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When Pastures AI returns a diagnosis, responses include source citations — links to real GitHub issues that informed the answer. This is a key differentiator: every recommendation is traceable to an actual resolution, not hallucinated.

What citations look like

Each citation in the response displays:
  • Repository name — e.g., k3s-io/k3s
  • Issue number — e.g., #8921
  • Link — opens the GitHub issue in a new tab
  • Status badge — color-coded open or closed indicator
Sources
↗ k3s-io/k3s#8921        closed
↗ rancher/rancher#43156   open
Citations appear below the AI response text in a dedicated “Sources” section.

How citations are generated

Source citations are powered by the Oracle corpus. When a query is processed:
  1. The query is embedded and matched against 48,000+ indexed issue resolutions
  2. The top-k matching issues are retrieved from the vector database
  3. The LLM generates a grounded response using these issues as context
  4. The matching issues are returned as structured citation metadata
Each citation includes the repository, issue number, URL, and current status (open/closed).

Mode availability

Oracle

Full citations from the 48K+ issue corpus

Demo

Realistic demo citations (e.g., k3s-io/k3s#8921)

BYO Model

No citations — requires the Oracle corpus
BYO model mode connects to your own OpenAI-compatible endpoint. Since it doesn’t have access to the Oracle corpus, responses will not include source citations. The AI may still be useful for general Kubernetes questions, but answers are not grounded in verified resolutions.

Citation data structure

The AI drawer receives citations as part of the response payload:
interface Source {
  repo: string;        // "k3s-io/k3s"
  issueNumber: number; // 8921
  url: string;         // "https://github.com/k3s-io/k3s/issues/8921"
  status: 'open' | 'closed';
}
Status badges use color coding: green for closed (resolved), red for open (still active). This helps users gauge whether the referenced fix is a known-good resolution or an ongoing discussion.