feat: 加入 Value Scoring 自動估值

app.py

@@ -403,16 +403,48 @@ def generate_l0_l8(file_path: str, file_bytes: bytes) -> dict:
     }
 
     # L7: 分發決策 (黃金數據管線 + SN13 標準)
+    # 取得 L5 支柱分數用於估值
+    pillar_scores = result["L5_content_strategy"]["pillar_details"]
+    uniqueness = 0.72
+    desirability = 0.85
+    demand_level = "high"
+    quality = "platinum"
+
+    # ⭐ Value Scoring 自動估值
+    pillar_weights = {"P1_Hook": 0.30, "P2_Series": 0.25, "P3_Bond": 0.25, "P4_Lifestyle": 0.20}
+    pillar_value = sum(pillar_weights[k] * pillar_scores.get(k, 0) for k in pillar_weights)
+
+    demand_mult = {"high": 2.0, "medium": 1.0, "low": 0.5}.get(demand_level, 1.0)
+    scarcity_bonus = 1.0 + (uniqueness * 0.5)
+    demand_bonus = 1.0 + (desirability * 0.5)
+    total_demand_mult = min(max(demand_mult * scarcity_bonus * demand_bonus, 0.3), 4.0)
+
+    quality_mult = {"diamond": 3.0, "platinum": 2.0, "silver": 1.0, "legacy": 0.3}.get(quality, 1.0)
+    freshness_factor = 1.0  # 新上傳 = 最新鮮
+
+    base_value = pillar_value * total_demand_mult * quality_mult * freshness_factor
+
     result["L7_distribution_decision"] = {
         "ai_value_score": 72.5,
         "human_value_score": 68.0,
-        "quality_tier": "platinum",          # diamond/platinum/silver/legacy
-        "recommended_track": "Dual_Track",   # AI_Track/Human_Track/Dual_Track
+        "quality_tier": quality,              # diamond/platinum/silver/legacy
+        "recommended_track": "Dual_Track",    # AI_Track/Human_Track/Dual_Track
 
         # ⭐ SN13 標準欄位
-        "uniqueness_score": 0.72,            # 稀缺性 (SN13: 越少礦工擁有越高)
-        "desirability_match": 0.85,          # 需求匹配度 (是否在熱門需求列表)
-        "miner_demand_level": "high",        # 礦工需求等級
+        "uniqueness_score": uniqueness,       # 稀缺性 (SN13: 越少礦工擁有越高)
+        "desirability_match": desirability,   # 需求匹配度 (是否在熱門需求列表)
+        "miner_demand_level": demand_level,   # 礦工需求等級
+
+        # ⭐ Value Scoring 自動估值 (NEW!)
+        "valuation": {
+            "price_ai_training_usd": round(base_value * 0.50, 4),   # AI 訓練價
+            "price_commercial_usd": round(base_value * 2.00, 4),    # 商用授權價
+            "price_exclusive_usd": round(base_value * 10.00, 4),    # 獨家授權價
+            "demand_multiplier": round(total_demand_mult, 2),
+            "quality_multiplier": quality_mult,
+            "freshness_factor": freshness_factor,
+            "valuation_formula": "pillar_value × demand_mult × quality_mult × freshness"
+        },
 
         "priority_distribution": ["Bittensor_SN13", "HuggingFace", "SNS"],
         "distribution_rationale": "高稀缺性+高需求匹配，優先供應 SN13"