Retrieved document

As explained in Grokking AI Applications

Textual information retrieved from a knowledge source and supplied to a language model alongside a user query.

A retrieved document is a relevant document or context chunk selected from a knowledge source and supplied to a language model with the user’s query. Retrieval gives a stateless, pretrained model the information it needs to reason about new data. section 4.1

A retrieved document fits into the RAG workflow:

• Retrieve the top k documents or chunks using a similarity metric such as Euclidean distance. section 4.1
• Attach the selected context to a composite prompt containing the user’s question. section 4.1
• Let the language model generate an answer grounded in the supplied context. section 4.1

Pet question

For “Who is the nasty cat?”, retrieval selects chunks stating that Fox is not well-mannered, Kit is cute, and Brian is a good kitten; the model answers, “Fox is the nasty cat.” section 4.1

Figure 4.1 A RAG-based flow includes three essential steps: document ingestion, document retrieval, and answer generation.

Trace retrieved documents through ingestion, retrieval, and answer generation in the RAG flow. section 4.1

How Grokking AI Applications covers it

How deep it goes

Explains top-k selection, similarity distance, prompt enrichment, and grounding, while deferring large-scale metadata and high-dimensional details.

Examples

Uses pet-related chunks about Fox, Kit, and Brian to demonstrate selecting context and generating an answer.

What you can do after

Understand how selected context enables a stateless language model to answer questions using retrieved information.

How it connects

Connects retrieval to RAG, embeddings, vector databases, similarity metrics, prompts, and language-model answer generation.

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Also explained in

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  Building Reliable AI SystemsInformation selected from an external knowledge source and supplied to a model as response context.

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Related concepts

• retrieval-augmented generationused by · Retrieval-augmented generation is a technique that retrieves relevant information from external sources and supplies it as context to a generative model when producing an output.
• promptpart of · An input, typically containing instructions or context, supplied to an artificial-intelligence model to guide or elicit its output.
• GPT modelused by · A GPT model is a generative pretrained Transformer language model that produces text autoregressively by predicting successive tokens from preceding context.
• prompt templateused by · A prompt template is a reusable structure for organizing instructions, context, and variable inputs supplied to a language model.
• generatorused by · A generator is a computational component or construct that produces data or values from inputs, representations, context, or specified constraints.
• fidelitymeasured by · Fidelity is the degree to which an output, model, or representation accurately reflects or is supported by its relevant source, target, evidence, or behavior.

This explainer was generated by Manning's knowledge graph from the text of Grokking AI Applications. The section links point to the parts of the book it draws on.