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/routers/content.py

@@ -111,6 +111,12 @@ def generate_content(
         "niche": character.niche,
         "topics": character.topics or [],
         "tone": character.tone or "professional",
+        "brand_voice": character.brand_voice,
+        "target_audience": character.target_audience,
+        "business_goals": character.business_goals,
+        "products_services": character.products_services,
+        "content_rules": character.content_rules or {},
+        "hashtag_profiles": character.hashtag_profiles or {},
     }
 
     base_url = _get_setting(db, "llm_base_url", current_user.id)
@@ -145,7 +151,19 @@ def generate_content(
             brief=request.brief,
         )
 
-        hashtags = generate_hashtags(text, llm, platform)
+        # Hashtag generation with profile support
+        ht_profile = char_dict.get("hashtag_profiles", {}).get(platform, {})
+        always_tags = ht_profile.get("always", [])
+        max_generated = ht_profile.get("max_generated", 12)
+        hashtags_generated = generate_hashtags(text, llm, platform, count=max_generated)
+        # Merge: always tags first, then generated (no duplicates)
+        seen = set()
+        hashtags = []
+        for tag in always_tags + hashtags_generated:
+            normalized = tag.lower()
+            if normalized not in seen:
+                seen.add(normalized)
+                hashtags.append(tag)
 
         affiliate_links_used: list[dict] = []
         if affiliate_link_dicts: