RAG Architecture Guide: From Basic Retrieval to Agentic RAG, GraphRAG & RAGAS Evaluation

Description

Deep dive into Retrieval-Augmented Generation (RAG). Learn about GraphRAG, Agentic RAG, RAGAS metrics, HyDE, and re-ranking. Master chunking strategies, vector databases, and multi-hop retrieval to mitigate hallucinations and optimize LLM performance. Essential for AI engineers. #rage #generativeai #llm #graphrag #aiarchitecture #machinelearning #vectordatabases #ragasiyangal RAG evaluation metrics, advanced RAG pipeline, GraphRAG tutorial, RAGAS framework, hybrid search BM25, vector search HNSW, query decomposition, agentic RAG patterns, LLM hallucination mitigation, retrieval re-ranking, context window optimization, semantic cache, FLARE RAG, corrective RAG CRAG, multi-query retrieval RAGAS, Evaluation Metrics, Faithfulness, GraphRAG, Knowledge Graphs, Multi-hop Retrieval, HyDE, Query Transformation, Retrieval Enhancement, Context Window, LLM Limitations, Retrieval Order, Re-ranking, Cross-Encoders, Retrieval Pipeline, Self-RAG, Agentic RAG, Reflection, Parent Document Retrieval, Chunking Strategies, Vector Databases, HNSW, Indexing, Query Decomposition, Agentic RAG, ColBERT, Late Interaction, Retrieval Models, RAGAS, Context Precision, Evaluation, Hallucination Mitigation, NLI, Verification, Semantic Cache, Latency Optimization, Structured Data RAG, Text-to-SQL, FLARE, Active Retrieval, Generation, Chunking, Recursive Splitting, Retrieval Evaluation, Recall@K, Corrective RAG, CRAG, Web Search, Product Quantization, Vector Compression, Multi-Query Retrieval, Query Expansion, Metadata Filtering, Vector Search, Hybrid Search, BM25, Sparse Retrieval, Context Window, LLM Constraints, Agentic RAG, Routing, Embedding Fine-tuning, Contrastive Learning, Re-ranking, Pipeline Stages, Evaluation, Data Leakage, Embeddings, Vectorization, Sentence Window Retrieval, Contextual Augmentation, RAG Components, Generator