69fc7033f3
* docs: add rsyslog issue assistant build files
Add README and prompt used to build the external Issue Assistant that
drives rsyslog issue assistant which creates great and AI-friendly
GitHub issues. This improves triage readiness and contributor experience
without touching runtime code. The assistant itself is free via the
ChatGPT store and will be linked from documentation and other entry points.
Note that the use of the assistant directly benenfits rsyslog AI First
ecosystem which ensures high quality AI code generation support.
Before: repository had no assistant build inputs.
After: versioned prompt and README are present; assistant is distributed
externally.
Technical details:
- Add ai/rsyslog_issue_assistant/{README.md,base_prompt.txt}.
- Prompt yields ASCII-only JSON metadata plus a Markdown body aligned
with rsyslog templates; selects type, proposes repo, and adds minimal
labels (always includes needs-triage).
- Heuristics default to rsyslog/rsyslog; librelp is chosen when clearly
indicated by the report.
- No runtime, module, ABI, or testbench changes; docs-only assets.
- README points to a web helper page to be linked from CONTRIBUTING.md.
Co-authored-by: gemini-code-assist[bot]
AI and Machine Learning Tooling for rsyslog
This directory contains AI and Machine Learning (ML) tools that
Purpose
The ai directory is designated for a new generation of tooling that will
interface with rsyslog. It will house external AI and ML models and
applications. This approach ensures the rsyslog core remains lean and
robust while allowing for flexible and powerful extensions.
Current Status
No tools exist yet.
This directory and its README.md have been created to provide a
consistent and official location for this work as it progresses.
Active development is ongoing, and tools will be added here once they
reach a stable state.
Vision
Future tools in this directory will leverage artificial intelligence and machine learning for tasks like advanced log analysis, anomaly detection, and intelligent system monitoring. The goal is to enhance rsyslog's capabilities without integrating complex models directly into the core daemon.