Adding a multivector named vector to an indexed collection breaks it (regression in 1.19.0): "Cannot merge vector storage: source is not a f32 multi-dense storage"

1. create collection: ok
2. 5000 points upserted; status=green indexed_vectors_count=5000 segments=4
3. PUT /collections/mv_add_repro/vectors/mv (multi): ok
4. set 'mv' on 2500 points via PUT /points/vectors
5. after 60 s: status=red segments=6 points_with_mv=2500
   query on 'mv': {'error': 'Wrong input: Conversion between multi and regular vectors failed'}

#!/usr/bin/env python3
"""Repro: adding a multivector named vector to an existing collection whose segments are already indexed.
Python stdlib only. Usage: repro.py [--url http://localhost:6333] [--on-disk] [--quant] [--kind multi|dense]"""
import argparse, json, random, time, urllib.request, urllib.error
ap = argparse.ArgumentParser()
ap.add_argument("--url", default="http://localhost:6333"); ap.add_argument("--on-disk", action="store_true")
ap.add_argument("--quant", action="store_true"); ap.add_argument("--kind", default="multi", choices=["multi", "dense"])
a = ap.parse_args(); B = a.url.rstrip("/") + "/collections/"
def req(method, path, body=None):
    r = urllib.request.Request(B + path, data=json.dumps(body).encode() if body is not None else None, method=method,
                               headers={"content-type": "application/json"})
    try: return json.load(urllib.request.urlopen(r, timeout=120))
    except urllib.error.HTTPError as e: return json.loads(e.read() or b"{}")
C, D = "mv_add_repro", 256
random.seed(1); vec = lambda: [random.random() for _ in range(D)]
req("DELETE", C)
cfg = {"vectors": {"a": {"size": D, "distance": "Cosine", "on_disk": a.on_disk}},
       "optimizers_config": {"default_segment_number": 4, "indexing_threshold": 100}}
if a.quant: cfg["quantization_config"] = {"scalar": {"type": "int8", "quantile": 0.99, "always_ram": True}}
print("1. create collection:", req("PUT", C, cfg)["status"])
for b in range(10):
    req("PUT", C + "/points?wait=true", {"points": [{"id": b * 500 + i, "vector": {"a": vec()}} for i in range(500)]})
t = time.time()
while time.time() - t < 300:
    r = req("GET", C)["result"]
    if r["status"] == "green" and (r.get("indexed_vectors_count") or 0) >= 5000: break
    time.sleep(2)
print(f"2. 5000 points upserted; status={r['status']} indexed_vectors_count={r.get('indexed_vectors_count')} segments={r['segments_count']}")
spec = {"dense": {"size": D, "distance": "Cosine"}}
if a.kind == "multi": spec["dense"]["multivector_config"] = {"comparator": "max_sim"}
print(f"3. PUT /collections/{C}/vectors/mv ({a.kind}):", req("PUT", C + "/vectors/mv", spec).get("status"))
mk = (lambda: [vec(), vec(), vec()]) if a.kind == "multi" else vec
for b in range(10):
    req("PUT", C + "/points/vectors?wait=true", {"points": [{"id": b * 500 + i, "vector": {"mv": mk()}} for i in range(0, 500, 2)]})
print("4. set 'mv' on 2500 points via PUT /points/vectors")
time.sleep(60)
r = req("GET", C)["result"]
q = req("POST", C + "/points/query", {"query": ([vec(), vec()] if a.kind == "multi" else vec()), "using": "mv", "limit": 3})
cnt = req("POST", C + "/points/count", {"exact": True, "filter": {"must": [{"has_vector": "mv"}]}})
print(f"5. after 60 s: status={r['status']} segments={r['segments_count']} points_with_mv={cnt.get('result', {}).get('count')}")
print("   query on 'mv':", "ok" if q.get("status") == "ok" else q.get("status"))