Cover Material, Copyright, and License

Preface

1. Requests from the Author
2. Setting Up Your Development Environment
3. What is Lisp Programming Style?
4. Hy is Python, But With a Lisp Syntax
5. How This Book Reflects My Views on Artificial Intelligence and the Future of Society and Technology
6. About the Book Cover

Introduction to the Hy Language

1. Using Python Libraries
2. Global vs. Local Variables
3. Using Python Code in Hy Programs
4. Using Hy Libraries in Python Programs
5. Replacing the Python slice (cut) Notation with the Hy Functional Form
6. Iterating Through a List With Index of Each Element
7. Formatted Output
8. Importing Libraries from Different Directories on Your Laptop
9. Hy Looks Like Clojure: How Similar Are They?
10. Plotting Data Using the Numpy and the Matplotlib Libraries
11. Bonus Points: Configuration for macOS and ITerm2 for Generating Plots Inline in a Hy REPL and Shell

Why Lisp?

1. I Hated the Waterfall Method in the 1970s but Learned to Love a Bottom-Up Programming Style
2. First Introduction to Lisp
3. Commercial Product Development and Deployment Using Lisp
4. Performing Bottom Up Development Inside a REPL is a Lifestyle Choice

Writing Web Applications

1. Getting Started With Flask: Using Python Decorators in Hy
2. Using Jinja2 Templates To Generate HTML
3. Handling HTTP Sessions and Cookies
4. Deploying Hy Language Flask Apps to Google Cloud Platform AppEngine
5. Wrap Up

Responsible Web Scraping

1. Using the Python BeautifulSoup Library in the Hy Language
2. Getting HTML Links from the DemocracyNow.org News Web Site
3. Getting Summaries of Front Page from the NPR.org News Web Site

Using the Brave Search APIs

1. Setting an Environment Variable for the Access Key for Brave Search APIs
2. Example Search Script
3. Wrap-up

Deep Learning

1. Simple Multi-layer Perceptron Neural Networks
2. Deep Learning
3. Using Keras and TensorFlow to Model The Wisconsin Cancer Data Set
4. Using a LSTM Recurrent Neural Network to Generate English Text Similar to the Philosopher Nietzsche’s Writing

Natural Language Processing

1. Exploring the spaCy Library
2. Implementing a HyNLP Wrapper for the Python spaCy Library
3. Wrap-up

Datastores

1. Sqlite
2. PostgreSQL
3. RDF Data Using the “rdflib” Library
4. Wrap-up

Linked Data, the Semantic Web, and Knowledge Graphs

1. Understanding the Resource Description Framework (RDF)
2. Resource Namespaces Provided in rdflib
3. Understanding the SPARQL Query Language
4. Wrapping the Python rdflib Library

Knowledge Graph Creator

1. Recommended Industrial Use of Knowledge Graphs
2. Design of KGCreator Application
3. Problems with using Literal Values in RDF
4. Revisiting This Example Using URIs Instead of Literal Values
5. Wrap-up

Knowledge Graph Navigator

1. Review of NLP Utilities Used in Application
2. Utilities to Colorize SPARQL and Generated Output
3. Text Utilities for Queries and Results
4. Finishing the Main Function for KGN
5. Wrap-up

Using OpenAI GPT

1. OpenAI Text Completion API

Using Google Gemini API

1. REST Interface
2. Using Google’s Python Package to Access Gemini
3. Wrap Up for Using the Gemini APIs

Running Local LLMs Using Ollama

1. Completions
2. Tool Use
3. Wrap Up for Running Local LLMs Using Ollama

Agents Using the Agno Agent Framework Running On a Local Ollama Model

1. An Agent For Answering Questions About A Specific Web Site
2. Wrap Up for Agno Agent Example

Using Perplexity Sonar Model for Combined Web Search and LLM Based Reasoning

1. A Hy Language Client Library for Perplexity
2. Example Output
3. Wrap Up for Using Perplexity

Using LangChain to Chain Together Large Language Models

1. Installing Necessary Packages
2. Basic Usage and Examples
3. Creating Embeddings
4. Using LangChain Vector Stores to Query Documents
5. LangChain Wrap Up

Large Language Models Experiments Using Google Colab

Book Wrap-up