fix: search race condition + brand detection + contacts + reassess

- loadDomains(): add generation counter so stale auto-advance fetches
  cannot overwrite a newer user-triggered search result; snapshot filter
  state before the first await so URL reflects what was requested; add
  HTTP status check so backend errors surface as toasts rather than
  silent empty results; auto-advance now calls loadDomains() without
  await so the counter increments correctly per page advance

- beauty_ai: word-boundary regex for short brands (≤5 chars) to stop
  'ref' matching 'reference'/'refresh'/'prefer' etc.; merge phones,
  whatsapp and social_links from site_analyzer directly into result
  (more reliable than AI extraction); add contact_whatsapp and
  contact_social fields to AI JSON schema

- db: add requeue_beauty() for re-assessing already-assessed domains

- beauty_main: /api/beauty/reassess/batch endpoint using requeue_beauty

- index.html: Re-assess Selected bulk button, per-row ↺ button in
  Browse and Pipeline, WhatsApp + social links in Pipeline contact panel

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

app/beauty_ai.py

@@ -128,9 +128,22 @@ BEAUTY_CATEGORIES = [
 # ── Brand detection (fast pre-scan, no AI) ─────────────────────────────────────
 
 def detect_brands_in_text(text: str) -> list[str]:
-    """Find which brands from the universe appear in the scraped page text."""
+    """Find which brands from the universe appear in the scraped page text.
+
+    Short brands (≤5 chars) use word-boundary matching to avoid false positives
+    like 'ref' matching 'reference', 'prefer', 'refresh', etc.
+    """
     tl = text.lower()
-    return [b for b in BEAUTY_BRANDS if b.lower() in tl][:60]
+    result = []
+    for b in BEAUTY_BRANDS:
+        bl = b.lower()
+        if len(bl) <= 5:
+            if re.search(r'(?<![a-zA-Z0-9])' + re.escape(bl) + r'(?![a-zA-Z0-9])', tl):
+                result.append(b)
+        else:
+            if bl in tl:
+                result.append(b)
+    return result[:60]
 
 
 def get_dist_matches(detected: list[str]) -> list[str]:
@@ -247,6 +260,8 @@ Respond ONLY with valid JSON, no markdown, no text outside JSON:
   "dist_matches": ["OurBrand1","OurBrand2"],
   "contact_email": "email or empty string",
   "contact_phone": "phone or empty string",
+  "contact_whatsapp": "whatsapp link or empty string",
+  "contact_social": "primary social profile URL or empty string",
   "b2b_proposal": "1-2 sentence value proposition in Spanish referencing their categories and our matching brands",
   "outreach_subject": "short Spanish subject line referencing their business name",
   "outreach_email": "3-4 sentence ready-to-send email in Spanish. Mention their business, 1-2 specific brands from our portfolio that match their range, and a clear call to action (catálogo, muestra, llamada).",
@@ -336,12 +351,27 @@ async def assess_beauty_domain(analysis: dict) -> dict:
             if not result.get("detected_brands") and detected:
                 result["detected_brands"] = detected
 
+            # Always merge contact data directly from site_analyzer — more reliable
+            # than AI extraction since it uses regex against raw HTML
+            phones      = analysis.get("phones", [])
+            whatsapp    = analysis.get("whatsapp", [])
+            social_links = analysis.get("social_links", [])
+            if phones and not result.get("contact_phone"):
+                result["contact_phone"] = phones[0]
+            if whatsapp:
+                result["contact_whatsapp"] = "; ".join(whatsapp[:2])
+            if social_links:
+                result["contact_social"] = "; ".join(social_links[:3])
+
             logger.info("Beauty AI %s → quality=%s, dist_matches=%s",
                         domain, result.get("lead_quality"), result.get("dist_matches"))
             return result
 
         except Exception as e:
             logger.error("Beauty AI error %s: %s", domain, e)
+            phones   = analysis.get("phones", [])
+            whatsapp = analysis.get("whatsapp", [])
+            social   = analysis.get("social_links", [])
             return {
                 "error": str(e)[:300],
                 "is_relevant": False,
@@ -349,4 +379,7 @@ async def assess_beauty_domain(analysis: dict) -> dict:
                 "dist_matches": dist_match,
                 "detected_brands": detected,
                 "contact_email": "",
+                "contact_phone": phones[0] if phones else "",
+                "contact_whatsapp": "; ".join(whatsapp[:2]) if whatsapp else "",
+                "contact_social": "; ".join(social[:3]) if social else "",
             }