Responsive Assistant for Navigating and Guiding Engineering with Rigor (RANGER)

Summary

RANGER (Responsive Assistant for Navigating and Guiding Engineering with Rigor) is a Python-based auto-response assistant that integrates with the GitHub API and a vector database to triage and answer new GitHub Discussions in the MOOSE ecosystem. When a new discussion is created, RANGER embeds the title (and optionally body) and retrieves semantically similar prior discussions from an indexed corpus of historical threads and documentation. It can then present the most relevant posts to the user or draft suggested replies for maintainers to review. The index is periodically refreshed (e.g., monthly) to incorporate new conversations, keeping suggestions aligned with the latest community knowledge. Built entirely on open-source tooling and designed to align with MOOSE workflows, RANGER can be configured to extend to other GitHub projects with Discussions enabled.

Solution

• Automated retrieval of similar threads: Uses vector search on prior discussions (titles + content) to surface near-duplicates and closely related topics for each new post.
• Suggested replies and links: Provides the asker (and/or moderators) with the top relevant prior posts so they can self-resolve or quickly confirm a response.
• Scheduled corpus updates: Regularly re-indexes new discussions to keep recommendations current without manual curation.
• Open-source, MOOSE-aware design: Tailored to MOOSE repositories and compatible with common open-source stacks for easy adoption and contribution.

Key Advantages

• Reduced time-to-answer: Faster first responses by pointing users to high-quality, already-accepted solutions.
• Developer efficiency: Offloads repetitive Q&A so maintainers can focus on novel, complex issues.
• Higher answer quality: Consistent, evidence-backed replies anchored in the community’s own prior discussions.
• Scalable across projects: Can be configured for other GitHub repositories using Discussions, not just MOOSE.
• Open-source alignment: Matches the licensing philosophy and collaboration norms of the MOOSE community.

Market Applications

• MOOSE core and MOOSE-based applications: Community support triage, onboarding assistance, and canonical answer surfacing.
• Open-source scientific and engineering projects: Any GitHub project with recurring questions in Discussions (e.g., simulation frameworks, HPC tools).
• Internal enterprise repos using GitHub Discussions: Self-service knowledge retrieval for product support and dev-tools teams.
• Academic collaborations and consortia: Faster peer support for research codebases where staff time is limited.

Access

This software is available as open-source and can be accessed through the software's GitHub Repository.