-
Preface
- A Comment on Licenses
- Running Gerbil Scheme on macOS and Linux
- History and Background to the Gerbil Scheme Project
- Core Gerbil Toolkits Used in this Book: :std/net/request and :std/text/json
- Suppressing or Fixing Compilation Warning Messages on macOS
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Setting Up Gerbil Scheme Development Environment
- Emacs Configuration
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Google Gemini API
- Example Code
- Example Output
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Ollama
- Example Code
- Install Ollama and Pull a Model to Experiment With
- Example Output
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OpenAI API
- Example Code
- Example Output
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Inexpensive and Fast LLM Inference Using the Groq Service
- Structure of Project and Build Instructions
- groq_inference.ss Utility
- Example scripts: kimi2.ss and gpt-oss-120b.ss
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Wikidata API Using SPARQL Queries
- Example Code
- Example Output
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Code for Natural Language Processing (NLP)
- Structure of Project and Build Instructions
- Top Level Project Code
- Other Source Files
- Test Run:
- Building and Running the Command Line Tool
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Gerbil Scheme FFI Example Using the C Language Raptor RDF Library
- Implementation of a FFI Bridge Library for Raptor
- Test Code
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Complete FFI Example: C Language Wrapper for Rasqal SPARQL Library and Sord RDF Datastore Library
- Library Selection
- Overview of the Project Structure and Build System
- Implementation of the C Language Wrapper
- A Gerbil Scheme Shim to Call The C Language Wrapper Code
- Gerbil Scheme Main Program for this Example
- Example Output
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Introduction To Writing Command Line Utilities
- Overview of the Command Line Utilities Project Structure and Build System
- Simple Structure for Command Line Utilities
- A More Flexible Structure for Command Line Utilities
- Wrap Up for Writing Command Line Utilities in Gerbil Scheme and Notes On User Built Libraries
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Command Line Applications For NLP
- Re-using the NLP Library For a Command Line Utility to Identify Categories or Topics in Input Text
- Using OpenAI’s GPT-5 model To Summarize Input Text
Gerbil Scheme in Action
AI Applications, Network Programming, and Utilities
Lisp languages are a secret weapon! Use the modern Gerbil Scheme for AI and other applications.
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About the Book
Gerbil Scheme is a practical modern Lisp language that is used in this book for Large Language Model (LLMs) and other AI projects, network programming, and for writing utilities.
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Author
About the Author
Mark Watson is a consultant specializing in LLMs, deep learning, machine learning, knowledge graphs, and general artificial intelligence software development. He uses Common Lisp, Clojure, Python, Java, Haskell, and Ruby for development.
He is the author of 20+ published books on Artificial Intelligence, Deep Learning, Java, Ruby, Machine Learning, Common LISP, Clojure, JavaScript, Semantic Web, NLP, C++, Linux, and Scheme. He has 55 US Patents.
Mark's consulting customer list includes: Google, Capital One, Olive AI, CompassLabs, Disney, Sitescout.com, Embed.ly, and Webmind Corporation.
Mark wrote ten traditional published books for McGraw Hill, Springer Verlag, J Wiley, and Morgan Kaufman publishers before adopting the LeanPub self-publishing platform.

Episode 253
An Interview with Mark Watson
Contents
Table of Contents
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