feat: Add Expert Transformation Agent with multi-expert perspective system

- Backend: Add expert transformation router with 3-step SSE pipeline
  - Step 0: Generate diverse expert team (random domains)
  - Step 1: Each expert generates keywords for attributes
  - Step 2: Batch generate descriptions for expert keywords
- Backend: Add simplified prompts for reliable JSON output
- Frontend: Add TransformationPanel with React Flow visualization
- Frontend: Add TransformationInputPanel for expert configuration
  - Expert count (2-8), keywords per expert (1-3)
  - Custom expert domains support
- Frontend: Add expert keyword nodes with expert badges
- Frontend: Improve description card layout (wider cards, more spacing)
- Frontend: Add fallback for missing descriptions with visual indicators

🤖 Generated with [Claude Code](https://claude.com/claude-code)

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

backend/app/prompts/expert_transformation_prompt.py

@@ -0,0 +1,78 @@
+"""Expert Transformation Agent 提示詞模組"""
+
+from typing import List, Optional
+
+
+def get_expert_generation_prompt(
+    query: str,
+    categories: List[str],
+    expert_count: int,
+    custom_experts: Optional[List[str]] = None
+) -> str:
+    """Step 0: 生成專家團隊（不依賴主題，純隨機多元）"""
+    custom_text = ""
+    if custom_experts and len(custom_experts) > 0:
+        custom_text = f"（已指定：{', '.join(custom_experts[:expert_count])}）"
+
+    return f"""/no_think
+隨機組建 {expert_count} 個來自完全不同領域的專家團隊{custom_text}。
+
+回傳 JSON：
+{{"experts": [{{"id": "expert-0", "name": "職業", "domain": "領域", "perspective": "角度"}}, ...]}}
+
+規則：
+- id 為 expert-0 到 expert-{expert_count - 1}
+- name 填寫職業名稱（非人名），2-5字
+- 各專家的 domain 必須來自截然不同的領域，越多元越好"""
+
+
+def get_expert_keyword_generation_prompt(
+    category: str,
+    attribute: str,
+    experts: List[dict],  # List[ExpertProfile]
+    keywords_per_expert: int = 1
+) -> str:
+    """Step 1: 專家視角關鍵字生成"""
+    experts_info = ", ".join([f"{exp['id']}:{exp['name']}({exp['domain']})" for exp in experts])
+
+    return f"""/no_think
+專家團隊：{experts_info}
+屬性：「{attribute}」（{category}）
+
+每位專家從自己的專業視角為此屬性生成 {keywords_per_expert} 個創新關鍵字（2-6字）。
+關鍵字要反映該專家領域的獨特思考方式。
+
+回傳 JSON：
+{{"keywords": [{{"keyword": "詞彙", "expert_id": "expert-X", "expert_name": "名稱"}}, ...]}}
+
+共需 {len(experts) * keywords_per_expert} 個關鍵字。"""
+
+
+def get_expert_batch_description_prompt(
+    query: str,
+    category: str,
+    expert_keywords: List[dict]  # List[ExpertKeyword]
+) -> str:
+    """Step 2: 批次生成專家關鍵字的描述"""
+    keywords_info = ", ".join([
+        f"{kw['expert_name']}:{kw['keyword']}"
+        for kw in expert_keywords
+    ])
+
+    # 建立 keyword -> (expert_id, expert_name) 的對照
+    keyword_expert_map = ", ".join([
+        f"{kw['keyword']}→{kw['expert_id']}/{kw['expert_name']}"
+        for kw in expert_keywords
+    ])
+
+    return f"""/no_think
+物件：「{query}」
+關鍵字（專家:詞彙）：{keywords_info}
+對照：{keyword_expert_map}
+
+為每個關鍵字生成創新描述（15-30字），說明如何將該概念應用到「{query}」上。
+
+回傳 JSON：
+{{"descriptions": [{{"keyword": "詞彙", "expert_id": "expert-X", "expert_name": "名稱", "description": "應用描述"}}, ...]}}
+
+共需 {len(expert_keywords)} 個描述。"""