Crafting intelligent GitHub Bots
summary
Quarkus shows concrete bots built with Quarkus GitHub App Framework and Quarkus LangChain4j that run on real scale — the project logs 75,871 CI minutes, 43–44 jobs per PR and 1,000+ contributors — and demonstrates three working automations: a regex+AI language detector that comments and closes non‑English issues, a build‑report generator that aggregates 40 failing jobs and creates code annotations, and a screenshot‑to‑code pipeline that OCRs pasted screenshots into Java snippets. Tools, code and live demos all run and succeed.
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chapters (11)
- 0:00Introduction to GitHub bots
- 3:08The case for automation
- 7:14GitHub apps with Quarkus
- 10:35Developing a simple GitHub bot
- 17:41Solving complex project issues
- 21:48Integrating LLMs with LangChain4j
- 25:31AI-driven automation demos
- 35:56Image processing with AI
- 40:28Command-based assistance
- 46:26Automated issue triage
- 49:00Conclusion and takeaways
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