Mastering Agentic AI Workflows with DSPy: Zero-Shot Modules, RAG Pipelines, Declarative Behavior Modeling, and Scalable Agent Engineering: 1 - Brossura
Libro 1 di 2: DSPy Agentic Engineering Series
Sinossi
Mastering Agentic AI Workflows with DSPy is the definitive hands-on guide to building reliable, transparent, and constraint-driven AI agents using DSPy. This volume focuses on the fundamentals of declarative agent engineering—teaching you how to design modular predictors, define precise behaviors with signatures, and construct stable workflows that eliminate the unpredictability of raw prompting.
You’ll learn how DSPy organizes reasoning, manages constraints, and structures outputs through signatures and modules. Step by step, the book walks you through building zero-shot and few-shot modules, designing retrieval-enhanced workflows, shaping behavior with curated datasets, and evaluating agent consistency through DSPy’s built-in optimization and evaluation tools.
The book emphasizes correctness, verification, and reproducibility at every stage—showing how to architect workflows that are explainable, debuggable, and maintainable in real production environments.
What You Will Learn
- How declarative signatures enforce predictable agent behavior
- Zero-shot and few-shot module construction with structured I/O
- DSPy-powered RAG pipelines that eliminate prompt instability
- Dataset creation for behavior shaping, evaluation, and benchmarking
- Multi-step workflow design using modular DSPy components
- Debugging, testing, and validating agent outputs with confidence
- Techniques for optimizing agent performance and reducing hallucinations
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
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Mastering Agentic AI Workflows with DSPy (Paperback)
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Paperback. Condizione: new. Paperback. Mastering Agentic AI Workflows with DSPy is the definitive hands-on guide to building reliable, transparent, and constraint-driven AI agents using DSPy. This volume focuses on the fundamentals of declarative agent engineering-teaching you how to design modular predictors, define precise behaviors with signatures, and construct stable workflows that eliminate the unpredictability of raw prompting.You'll learn how DSPy organizes reasoning, manages constraints, and structures outputs through signatures and modules. Step by step, the book walks you through building zero-shot and few-shot modules, designing retrieval-enhanced workflows, shaping behavior with curated datasets, and evaluating agent consistency through DSPy's built-in optimization and evaluation tools.The book emphasizes correctness, verification, and reproducibility at every stage-showing how to architect workflows that are explainable, debuggable, and maintainable in real production environments.What You Will LearnHow declarative signatures enforce predictable agent behaviorZero-shot and few-shot module construction with structured I/ODSPy-powered RAG pipelines that eliminate prompt instabilityDataset creation for behavior shaping, evaluation, and benchmarkingMulti-step workflow design using modular DSPy componentsDebugging, testing, and validating agent outputs with confidenceTechniques for optimizing agent performance and reducing hallucinationsWhether you're an AI engineer, Python developer, or system architect, this book gives you the technical clarity and practical workflows needed to engineer predictable DSPy agents from day one. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9798279055296
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Mastering Agentic AI Workflows with DSPy
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PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000. Codice articolo L2-9798279055296
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Mastering Agentic AI Workflows with DSPy (Paperback)
Print on DemandDa: CitiRetail, Stevenage, Regno Unito
Valutazione del venditore 5 su 5 stelle
Paperback. Condizione: new. Paperback. Mastering Agentic AI Workflows with DSPy is the definitive hands-on guide to building reliable, transparent, and constraint-driven AI agents using DSPy. This volume focuses on the fundamentals of declarative agent engineering-teaching you how to design modular predictors, define precise behaviors with signatures, and construct stable workflows that eliminate the unpredictability of raw prompting.You'll learn how DSPy organizes reasoning, manages constraints, and structures outputs through signatures and modules. Step by step, the book walks you through building zero-shot and few-shot modules, designing retrieval-enhanced workflows, shaping behavior with curated datasets, and evaluating agent consistency through DSPy's built-in optimization and evaluation tools.The book emphasizes correctness, verification, and reproducibility at every stage-showing how to architect workflows that are explainable, debuggable, and maintainable in real production environments.What You Will LearnHow declarative signatures enforce predictable agent behaviorZero-shot and few-shot module construction with structured I/ODSPy-powered RAG pipelines that eliminate prompt instabilityDataset creation for behavior shaping, evaluation, and benchmarkingMulti-step workflow design using modular DSPy componentsDebugging, testing, and validating agent outputs with confidenceTechniques for optimizing agent performance and reducing hallucinationsWhether you're an AI engineer, Python developer, or system architect, this book gives you the technical clarity and practical workflows needed to engineer predictable DSPy agents from day one. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Codice articolo 9798279055296
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