Generative AI is transforming software development. Stay on the cutting edge with this guide to AI pair programming! Learn how to make the most of modern tools like ChatGPT and GitHub Copilot to improve your coding. Automate refactoring, debugging, and other tedious tasks, and use techniques such as prompt engineering and retrieval-augmented generation to get the code you need. Follow practical examples that show how you can program faster, more efficiently, and with fewer errors with the help of AI.
In this book, you'll learn about:
a. Hype versus Reality
Learn from expert developers to understand the possibilities (and pitfalls) of AI tools. With the help of practical code examples, see how to use AI helpers correctly to their full potential.
b. Assistants for All Tasks
This guide gives you an up-to-date overview of all aspects of AI-assisted coding: GitHub Copilot autocompletions, project bootstrapping with OpenHands, debugging and refactoring, application development, and more.
c. In the Cloud or Local?
Use OpenAI's API to integrate AI models directly into your own scripts and automations-or use local large language models (LLMs) to work independently of cloud services.
Highlights include:
1) Structured programming with AI
2) Debugging
3) Unit testing
4) Refactoring
5) Automatic document creation
6) Database development and design
7) Scripting and administration
8) Local large language models (LLMs)
9) Retrieval-augmented generation (RAG)
10) ChatGPT and GitHub Copilot
11) OpenHands
12) OpenAI API
Sprache
Verlagsort
Verlagsgruppe
Rheinwerk Publishing Inc.
Zielgruppe
Editions-Typ
Produkt-Hinweis
Maße
Höhe: 253 mm
Breite: 179 mm
Dicke: 21 mm
Gewicht
ISBN-13
978-1-4932-2693-1 (9781493226931)
Schweitzer Klassifikation
Autor*in
Michael Kofler is a programmer and one of the most successful and versatile computing authors in the German-speaking world. His current topics include AI, Linux, Docker, Git, hacking and security, Raspberry Pi, and the programming languages Swift, Java, Python, and Kotlin. Michael also teaches at the Joanneum University of Applied Sciences in Kapfenberg, Austria.
Bernd Öggl is an experienced system administrator and programmer. He enjoys experimenting with new technologies and works with AI in software development using GitHub Copilot. He is particularly interested in local large language models (LLMs) and advancements such as OpenHands and retrieval-augmented generation (RAG).
Sebastian Springer is a JavaScript engineer at MaibornWolff. In addition to developing and designing both client-side and server-side JavaScript applications, he focuses on imparting knowledge. He inspires enthusiasm for professional development with JavaScript as a lecturer for JavaScript, a speaker at numerous conferences, and an author. Sebastian was previously a team leader at Mayflower GmbH, a premier web development agency in Germany. He was responsible for project and team management, architecture, and customer care for companies such as Nintendo Europe and Siemens.
... Preface ... 17
... Local Execution of Language Models ... 17
... Coding with AI Support for Advanced Users ... 18
... AI Makes Mistakes and Hallucinates ... 19
... The Three Stages of Using AI ... 19
... There's No Getting around AI Tools ... 20
Part I ... Coding with AI Support ... 23
1 ... Introduction ... 25
1.1 ... Coding via Chat ... 25
1.2 ... The Art of Prompting ... 34
1.3 ... Code Wizards ... 41
1.4 ... Chat or Wizard? ... 52
1.5 ... Basic Principles of Large Language Models ... 53
2 ... Pair Programming ... 67
2.1 ... Structuring Code into Functions ... 68
2.2 ... Example: IBAN Validation ... 76
2.3 ... Object-Oriented Programming ... 83
2.4 ... Example: Quiz ... 91
2.5 ... Example: Solving Sudoku ... 97
3 ... Debugging ... 107
3.1 ... Web Applications ... 108
3.2 ... App Development ... 116
3.3 ... Developing on Raspberry Pi ... 119
3.4 ... Visual Studio and Visual Studio Code ... 122
3.5 ... Conclusion ... 125
4 ... Refactoring ... 127
4.1 ... Introduction to Refactoring ... 127
4.2 ... Refactoring Using AI Tools ... 128
4.3 ... Best Practices ... 141
4.4 ... Conclusion ... 142
5 ... Testing Software ... 145
5.1 ... Generating Test Data ... 146
5.2 ... AI-Supported Test Automation ... 149
5.3 ... Test-Driven Development with AI ... 155
5.4 ... Using Dependencies ... 161
5.5 ... Optimizing Tests ... 167
5.6 ... End-to-End Tests ... 174
5.7 ... Conclusion ... 178
6 ... Documenting Software ... 179
6.1 ... Challenges with Documentation ... 180
6.2 ... Inline Documentation ... 181
6.3 ... Function and Class Documentation ... 184
6.4 ... API Documentation ... 187
6.5 ... Outdated Documentation ... 191
6.6 ... Conclusion ... 194
7 ... Databases ... 195
7.1 ... Database Design ... 195
7.2 ... SQL Commands ... 205
7.3 ... Administration ... 213
7.4 ... Client Programming ... 219
8 ... Scripting and System Administration ... 221
8.1 ... Scripting ... 221
8.2 ... Example: Converting a Python Script to PHP Code ... 228
8.3 ... Regular Expressions ... 230
8.4 ... System Administration ... 234
8.5 ... Example: "wget" Script Plus "tmpfs" Configuration ... 240
8.6 ... Calling GitHub Copilot and ChatGPT in the Terminal ... 245
Part II ... Local Language Models and Advanced AI Tools ... 251
9 ... Executing Language Models Locally ... 253
9.1 ... Spoiled for Choice of Large Language Model ... 254
9.2 ... GPT4All ... 259
9.3 ... Ollama ... 262
9.4 ... Open WebUI for Ollama ... 267
9.5 ... Continue ... 275
9.6 ... Ollama API ... 277
9.7 ... Tabby ... 280
9.8 ... Conclusion ... 282
10 ... Automated Code Processing ... 285
10.1 ... OpenAI API ... 286
10.2 ... Ollama API ... 297
10.3 ... Groq API ... 299
10.4 ... Example: Automated Commenting of Code ... 301
10.5 ... Example: From Python 2 to Python 3 ... 308
11 ... Level 3 Tools: OpenHands and Aider ... 313
11.1 ... OpenHands ... 314
11.2 ... Using OpenHands ... 320
11.3 ... Aider ... 323
11.4 ... Using Aider ... 328
12 ... Retrieval-Augmented Generation and Text-to-SQL ... 337
12.1 ... RAG Quick Start ... 338
12.2 ... The Viel-Falter (Many Butterflies) Project ... 341
12.3 ... Loading Documents ... 343
12.4 ... Creating an Index ... 345
12.5 ... Vector Store Databases ... 348
12.6 ... RAG Queries ... 351
12.7 ... Text-to-SQL ... 355
13 ... Risks and Outlook ... 367
13.1 ... Issues and Limitations of Using AI Tools ... 367
13.2 ... Exemplary AI Failure ... 370
13.3 ... Ethical Issues ... 381
13.4 ... Conclusions and Outlook ... 384
... The Authors ... 389
... Index ... 391
