gbanyan
baea210109
- Add random seed and diversity hints to expert generation prompt - Explicitly avoid common professions (醫生、工程師、教師、律師等) - Change description generation from batch to one-by-one for reliability - Increase default temperature from 0.7 to 0.95 for more creative output - Add description_progress SSE event for real-time feedback 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
88 lines
2.7 KiB
Python
88 lines
2.7 KiB
Python
"""Expert Transformation Agent 提示詞模組"""
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from typing import List, Optional
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def get_expert_generation_prompt(
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query: str,
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categories: List[str],
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expert_count: int,
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custom_experts: Optional[List[str]] = None
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) -> str:
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"""Step 0: 生成專家團隊（不依賴主題，純隨機多元）"""
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import time
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import random
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custom_text = ""
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if custom_experts and len(custom_experts) > 0:
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custom_text = f"（已指定：{', '.join(custom_experts[:expert_count])}）"
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# 加入時間戳和隨機數來增加多樣性
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seed = int(time.time() * 1000) % 10000
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diversity_hints = [
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"冷門、非主流、跨領域",
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"罕見職業、新興領域、邊緣學科",
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"非傳統、創新、小眾專業",
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"未來趨向、實驗性、非常規",
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"跨文化、混合領域、獨特視角"
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]
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hint = random.choice(diversity_hints)
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return f"""/no_think
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隨機組建 {expert_count} 個來自完全不同領域的專家團隊{custom_text}。
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【創新要求】（隨機種子:{seed}）
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- 優先選擇{hint}的專家
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- 避免常見職業（如醫生、工程師、教師、律師等）
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- 每個專家必須來自完全不相關的領域
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- 越罕見、越創新越好
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回傳 JSON：
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{{"experts": [{{"id": "expert-0", "name": "職業", "domain": "領域", "perspective": "角度"}}, ...]}}
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規則：
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- id 為 expert-0 到 expert-{expert_count - 1}
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- name 填寫職業名稱（非人名），2-5字
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- domain 要具體且獨特，不可重複類型"""
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def get_expert_keyword_generation_prompt(
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category: str,
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attribute: str,
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experts: List[dict], # List[ExpertProfile]
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keywords_per_expert: int = 1
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) -> str:
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"""Step 1: 專家視角關鍵字生成"""
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experts_info = ", ".join([f"{exp['id']}:{exp['name']}({exp['domain']})" for exp in experts])
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return f"""/no_think
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專家團隊：{experts_info}
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屬性：「{attribute}」（{category}）
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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）。
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關鍵字要反映該專家領域的獨特思考方式。
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回傳 JSON：
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{{"keywords": [{{"keyword": "詞彙", "expert_id": "expert-X", "expert_name": "名稱"}}, ...]}}
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共需 {len(experts) * keywords_per_expert} 個關鍵字。"""
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def get_single_description_prompt(
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query: str,
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keyword: str,
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expert_id: str,
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expert_name: str,
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expert_domain: str
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) -> str:
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"""Step 2: 為單一關鍵字生成描述"""
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return f"""/no_think
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物件：「{query}」
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專家：{expert_name}（{expert_domain}）
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關鍵字：{keyword}
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從這位專家的視角，生成一段創新應用描述（15-30字），說明如何將「{keyword}」的概念應用到「{query}」上。
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回傳 JSON：
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{{"description": "應用描述"}}"""
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