable, and Ethical LLM Solutions with LangChain, LangGraph & Beyond
Unlock the full potential of Generative AI and Large Language Models (LLMs) with the ultimate technical guide for developers, AI architects, and machine learning engineers building production-grade, reliable, and secure AI systems.
This book is your complete blueprint to designing, deploying, and managing scalable AI applications using cutting-edge frameworks including LangChain, LangGraph, LlamaIndex, Haystack, DSPy, and AutoGen. Whether you're building Retrieval-Augmented Generation (RAG) pipelines, multi-agent orchestration systems, or enterprise AI workflows, this guide delivers purely practical, code-driven methodologies from start to finish.
What You'll Master Inside:
- Engineering reliable, fault-tolerant AI architectures
- Building advanced RAG pipelines that minimize hallucinations
- Implementing multi-agent AI systems with LangGraph and AutoGen
- Designing for security, privacy, and compliance (OWASP, GDPR, HIPAA, EU AI Act)
- Deploying AI with Infrastructure-as-Code (Terraform, Kubernetes, Docker)
- Continuous evaluation with AutoEval, regression testing, and CI/CD pipelines
- Implementing observability, monitoring, and self-healing AI pipelines
- Ethical AI frameworks for bias detection, explainability, and sustainability
Bonus Appendices & Resources:
- AI Security Cheat Sheet (OWASP LLM Risks & Mitigations)
- Production-Ready Prompt Engineering Templates
- Observability & Monitoring Setup Scripts
- Ethical AI & Governance Checklists
- CI/CD Infrastructure Templates for Prompts & Models
- Glossary of Key AI, LLM, and MLOps Terms
Who This Book is For:
- AI/ML Developers deploying LLMs in production
- MLOps Engineers implementing scalable AI pipelines
- Data Scientists transitioning to enterprise-grade AI systems
- Technical Architects designing secure, compliant AI infrastructures
If you want to future-proof your AI systems, deploy enterprise-grade, ethical, and performant LLM applications, and stay ahead in the fast-evolving AI landscape - this book is your indispensable guide.
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