Outreachy 2026 project for improving RPM packaging in Fedora, with RAG-enhanced models using RamaLama. This repo will house the artifacts developed for the project.
Justin Wheeler
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These `.pyc` files were accidentally committed alongside the docs changes. They are build artifacts that belong in `.gitignore` (which already excludes `__pycache__/`), not in the repository. Assisted-by: Claude Opus 4.6 (1M context) Signed-off-by: Justin Wheeler <jwheel@redhat.com> |
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Develop a SLM/LLM using Ramalama RAG based off Fedora RPM Packaging Guidelines
This is an Outreachy 2026 internship project with Fedora.
Project Description
This project focuses on applying machine learning to improve the quality and consistency of software packaging within the Fedora Project. The intern will enhance a model using RamaLama and its Retrieval Augmented Generation (RAG) capabilities to help identify deviations from established RPM packaging guidelines. This initiative introduces modern AI/ML practices into our infrastructure, serving as a high-impact example of open source best practices.
Project Team
- Coordinator: Justin Wheeler @jflory7
- Mentors: Dominik Kawka @dominikkawka, Carol Chen @cybette
- Intern: Francois Gonothi Toure @gtfrans2re
Use the issue tracker or ping the team members in #ai-ml:fedoraproject.org on Fedora Chat if you have any questions or issues.