feat: rich character profiles — brand voice, target, rules, hashtag profiles

Backend:
- Character model: add brand_voice, target_audience, business_goals,
  products_services, content_rules (JSON do/dont), hashtag_profiles (JSON)
- Content generation: inject full character context into LLM system prompt
  (voice, audience, goals, products, rules)
- Hashtag generation: merge always-on tags from profile with AI-generated tags
- Schema: update CharacterBase and CharacterUpdate with new fields

Frontend:
- CharacterForm: new sections "Identità e Voce", "Regole Contenuti",
  "Profili Hashtag" with dedicated editors
- RulesEditor: do/don't list with add/remove
- HashtagProfileEditor: per-platform tabs, fixed hashtags + max generated count
- All fields loaded on edit, saved on submit

DB migration: 6 new columns added to characters table

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

backend/app/models.py

@@ -48,6 +48,13 @@ class Character(Base):
     niche = Column(String(200), nullable=False)
     topics = Column(JSON, default=list)
     tone = Column(Text)
+    # Rich profile fields
+    brand_voice = Column(Text, nullable=True)        # how the character communicates (long description)
+    target_audience = Column(Text, nullable=True)     # who reads the content
+    business_goals = Column(Text, nullable=True)      # why they create content
+    products_services = Column(Text, nullable=True)   # what they offer
+    content_rules = Column(JSON, default=dict)        # {"do": [...], "dont": [...]}
+    hashtag_profiles = Column(JSON, default=dict)     # per-platform hashtag config
     visual_style = Column(JSON, default=dict)
     social_accounts = Column(JSON, default=dict)
     affiliate_links = Column(JSON, default=list)