chore: save local changes

backend/app/prompts/expert_transformation_prompt.py

@@ -1,34 +1,68 @@
-"""Expert Transformation Agent 提示詞模組"""
+"""Expert Transformation Agent prompts module - Bilingual support"""
 
 from typing import List, Optional
+from .language_config import LanguageType
 
 
 def get_expert_generation_prompt(
     query: str,
     categories: List[str],
     expert_count: int,
-    custom_experts: Optional[List[str]] = None
+    custom_experts: Optional[List[str]] = None,
+    lang: LanguageType = "zh"
 ) -> str:
-    """Step 0: 生成專家團隊（不依賴主題，純隨機多元）"""
+    """Step 0: Generate expert team (not dependent on topic, purely random and diverse)"""
     import time
     import random
 
-    custom_text = ""
-    if custom_experts and len(custom_experts) > 0:
-        custom_text = f"（已指定：{', '.join(custom_experts[:expert_count])}）"
-
-    # 加入時間戳和隨機數來增加多樣性
+    # Add timestamp and random number for diversity
     seed = int(time.time() * 1000) % 10000
-    diversity_hints = [
-        "冷門、非主流、跨領域",
-        "罕見職業、新興領域、邊緣學科",
-        "非傳統、創新、小眾專業",
-        "未來趨向、實驗性、非常規",
-        "跨文化、混合領域、獨特視角"
-    ]
-    hint = random.choice(diversity_hints)
 
-    return f"""/no_think
+    if lang == "en":
+        custom_text = ""
+        if custom_experts and len(custom_experts) > 0:
+            custom_text = f" (Specified: {', '.join(custom_experts[:expert_count])})"
+
+        diversity_hints = [
+            "obscure, non-mainstream, cross-disciplinary",
+            "rare occupations, emerging fields, fringe disciplines",
+            "unconventional, innovative, niche specialties",
+            "future-oriented, experimental, non-traditional",
+            "cross-cultural, hybrid fields, unique perspectives"
+        ]
+        hint = random.choice(diversity_hints)
+
+        return f"""/no_think
+Randomly assemble a team of {expert_count} experts from completely different fields{custom_text}.
+
+[Innovation Requirements] (Random seed: {seed})
+- Prioritize {hint} experts
+- Avoid common professions (such as doctors, engineers, teachers, lawyers, etc.)
+- Each expert must be from a completely unrelated field
+- The rarer and more innovative, the better
+
+Return JSON:
+{{"experts": [{{"id": "expert-0", "name": "profession", "domain": "field", "perspective": "viewpoint"}}, ...]}}
+
+Rules:
+- id should be expert-0 to expert-{expert_count - 1}
+- name is the profession name (not a person's name), 2-5 words
+- domain should be specific and unique, no duplicate types"""
+    else:
+        custom_text = ""
+        if custom_experts and len(custom_experts) > 0:
+            custom_text = f"（已指定：{', '.join(custom_experts[:expert_count])}）"
+
+        diversity_hints = [
+            "冷門、非主流、跨領域",
+            "罕見職業、新興領域、邊緣學科",
+            "非傳統、創新、小眾專業",
+            "未來趨向、實驗性、非常規",
+            "跨文化、混合領域、獨特視角"
+        ]
+        hint = random.choice(diversity_hints)
+
+        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}。
 
 【創新要求】（隨機種子:{seed}）
@@ -50,13 +84,39 @@ def get_expert_keyword_generation_prompt(
     category: str,
     attribute: str,
     experts: List[dict],  # List[ExpertProfile]
-    keywords_per_expert: int = 1
+    keywords_per_expert: int = 1,
+    lang: LanguageType = "zh"
 ) -> str:
-    """Step 1: 專家視角關鍵字生成"""
-    # 建立專家列表，格式更清晰
+    """Step 1: Expert perspective keyword generation"""
+    # Build expert list in clearer format
     experts_list = "\n".join([f"- {exp['id']}: {exp['name']}" for exp in experts])
 
-    return f"""/no_think
+    if lang == "en":
+        return f"""/no_think
+You need to play the role of the following experts to generate innovative keywords for an attribute:
+
+[Expert List]
+{experts_list}
+
+[Task]
+Attribute: "{attribute}" (Category: {category})
+
+For each expert, please:
+1. First understand the professional background, knowledge domain, and work content of that profession
+2. Think about "{attribute}" from that profession's unique perspective
+3. Generate {keywords_per_expert} innovative keyword(s) related to that specialty (2-6 words)
+
+Keywords must reflect that expert's professional thinking style, for example:
+- Accountant viewing "movement" → "cash flow", "cost-benefit"
+- Architect viewing "movement" → "circulation design", "spatial flow"
+- Psychologist viewing "movement" → "behavioral motivation", "emotional transition"
+
+Return JSON:
+{{"keywords": [{{"keyword": "term", "expert_id": "expert-X", "expert_name": "name"}}, ...]}}
+
+Total of {len(experts) * keywords_per_expert} keywords needed, each keyword must be clearly related to the corresponding expert's professional field."""
+    else:
+        return f"""/no_think
 你需要扮演以下專家，為屬性生成創新關鍵字：
 
 【專家名單】
@@ -86,13 +146,29 @@ def get_single_description_prompt(
     keyword: str,
     expert_id: str,
     expert_name: str,
-    expert_domain: str
+    expert_domain: str,
+    lang: LanguageType = "zh"
 ) -> str:
-    """Step 2: 為單一關鍵字生成描述"""
-    # 如果 domain 是通用的，就只用職業名稱
-    domain_text = f"（{expert_domain}領域）" if expert_domain and expert_domain != "Professional Field" else ""
+    """Step 2: Generate description for a single keyword"""
+    if lang == "en":
+        # If domain is generic, just use profession name
+        domain_text = f" ({expert_domain} field)" if expert_domain and expert_domain != "Professional Field" else ""
 
-    return f"""/no_think
+        return f"""/no_think
+You are a {expert_name}{domain_text}.
+
+Task: Generate an innovative application description for "{query}".
+Keyword: {keyword}
+
+From your professional perspective, explain how to apply the concept of "{keyword}" to "{query}". The description should be specific, creative, 15-30 words.
+
+Return JSON only, no other text:
+{{"description": "your innovative application description"}}"""
+    else:
+        # 如果 domain 是通用的，就只用職業名稱
+        domain_text = f"（{expert_domain}領域）" if expert_domain and expert_domain != "Professional Field" else ""
+
+        return f"""/no_think
 你是一位{expert_name}{domain_text}。
 
 任務：為「{query}」生成一段創新應用描述。