feat: Add 1-5 star rating to ZOPK news AI evaluation

- Add ai_relevance_score column (1-5) to zopk_news table
- Update AI prompt to return score with detailed criteria:
  * 1 star = very weak (loose connection to region/industry)
  * 2 stars = weak (general industry news)
  * 3 stars = medium (relates to ZOPK industry but not directly)
  * 4 stars = strong (directly about ZOPK investments/companies)
  * 5 stars = perfect (main topic is ZOPK, Kongsberg, offshore Baltic)
- Display star ratings in admin dashboard with color-coded badges
- Score >= 3 marks news as relevant, < 3 as not relevant

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

database.py

@@ -1781,6 +1781,7 @@ class ZOPKNews(Base):
 
     # AI Relevance Evaluation (Gemini)
     ai_relevant = Column(Boolean)  # True = relevant to ZOPK, False = not relevant, NULL = not evaluated
+    ai_relevance_score = Column(Integer)  # 1-5 stars: 1=weak match, 5=perfect match
     ai_evaluation_reason = Column(Text)  # AI's explanation of relevance decision
     ai_evaluated_at = Column(DateTime)  # When AI evaluation was performed
     ai_model = Column(String(100))  # Which AI model was used (e.g., gemini-2.0-flash)

database/migrations/005_zopk_knowledge_base.sql

@@ -446,8 +446,18 @@ BEGIN
     END IF;
 END $$;
 
+-- AI relevance score (1-5 stars: 1=weak, 5=perfect match)
+DO $$
+BEGIN
+    IF NOT EXISTS (SELECT 1 FROM information_schema.columns
+                   WHERE table_name = 'zopk_news' AND column_name = 'ai_relevance_score') THEN
+        ALTER TABLE zopk_news ADD COLUMN ai_relevance_score INTEGER CHECK (ai_relevance_score >= 1 AND ai_relevance_score <= 5);
+    END IF;
+END $$;
+
 -- Index for AI relevance filtering
 CREATE INDEX IF NOT EXISTS idx_zopk_news_ai_relevant ON zopk_news(ai_relevant);
+CREATE INDEX IF NOT EXISTS idx_zopk_news_ai_score ON zopk_news(ai_relevance_score);
 
 -- ============================================================
 -- MIGRATION COMPLETE

templates/admin/zopk_dashboard.html

@@ -194,6 +194,23 @@
         color: #991b1b;
     }
 
+    /* Star rating display */
+    .ai-stars {
+        display: inline-flex;
+        gap: 1px;
+        font-size: 11px;
+        letter-spacing: -1px;
+    }
+
+    .ai-stars .star-filled { color: #f59e0b; }
+    .ai-stars .star-empty { color: #d1d5db; }
+
+    .ai-badge.score-5 { background: #dcfce7; color: #166534; }
+    .ai-badge.score-4 { background: #d1fae5; color: #047857; }
+    .ai-badge.score-3 { background: #fef3c7; color: #92400e; }
+    .ai-badge.score-2 { background: #fee2e2; color: #b91c1c; }
+    .ai-badge.score-1 { background: #fecaca; color: #991b1b; }
+
     /* AI Evaluation Modal */
     .modal-icon {
         font-size: 48px;
@@ -964,10 +981,15 @@
                     {% elif news.status == 'rejected' %}
                     <span class="confidence-badge low">✗ Odrzucony</span>
                     {% endif %}
-                    {# AI Evaluation badge #}
+                    {# AI Evaluation badge with star rating #}
                     {% if news.ai_relevant is not none %}
-                    <span class="ai-badge {{ 'relevant' if news.ai_relevant else 'not-relevant' }}" title="{{ news.ai_evaluation_reason or '' }}">
-                        🤖 {{ 'Pasuje' if news.ai_relevant else 'Nie pasuje' }}
+                    <span class="ai-badge score-{{ news.ai_relevance_score or 3 }}" title="{{ news.ai_evaluation_reason or '' }}">
+                        🤖
+                        <span class="ai-stars">
+                            {% for i in range(1, 6) %}
+                                <span class="{{ 'star-filled' if i <= (news.ai_relevance_score or 0) else 'star-empty' }}">★</span>
+                            {% endfor %}
+                        </span>
                     </span>
                     {% endif %}
                 </div>

zopk_news_service.py

@@ -563,15 +563,27 @@ Data: {date}
 
 **Twoje zadanie:**
 1. Oceń czy artykuł dotyczy ZOPK lub powiązanych tematów
-2. Odpowiedz TYLKO w formacie JSON (bez żadnego innego tekstu):
+2. Przyznaj ocenę od 1 do 5 gwiazdek:
+   - ⭐ 1 = Bardzo słabo powiązany (luźna styczność z regionem/przemysłem)
+   - ⭐⭐ 2 = Słabo powiązany (ogólne wiadomości branżowe)
+   - ⭐⭐⭐ 3 = Średnio powiązany (dotyczy branży ZOPK, ale nie bezpośrednio projektu)
+   - ⭐⭐⭐⭐ 4 = Mocno powiązany (bezpośrednio dotyczy inwestycji lub kluczowych firm ZOPK)
+   - ⭐⭐⭐⭐⭐ 5 = Doskonale pasuje (główny temat to ZOPK, Kongsberg, offshore Baltic, elektrownia Choczewo)
 
-{{"relevant": true/false, "reason": "krótkie uzasadnienie po polsku (max 100 znaków)"}}
+3. Odpowiedz TYLKO w formacie JSON (bez żadnego innego tekstu):
+
+{{"relevant": true/false, "score": 1-5, "reason": "krótkie uzasadnienie po polsku (max 100 znaków)"}}
+
+Zasady:
+- relevant=true gdy score >= 3
+- relevant=false gdy score < 3
 
 Przykłady odpowiedzi:
-{{"relevant": true, "reason": "Dotyczy inwestycji Kongsberg w Rumi"}}
-{{"relevant": false, "reason": "Artykuł o lokalnych wydarzeniach kulturalnych"}}
-{{"relevant": true, "reason": "Informacje o farmach wiatrowych na Bałtyku"}}
-{{"relevant": false, "reason": "News sportowy bez związku z przemysłem"}}"""
+{{"relevant": true, "score": 5, "reason": "Bezpośrednio o inwestycji Kongsberg w Rumi"}}
+{{"relevant": true, "score": 4, "reason": "Dotyczy farm wiatrowych Baltic Power"}}
+{{"relevant": true, "score": 3, "reason": "Ogólne informacje o offshore wind w Polsce"}}
+{{"relevant": false, "score": 2, "reason": "Artykuł o energetyce, ale nie dotyczy Bałtyku"}}
+{{"relevant": false, "score": 1, "reason": "News sportowy bez związku z przemysłem"}}"""
 
 
 def evaluate_news_relevance(news_item, gemini_service=None) -> Dict:
@@ -632,21 +644,25 @@ def evaluate_news_relevance(news_item, gemini_service=None) -> Dict:
         json_match = re.search(r'\{[^{}]*\}', response)
         if json_match:
             result = json.loads(json_match.group())
+            # Extract score (1-5), default to 3 if not present
+            score = int(result.get('score', 3))
+            score = max(1, min(5, score))  # Clamp to 1-5 range
             return {
-                'relevant': bool(result.get('relevant', False)),
+                'relevant': bool(result.get('relevant', score >= 3)),
+                'score': score,
                 'reason': str(result.get('reason', ''))[:255],
                 'evaluated': True
             }
         else:
             logger.warning(f"Could not parse Gemini response: {response[:200]}")
-            return {'relevant': None, 'reason': 'Invalid AI response format', 'evaluated': False}
+            return {'relevant': None, 'score': None, 'reason': 'Invalid AI response format', 'evaluated': False}
 
     except json.JSONDecodeError as e:
         logger.error(f"JSON decode error: {e}")
-        return {'relevant': None, 'reason': f'JSON parse error: {str(e)[:50]}', 'evaluated': False}
+        return {'relevant': None, 'score': None, 'reason': f'JSON parse error: {str(e)[:50]}', 'evaluated': False}
     except Exception as e:
         logger.error(f"Gemini evaluation error: {e}")
-        return {'relevant': None, 'reason': f'AI error: {str(e)[:50]}', 'evaluated': False}
+        return {'relevant': None, 'score': None, 'reason': f'AI error: {str(e)[:50]}', 'evaluated': False}
 
 
 def evaluate_pending_news(db_session, limit: int = 50, user_id: int = None) -> Dict:
@@ -704,6 +720,7 @@ def evaluate_pending_news(db_session, limit: int = 50, user_id: int = None) -> D
 
         if result['evaluated']:
             news.ai_relevant = result['relevant']
+            news.ai_relevance_score = result.get('score')  # 1-5 stars
             news.ai_evaluation_reason = result['reason']
             news.ai_evaluated_at = datetime.now()
             news.ai_model = 'gemini-2.0-flash'