LR
Lucia Rossi
2 weeks ago
Practical and rigorous at the same time. I went straight from reading a capsule to shipping it at work.
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Vizuara AI Labs · intermediate
RAG in Production
Build RAG systems that survive real users.
Go from a toy retrieval demo to a production-grade RAG pipeline: ingestion, chunking, embeddings, indexing, retrieval, and generation, built and illustrated end to end. Then level up with advanced retrieval, rigorous evaluation, and agentic and graph RAG.
42 capsules154 figures~8 hoursby Dr. Raj Dandekar
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00RAG Foundations5 capsules
RAG Foundations — 5 chapters.
01Why RAG Existsintuitionfree11 min02What Is Retrieval-Augmented Generation?conceptfree12 min03The RAG Pipeline End to Endconcept🔒13 min04Your First Minimal RAGcode🔒12 min05RAG vs Fine-tuning vs Long Contextdeep-dive🔒12 min01Data Ingestion4 capsules
Data Ingestion — 4 chapters.
06Ingestion Is the Hard Partintuition🔒13 min07Loading Documents: PDF, HTML, and Beyondcode🔒12 min08Cleaning, Normalizing, and Metadatacode🔒10 min09Building a Robust Ingestion Pipelineproject🔒14 min02Chunking5 capsules
Chunking — 5 chapters.
10Why Chunking Decides Retrieval Qualityintuition🔒11 min11Fixed-Size and Overlap Chunkingcode🔒11 min12Recursive and Structure-Aware Chunkingcode🔒12 min13Semantic Chunkingdeep-dive🔒12 min14Choosing Chunk Size and Overlapproject🔒12 min03Embeddings & Indexing6 capsules
Embeddings & Indexing — 6 chapters.
15What Embeddings Actually Encodeconcept🔒12 min16Choosing an Embedding Modeldeep-dive🔒14 min17Similarity Metrics: Cosine, Dot, Euclideanmath🔒11 min18Vector Indexes and ANN Searchconcept🔒14 min19Vector Databases in Practicecode🔒14 min20Building the Indexproject🔒13 min04Retrieval & Generation5 capsules
Retrieval & Generation — 5 chapters.
21The Retrieval Stepconcept🔒12 min22Prompt Augmentation and Context Assemblycode🔒11 min23Generation, Grounding, and Citationsdeep-dive🔒10 min24Building a Naive RAG Chatbotproject🔒12 min25Where Naive RAG Breaksintuition🔒14 min05Advanced RAG6 capsules
Advanced RAG — 6 chapters.
26The Advanced RAG Playbookconcept🔒10 min27Query Transformation and Expansiondeep-dive🔒11 min28Hybrid Search: Dense plus Sparsecode🔒12 min29Re-ranking with Cross-Encodersdeep-dive🔒11 min30Context Compression and Filteringcode🔒14 min31Building an Advanced RAG Pipelineproject🔒11 min06Evaluating RAG6 capsules
Evaluating RAG — 6 chapters.
32You Cannot Improve What You Cannot Measureintuition🔒13 min33Retrieval Metrics: Recall, Precision, MRRmath🔒13 min34Generation Metrics: Faithfulness and Relevanceconcept🔒10 min35RAGAS and LLM-as-Judgecode🔒14 min36Building an Evaluation Datasetproject🔒12 min37Closing the Evaluation Loopdeep-dive🔒13 min07Agentic & Graph RAG5 capsules
Agentic & Graph RAG — 5 chapters.
38Beyond Single-Shot Retrievalintuition🔒10 min39Agentic RAG with Tools and Routingconcept🔒12 min40Graph RAG: Knowledge as a Graphdeep-dive🔒12 min41Building Agentic and Graph RAGproject🔒12 min42Shipping RAG to Productionproject🔒14 minRatings & reviews
1,654 readersRate this book
PN
Priya Nair
3 months ago
This is the resource I wish I had when I started. Clear mental models, zero fluff.
LC
Liam Chen
6 months ago
Beautifully produced and genuinely deep. The reader experience makes it easy to keep going for hours.
IR
Ishita Rao
6 months ago
Rare mix of depth and readability. The worked examples are the clearest I have seen on this subject.