How deeply does Spring AI in Action cover stuffing the prompt?

Explains file storage, resource loading, template substitution, and API invocation, then defers large-document handling to RAG.

Stuffing the prompt

As explained in Spring AI in Action

Prompt stuffing is the technique of placing an entire source document or large body of reference text directly into a model prompt.

Stuffing the prompt places a source document or large reference text alongside a question, giving the model an open-book context for answering topics absent from its training. section 3.2

A Spring application implements the technique by:

Storing Burger Battle rules in a classpath text file. section 3.2

Answering a rules question

Asking what the Destroy card does returns an answer grounded in the supplied Burger Battle rules. The same endpoint can answer a chess question when chess rules are available.

How Spring AI in Action covers it

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Related concepts

promptuses · An input, typically containing instructions or context, supplied to an artificial-intelligence model to guide or elicit its output.
retrieval-augmented generationaddressed 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.
MapReducealternative to · MapReduce is a computational pattern that applies map operations to input elements or partitions and combines the intermediate results through reduction or aggregation.
context windowconfigured by · A context window is the bounded sequence of tokens or other input information a model can access when processing or generating an output.

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