Vowel families must be local

Slant/multi attachment, multi buckets, and unequal-length containment
fusion now require members within ~6-8 lines. "All Me" was chaining
Baby/Mercedes/loan/being/Daddy into one teal family across 110 lines;
vowel assonance is local evidence, not global. Perfect rhymes and
equal-key fusion stay global (a real rhyme carries any distance).

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

app.py

@@ -696,7 +696,8 @@ def analyze(draft: Draft):
 
     def attach_or_collect(t, key, bucket, gmap):
         gi = gmap.get((t["sid"], key))
-        if gi is not None:
+        if gi is not None and any(abs(m["line"] - t["line"]) <= 8
+                                  for m in raw_groups[gi]["toks"]):
             raw_groups[gi]["toks"].append(t)
             t["slant"] = True
             grouped.add(id(t))
@@ -819,16 +820,40 @@ def analyze(draft: Draft):
         attach_or_collect(p, key, by_multi, group_by_multi)
 
     for (sid, key), toks in by_par.items():
-        toks = [t for t in toks if id(t) not in grouped]
-        if len(toks) >= 2 and len({t["word"].split()[0] for t in toks}) >= 2:
-            raw_groups.append({"toks": toks, "slant": True, "key": key})
-            grouped.update(id(t) for t in toks)
+        toks = sorted((t for t in toks if id(t) not in grouped),
+                      key=lambda t: t["line"])
+        runs, cur = [], []
+        for t in toks:
+            if cur and t["line"] - cur[-1]["line"] > 6:
+                runs.append(cur)
+                cur = []
+            cur.append(t)
+        if cur:
+            runs.append(cur)
+        for run in runs:
+            if len(run) >= 2 and len({t["word"].split()[0] for t in run}) >= 2:
+                raw_groups.append({"toks": run, "slant": True, "key": key})
+                grouped.update(id(t) for t in run)
 
     # biggest buckets claim first (a token may sit in several via its
     # anchors); distinctness by anchor word, so the phrase "fire burns"
     # can't pose as a different word than the "fire" it starts with
     def _flush_multi(toks, key):
-        toks = [t for t in toks if id(t) not in grouped]
+        toks = sorted((t for t in toks if id(t) not in grouped),
+                      key=lambda t: t["line"])
+        # vowel evidence is local: split on gaps of more than 6 lines
+        runs, cur = [], []
+        for t in toks:
+            if cur and t["line"] - cur[-1]["line"] > 6:
+                runs.append(cur)
+                cur = []
+            cur.append(t)
+        if cur:
+            runs.append(cur)
+        for run in runs:
+            _flush_multi_run(run, key)
+
+    def _flush_multi_run(toks, key):
         if len(toks) < 2 or len({t["word"].split()[0] for t in toks}) < 2:
             return
         # an all-phrase bucket whose members mirror the same two word
@@ -1029,6 +1054,14 @@ def analyze(draft: Draft):
                 if (len(va) == 1 and len(vb) == 1
                         and not _sets_nest(_gtags(ai), _gtags(bi))):
                     continue
+                if va != vb:
+                    # containment (unequal lengths) is weaker evidence
+                    # than identity: the families must actually meet —
+                    # Baby (l23) never fuses with Daddy (l136)
+                    la = {t["line"] for t in raw_groups[ai]["toks"]}
+                    lb = {t["line"] for t in raw_groups[bi]["toks"]}
+                    if min(abs(x - y) for x in la for y in lb) > 8:
+                        continue
                 mparent[mfind(ai)] = mfind(bi)
 
     mclusters = defaultdict(list)

tests/test_rhymes.py

@@ -686,3 +686,15 @@ def test_forever_does_not_glue_to_sequential():
     assert "forever" not in seq and "ever" not in seq
     assert "question" not in seq and "extra" not in seq
     group_with(text, "style", "mile")
+
+
+def test_vowel_families_are_local():
+    # a 100-line gap can't chain a vowel family — Baby/Daddy/loan/being
+    # were one teal blob across all of "All Me"
+    text = "Baby girl I see you\n" + ("filler line here\n" * 100) + "my old daddy\n"
+    from collections import defaultdict
+    res = analyze(Draft(text=text))
+    bg = defaultdict(set)
+    for tok in res["tokens"]:
+        bg[tok["g"]].add(res["lines"][tok["l"]][tok["s"]:tok["e"]].lower())
+    assert not any({"baby", "daddy"} <= s for s in bg.values())