Generation

As explained in Learn Go with Pocket-Sized Projects

A response message is a Protobuf message containing the output data for an API operation.

How Learn Go with Pocket-Sized Projects covers it

How deep it goes

Explains dedicated message declarations and compatibility rationale, stopping short of generated implementation details.

Examples

Uses the CreateHabit endpoint with CreateHabitRequest and CreateHabitResponse containing a Habit field.

What it assumes

Assumes familiarity with services and endpoints while defining Protobuf message structure through the CreateHabit example.

What you can do after

Build it from scratch by declaring version-tolerant Protobuf responses for gRPC endpoints.

How it connects

Connects response messages with Protobuf, gRPC, service definitions, request messages, and API versioning.

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Also explained in

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  Learn Generative AI with PyTorchA language-modeling task in which new text is produced without conditioning on a specific task label, here using a generic or empty prompt.
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  Deep Learning with Python, Third EditionThe process of producing new text token by token from a trained language model, often by feeding previous outputs back as inputs.
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  Natural Language Processing in Action, Second EditionNatural language generation, or text generation, is the computational production of human-readable natural-language text.
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  Generative AI in ActionNatural language generation is the computational production of human-readable language from structured or unstructured inputs.
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  Build a Reasoning Model (From Scratch)The process of producing new textual output from a language model given prior context or instructions.
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  Deep Learning with R, Third EditionThe computational generation of natural-language text by a model.
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  Deep Learning with PyTorch, Second EditionThe task of producing a token sequence as output, conditioned on preceding input or context.
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  Grokking AI Algorithms, Second EditionLanguage generation is the computational production of natural-language text from learned patterns or supplied information.
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  Statistics Every Programmer NeedsPrediction is the process of estimating an outcome from patterns or information in input data without necessarily modeling its temporal ordering.
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  Math and Architectures of Deep LearningA modeling approach that learns a data distribution so new samples resembling the training data can be generated.
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  Sutskever's ListA model that learns a data distribution and can sample new data from it.
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  Causal AIA generative model is a model that represents a process for generating observations, typically by specifying a joint or conditional probability distribution.
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  Statistics Slam DunkThe predict() function is an R function that generates predictions from a fitted model for supplied data, optionally returning interval estimates.
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  Build AI-Enhanced Web AppsThe production of natural-language text by a computational model from an input or context.
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  Digital Twins in ActionGenerative AI is a class of artificial-intelligence models that produces new content or data from learned patterns.
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  Domain-Specific Small Language ModelsThe task of producing output sequences from a model given an input context or prompt, here applied to proteins rather than natural language.
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  Transformers in ActionNatural language generation is the computational production of human-readable language from learned representations or structured information.
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  AI-Powered SearchA generative model is a model that produces new data or content according to patterns learned from its training data.
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  Build an AI Agent (From Scratch)A task response is a standardized A2A message returned by an agent server with the result of processing a task request.

Compare how 20 books explain generation →

Related concepts

• language modelproduced by · A language model is a computational model that represents patterns in linguistic tokens to estimate sequence probabilities and predict or generate language from context.
• variational autoencoderincludes · A variational autoencoder is a generative neural network that learns a probabilistic latent representation of data and decodes samples from it to reconstruct or generate data.
• retrieval-augmented generationpart of · 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.
• Model Servingequivalent to · A model-serving platform is software infrastructure that hosts trained models and exposes inference by accepting requests and returning model outputs.
• labelcontrasts with · A label is a value or annotation associated with an item that identifies its target category, outcome, or reference answer for learning or evaluation.

This explainer was generated by Manning's knowledge graph from the text of Learn Go with Pocket-Sized Projects. The section links point to the parts of the book it draws on.