Phase B1: multi-tag groupings model (backend)

Three-layer organization: primary topic (one per article, for ranking and
brief balance) + grouping tags (1-4 per article from a controlled vocabulary,
the organic "wandering" axis) + tonal flavor.

- taxonomy: add technology + learning topics; 4 calm tag families
  (Discovery & Wonder, People & Kindness, Solutions & Progress, Mind & Craft)
  defined in code, not the DB; ALLOWED_TAGS union + coerce_tags validation.
- db: article_tags(article_id, tag) join table + tag index.
- llm: tags added to the classifier json_schema (enum-constrained, maxItems 4)
  and system prompt; normalize_scores coerces tags; upsert_article_score
  replaces a row's tags atomically on every (re)classification.
- queries: feed gains a tag filter and exposes tags via group_concat; tag_counts.
- api: Article.tags, feed tag param, and /api/families with per-tag counts.
- tests: coerce/normalize/upsert/tag-filter/reclassify-replace/tag_counts +
  /api/families. 99 passing.

Corpus reclassify (re-tag + new primary topics) runs separately against the
local LLM. Frontend (B2) pairs with this; the live site is unchanged until then.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

tests/test_api.py

@@ -80,3 +80,10 @@ def test_feed_excludes_dismissed(client):
     r = client.get("/api/feed", params={"exclude": "1"})
     ids = [i["id"] for i in r.json()["items"]]
     assert 1 not in ids
+
+
+def test_families_endpoint(client):
+    fams = client.get("/api/families").json()
+    names = [f["name"] for f in fams]
+    assert "Discovery & Wonder" in names
+    assert all("tags" in f and isinstance(f["tags"], list) for f in fams)