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
Start Reading →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
Start Reading →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
Start Reading →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
Start Reading →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
Start Reading →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
Start Reading →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
Start Reading →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
Start Reading →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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