Production-Ready RAG Tutorial 2026 | Build & Deploy Local and Enterprise RAG Systems
π Topics Covered RAG Fundamentals β What is RAG? β Why RAG is better than Fine-Tuning for many use cases β RAG Workflow Explained β RAG vs Fine-Tuning β RAG vs AI Agents Local Development Setup β Install Ollama β Run Local LLMs β Document Processing β PDF Parsing β Chunking Strategies β Embedding Models β Local Vector Database Setup ChromaDB FAISS β Query Pipeline Production Architecture β Enterprise RAG Architecture β API Layer β Authentication & Authorization β Hybrid Search β Metadata Filtering β Multi-Tenant Architecture β High Availability β Horizontal Scaling β Caching Strategies Vector Databases β ChromaDB β FAISS β Pinecone β Weaviate β Milvus β Qdrant LLM Integration β Local Models Llama Mistral Gemma β Cloud Models GPT Claude Gemini Advanced RAG Concepts β Parent-Child Chunking β Semantic Search β Hybrid Search β Reranking β Context Compression β Knowledge Graph RAG β Agentic RAG β Multi-Agent RAG Production Deployment β Docker β Kubernetes β AWS β Azure β Google Cloud β Monitoring β Logging β Observability β Security β Cost Optimization π Production Architecture Covered User β βΌ Angular / React UI β βΌ API Gateway β βΌ Authentication Layer β βΌ RAG Orchestrator β βββ Embedding Service β βββ Vector Database β βββ Metadata Store β βββ Reranker β βββ LLM Service β βΌ Generated Response π― What You'll Learn β Build a ChatGPT-style chatbot β Query PDFs and documents β Create enterprise knowledge assistants β Deploy RAG on your laptop β Scale RAG for thousands of users β Secure enterprise AI systems β Design production-ready architectures β Reduce LLM hallucinations β Optimize costs πΌ Real-World Use Cases Enterprise Knowledge Assistant Search HR, Legal, Compliance, and Policy documents. Healthcare Assistant Search medical reports and healthcare guidelines. Banking Assistant Query policies, regulations, and customer documentation. Legal Assistant Search contracts and legal agreements. Customer Support Use company documentation for accurate responses. Software Development Search architecture documents, APIs, and codebases. π¨βπ» Perfect For AI Engineers Solution Architects Software Engineers Cloud Engineers Data Engineers Product Managers CTOs Technical Leads Enterprise Architects #RAG #RetrievalAugmentedGeneration #GenerativeAI #LLM #AIEngineer #LangChain #LlamaIndex #VectorDatabase #EnterpriseAI #AIAgents #ArtificialIntelligence #MachineLearning #SoftwareArchitecture #CloudComputing #ProductionAI

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