Files
novelty-seeking/backend/app/prompts/attribute_prompt.py
gbanyan 91f7f41bc1 feat: Add dynamic category system for attribute analysis
Backend:
- Add CategoryMode enum with 4 modes (fixed_only, fixed_plus_custom, custom_only, dynamic_auto)
- Add Step 0 for LLM category analysis before attribute generation
- Implement dynamic prompts for Step 1/2 that work with N categories
- Add execute_step0(), resolve_final_categories(), assemble_dynamic_attribute_tree()
- Update SSE events to include step0_start, step0_complete, categories_resolved

Frontend:
- Add CategorySelector component with mode selection, custom category input, and category count slider
- Update types with CategoryDefinition, Step0Result, DynamicStep1Result, DynamicCausalChain
- Update api.ts with new SSE event handlers
- Update useAttribute hook with category parameters
- Integrate CategorySelector into InputPanel
- Fix mindmap to dynamically extract and display N categories (was hardcoded to 4)
- Add CSS styles for depth 5-8 to support more category levels

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

Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-02 23:04:35 +08:00

216 lines
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from typing import List, Optional, Dict
import json
DEFAULT_CATEGORIES = ["材料", "功能", "用途", "使用族群", "特性"]
CATEGORY_DESCRIPTIONS = {
"材料": "物件由什麼材料組成",
"功能": "物件能做什麼",
"用途": "物件在什麼場景使用",
"使用族群": "誰會使用這個物件",
"特性": "物件有什麼特徵",
}
def get_attribute_prompt(query: str, categories: Optional[List[str]] = None) -> str:
"""Generate prompt with causal chain structure."""
prompt = f"""分析「{query}」的屬性,以因果鏈方式呈現:材料→功能→用途→使用族群。
請列出 3-5 種材料,每種材料延伸出完整因果鏈。
JSON 格式:
{{"name": "{query}", "children": [{{"name": "材料名", "category": "材料", "children": [{{"name": "功能名", "category": "功能", "children": [{{"name": "用途名", "category": "用途", "children": [{{"name": "族群名", "category": "使用族群"}}]}}]}}]}}]}}
只回傳 JSON。"""
return prompt
def get_step1_attributes_prompt(query: str) -> str:
"""Step 1: 生成各類別的屬性列表(平行結構)"""
return f"""/no_think
分析「{query}」,列出以下四個類別的屬性。每個類別列出 3-5 個常見屬性。
只回傳 JSON格式如下
{{"materials": ["材料1", "材料2", "材料3"], "functions": ["功能1", "功能2", "功能3"], "usages": ["用途1", "用途2", "用途3"], "users": ["族群1", "族群2", "族群3"]}}
物件:{query}"""
def get_step2_causal_chain_prompt(
query: str,
materials: List[str],
functions: List[str],
usages: List[str],
users: List[str],
existing_chains: List[dict],
chain_index: int
) -> str:
"""Step 2: 生成單條因果鏈"""
existing_chains_text = ""
if existing_chains:
chains_list = [
f"- {c['material']}{c['function']}{c['usage']}{c['user']}"
for c in existing_chains
]
existing_chains_text = f"""
【已生成的因果鏈,請勿重複】
{chr(10).join(chains_list)}
"""
return f"""/no_think
為「{query}」生成第 {chain_index} 條因果鏈。
【可選材料】{', '.join(materials)}
【可選功能】{', '.join(functions)}
【可選用途】{', '.join(usages)}
【可選族群】{', '.join(users)}
{existing_chains_text}
【規則】
1. 從每個類別選擇一個屬性,組成合理的因果鏈
2. 因果關係必須合邏輯(材料決定功能,功能決定用途,用途決定族群)
3. 不要與已生成的因果鏈重複
只回傳 JSON
{{"material": "選擇的材料", "function": "選擇的功能", "usage": "選擇的用途", "user": "選擇的族群"}}"""
def get_flat_attribute_prompt(query: str, categories: Optional[List[str]] = None) -> str:
"""Generate prompt with flat/parallel categories (original design)."""
cats = categories if categories else DEFAULT_CATEGORIES
# Build category list
category_lines = []
for cat in cats:
desc = CATEGORY_DESCRIPTIONS.get(cat, f"{cat}的相關屬性")
category_lines.append(f"- {cat}{desc}")
categories_text = "\n".join(category_lines)
prompt = f"""/no_think
你是一個物件屬性分析專家。請將用戶輸入的物件拆解成以下屬性類別。
【必須包含的類別】
{categories_text}
【重要】回傳格式必須是合法的 JSON每個節點都必須有 "name" 欄位:
```json
{{
"name": "物件名稱",
"children": [
{{
"name": "類別名稱",
"children": [
{{"name": "屬性1"}},
{{"name": "屬性2"}}
]
}}
]
}}
```
只回傳 JSON不要有任何其他文字。
用戶輸入:{query}"""
return prompt
# ===== Dynamic category system prompts =====
def get_step0_category_analysis_prompt(query: str, suggested_count: int = 3) -> str:
"""Step 0: LLM 分析建議類別"""
return f"""/no_think
分析「{query}」,建議 {suggested_count} 個最適合的屬性類別來描述它。
【常見類別參考】材料、功能、用途、使用族群、特性、形狀、顏色、尺寸、品牌、價格區間
【重要】
1. 選擇最能描述此物件本質的類別
2. 類別之間應該有邏輯關係(如:材料→功能→用途)
3. 不要選擇過於抽象或重複的類別
只回傳 JSON
{{
"categories": [
{{"name": "類別1", "description": "說明1", "order": 0}},
{{"name": "類別2", "description": "說明2", "order": 1}}
]
}}
物件:{query}"""
def get_step1_dynamic_attributes_prompt(
query: str,
categories: List # List[CategoryDefinition]
) -> str:
"""動態 Step 1 - 根據類別列表生成屬性"""
# 按 order 排序並構建描述
sorted_cats = sorted(categories, key=lambda x: x.order if hasattr(x, 'order') else x.get('order', 0))
category_desc = "\n".join([
f"- {cat.name if hasattr(cat, 'name') else cat['name']}: {cat.description if hasattr(cat, 'description') else cat.get('description', '相關屬性')}"
for cat in sorted_cats
])
category_keys = [cat.name if hasattr(cat, 'name') else cat['name'] for cat in sorted_cats]
json_template = {cat: ["屬性1", "屬性2", "屬性3"] for cat in category_keys}
return f"""/no_think
分析「{query}」,列出以下類別的屬性。每個類別列出 3-5 個常見屬性。
【類別列表】
{category_desc}
只回傳 JSON
{json.dumps(json_template, ensure_ascii=False, indent=2)}
物件:{query}"""
def get_step2_dynamic_causal_chain_prompt(
query: str,
categories: List, # List[CategoryDefinition]
attributes_by_category: Dict[str, List[str]],
existing_chains: List[Dict[str, str]],
chain_index: int
) -> str:
"""動態 Step 2 - 生成動態類別的因果鏈"""
sorted_cats = sorted(categories, key=lambda x: x.order if hasattr(x, 'order') else x.get('order', 0))
# 構建可選屬性
available_attrs = "\n".join([
f"{cat.name if hasattr(cat, 'name') else cat['name']}{', '.join(attributes_by_category.get(cat.name if hasattr(cat, 'name') else cat['name'], []))}"
for cat in sorted_cats
])
# 已生成的因果鏈
existing_text = ""
if existing_chains:
chains_list = [
"".join([chain.get(cat.name if hasattr(cat, 'name') else cat['name'], '?') for cat in sorted_cats])
for chain in existing_chains
]
existing_text = f"\n【已生成,請勿重複】\n" + "\n".join([f"- {c}" for c in chains_list])
# JSON 模板
json_template = {cat.name if hasattr(cat, 'name') else cat['name']: f"選擇的{cat.name if hasattr(cat, 'name') else cat['name']}" for cat in sorted_cats}
return f"""/no_think
為「{query}」生成第 {chain_index} 條因果鏈。
【可選屬性】
{available_attrs}
{existing_text}
【規則】
1. 從每個類別選擇一個屬性
2. 因果關係必須合理
3. 不要重複
只回傳 JSON
{json.dumps(json_template, ensure_ascii=False, indent=2)}"""