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5.2 Building RAG Systems

Intermediate · 9 articles · MODULE 5: RAG SYSTEMS

Chunk Size, Overlap, and Retrieval Thresholds in RAG Systems

Tutorial · Intermediate · 21 min

A retrieval-augmented system can't compare a question against a whole document at once, so the document is split into overlapping chunks that get embedded and searched independently.

ChunkingRetrieval

Includes Colab notebook

By: Anacodic Team

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Vector Databases: Dimensions, Footprint, and the Migration Nobody Plans For

Tutorial · Intermediate · 26 min

A vector database stores one embedding per chunk and finds the nearest ones — but an index is only meaningful for vectors produced by the model that built it.

Vector DatabasesEmbeddings

By: Anacodic Team

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Document Processing: What You Index Sets the Ceiling

Tutorial · Intermediate · 26 min

Everything downstream of ingestion can only work with text you actually put in the index, and the three decisions that cap the system all fail silently.

IngestionExtraction

By: Anacodic Team

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Generation Pipeline: Assembling Context and Enforcing a Citation Contract

Tutorial · Intermediate · 26 min

Retrieval hands you a ranked list; generation has to turn it into an answer someone can check — and the prompt wording is rarely what decides that.

GenerationCitations

By: Anacodic Team

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Chunking Strategies

Tutorial · Intermediate · 22 min

Chunking decides what retrieval is able to return, so it caps everything downstream. The metric is not size but whether a rule survives intact.

ChunkingDocs

By: Anacodic Team

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Retrieval Techniques

Tutorial · Intermediate · 23 min

Lexical and dense retrievers fail on different queries, which is why hybrid search exists. Fusing them has a trap worth knowing about.

RetrievalVectors

By: Anacodic Team

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Token-Aware Chunking and Reproducible Index Builds

Tutorial · Intermediate · 24 min

A chunk budget expressed in words is a promise about the wrong unit. The model bills and truncates in tokens, and the tokens-per-word ratio varies with the content.

ChunkingIngestion

By: Anacodic Team

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Tables in RAG: Why Flattening Breaks the Answer, Not the Search

Tutorial · Intermediate · 21 min

A table that loses its grid usually keeps retrieving perfectly well; what is destroyed is the binding between a value and the row and column that give it meaning.

IngestionRetrieval

By: Anacodic Team

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Semantic Chunking: Letting the Boundary Follow the Topic

Tutorial · Intermediate · 23 min

Fixed-size chunking cuts at a word count, which lands mid-topic; semantic chunking embeds each sentence and starts a new chunk where the similarity drops.

ChunkingIngestion

By: Anacodic Team

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