{# FE2-4: related-work fragment — lazy-loaded into #corpus-related.

   Context:
     doi      — the seed paper's DOI (embedded literally in hx-get URLs; the
                {doi:path} route accepts "10.x/y" verbatim, so NO urlencode on
                the path. Query VALUES (mode) are urlencode'd — the FE2-2 lesson).
     mode     — active retrieval mode ("vector" | "graph" | "hybrid").
     related  — list of {doi, score[, title], source} dicts, or None for the
                no-data path. Each row carries an explicit `source`
                ("vector"|"graph"|"hybrid") set by how it was actually found;
                the per-row provenance pill below renders that truthfully so a
                vector neighbour is NEVER presented as a graph relationship.
                None means: graph/hybrid → graph-not-built notice; vector →
                no-embedded-neighbours notice.
     error    — True when the retrieval raised (generic notice, no detail leaked).

   All content is rendered through Jinja autoescape ONLY — never |safe.
#}
<div class="card" id="corpus-related-card">
  <h2>Related work</h2>

  {# Mode toggle: each link re-requests this fragment for a different retrieval
     mode and swaps itself back into #corpus-related. The DOI path is literal;
     the mode query value is urlencode'd. #}
  <p class="button-row" role="group" aria-label="Retrieval mode">
    {% for m in ["vector", "graph", "hybrid"] %}
    <a class="btn btn-secondary btn-sm{% if m == mode %} active{% endif %}"
       hx-get="/corpus/{{ doi }}/related?mode={{ m | urlencode }}"
       hx-target="#corpus-related"
       hx-swap="innerHTML"
       href="/corpus/{{ doi }}/related?mode={{ m | urlencode }}">{{ m }}</a>
    {% endfor %}
  </p>

  {% if error %}
  <p class="field-note">Could not load related work — check the server logs.</p>
  {% elif related is none %}
    {# No-data path is mode-specific so we never lie about why it's empty:
       graph/hybrid need the graph built; vector needs embeddings. #}
    {% if mode == "vector" %}
  <p class="field-note">
    No embedded neighbours found — this paper has no vector embeddings yet, so
    similar papers can't be computed. Run <code>lit-monitor brain-build</code>
    to embed the corpus.
  </p>
    {% else %}
  <p class="field-note">
    No knowledge graph is built yet, so related work cannot be computed. Run
    <code>lit-monitor graph backfill --all</code> to build the graph.
  </p>
    {% endif %}
  {% elif related %}
  <table class="papers-table">
    <thead>
      <tr><th>Paper</th><th>Via</th><th>Score</th></tr>
    </thead>
    <tbody>
      {% for item in related %}
      <tr>
        <td>
          {# DOI embedded literally in the detail-page link so the {doi:path}
             detail route matches. #}
          <a href="/corpus/{{ item.doi }}">{{ item.title or item.doi }}</a>
        </td>
        <td>
          {# Truthful per-result provenance: derived from each row's own
             `source` field (how it was actually retrieved), NOT from the active
             mode toggle. A vector neighbour is labelled as such even if the
             toggle were somehow inconsistent. #}
          {% if item.source == "vector" %}
          <span class="pill" title="found by embedding cosine similarity">via vector similarity</span>
          {% elif item.source == "graph" %}
          <span class="pill" title="found via the knowledge graph">via knowledge graph</span>
          {% elif item.source == "hybrid" %}
          <span class="pill" title="found by fusing vector + graph">via hybrid (vector + graph)</span>
          {% else %}
          <span class="muted">&mdash;</span>
          {% endif %}
        </td>
        <td><span class="score">{{ "%.3f" | format(item.score or 0 | float) }}</span></td>
      </tr>
      {% endfor %}
    </tbody>
  </table>
  {% else %}
  <p class="field-note">No related papers found for this mode.</p>
  {% endif %}
</div>