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Introduction to JSON and TOON for AI
This chapter introduces JSON and TOON, explaining their role in AI, why they are critical for Large Language Models, and guides you through setting up …
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Core Concepts: Understanding TOON
This chapter introduces TOON (Token-Oriented Object Notation), explaining its core syntax, design philosophy for token efficiency, and how it differs …
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Intermediate Topics: TOON's Advanced Features and Best Practices
Explore TOON's advanced syntax, including key folding, custom delimiters, and detailed quoting rules. Learn best practices for maximizing token …
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Advanced Topics: Performance Comparison and Optimization
This chapter provides a deep dive into the performance characteristics of JSON and TOON. It covers token cost analysis, benchmarks across various LLMs …
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Advanced Topics: Hybrid Approaches and Ecosystems
This chapter delves into hybrid data strategies, integrating JSON and TOON in AI workflows. It covers the tools, libraries, and best practices for …
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Guided Project 1: Building a Structured Data Extraction Agent
A step-by-step guided project to build an AI agent capable of extracting structured information from unstructured text. This project leverages both …
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Guided Project 2: Optimizing LLM Prompts with TOON
This project guides you through refactoring complex JSON prompts into token-efficient TOON to reduce costs and improve LLM performance. You'll work …
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Bonus Section: Further Learning and Resources
A curated list of recommended resources to deepen your understanding of JSON and TOON, including official documentation, online courses, influential …
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