451 lines
15 KiB
Python
451 lines
15 KiB
Python
from typing import List, Optional, Dict
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import json
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from .language_config import (
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LanguageType,
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DEFAULT_CATEGORIES,
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CATEGORY_DESCRIPTIONS,
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)
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def get_default_categories(lang: LanguageType = "zh") -> List[str]:
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return DEFAULT_CATEGORIES.get(lang, DEFAULT_CATEGORIES["zh"])
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def get_category_descriptions(lang: LanguageType = "zh") -> Dict[str, str]:
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return CATEGORY_DESCRIPTIONS.get(lang, CATEGORY_DESCRIPTIONS["zh"])
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def get_attribute_prompt(
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query: str,
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categories: Optional[List[str]] = None,
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lang: LanguageType = "zh"
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) -> str:
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"""Generate prompt with causal chain structure."""
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if lang == "en":
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prompt = f"""Analyze the attributes of "{query}" in a causal chain format: Materials→Functions→Usages→User Groups.
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List 3-5 types of materials, each extending into a complete causal chain.
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JSON format:
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{{"name": "{query}", "children": [{{"name": "Material Name", "category": "Materials", "children": [{{"name": "Function Name", "category": "Functions", "children": [{{"name": "Usage Name", "category": "Usages", "children": [{{"name": "User Group Name", "category": "User Groups"}}]}}]}}]}}]}}
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Return JSON only."""
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else:
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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。
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請列出 3-5 種材料，每種材料延伸出完整因果鏈。
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JSON 格式：
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{{"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"}}]}}]}}]}}]}}
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只回傳 JSON。"""
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return prompt
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def get_step1_attributes_prompt(query: str, lang: LanguageType = "zh") -> str:
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"""Step 1: Generate attribute list for each category (parallel structure)"""
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if lang == "en":
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return f"""/no_think
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Analyze "{query}" and list attributes for the following four categories. List 3-5 common attributes for each category.
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Return JSON only, in the following format:
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{{"materials": ["material1", "material2", "material3"], "functions": ["function1", "function2", "function3"], "usages": ["usage1", "usage2", "usage3"], "users": ["user group1", "user group2", "user group3"]}}
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Object: {query}"""
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else:
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return f"""/no_think
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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。
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只回傳 JSON，格式如下：
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{{"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"]}}
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物件：{query}"""
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def get_step2_causal_chain_prompt(
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query: str,
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materials: List[str],
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functions: List[str],
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usages: List[str],
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users: List[str],
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existing_chains: List[dict],
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chain_index: int,
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lang: LanguageType = "zh"
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) -> str:
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"""Step 2: Generate a single causal chain"""
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existing_chains_text = ""
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if lang == "en":
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if existing_chains:
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chains_list = [
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f"- {c['material']} → {c['function']} → {c['usage']} → {c['user']}"
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for c in existing_chains
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]
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existing_chains_text = f"""
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[Already generated causal chains, do not repeat]
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{chr(10).join(chains_list)}
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"""
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return f"""/no_think
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Generate causal chain #{chain_index} for "{query}".
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[Available Materials] {', '.join(materials)}
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[Available Functions] {', '.join(functions)}
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[Available Usages] {', '.join(usages)}
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[Available User Groups] {', '.join(users)}
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{existing_chains_text}
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[Rules]
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1. Select one attribute from each category to form a logical causal chain
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2. The causal relationship must be logical (materials determine functions, functions determine usages, usages determine user groups)
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3. Do not repeat existing causal chains
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Return JSON only:
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{{"material": "selected material", "function": "selected function", "usage": "selected usage", "user": "selected user group"}}"""
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else:
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if existing_chains:
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chains_list = [
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f"- {c['material']} → {c['function']} → {c['usage']} → {c['user']}"
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for c in existing_chains
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]
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existing_chains_text = f"""
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【已生成的因果鏈，請勿重複】
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{chr(10).join(chains_list)}
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"""
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return f"""/no_think
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為「{query}」生成第 {chain_index} 條因果鏈。
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【可選材料】{', '.join(materials)}
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【可選功能】{', '.join(functions)}
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【可選用途】{', '.join(usages)}
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【可選族群】{', '.join(users)}
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{existing_chains_text}
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【規則】
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1. 從每個類別選擇一個屬性，組成合理的因果鏈
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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）
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3. 不要與已生成的因果鏈重複
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只回傳 JSON：
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{{"material": "選擇的材料", "function": "選擇的功能", "usage": "選擇的用途", "user": "選擇的族群"}}"""
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def get_flat_attribute_prompt(
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query: str,
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categories: Optional[List[str]] = None,
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lang: LanguageType = "zh"
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) -> str:
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"""Generate prompt with flat/parallel categories (original design)."""
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cats = categories if categories else get_default_categories(lang)
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cat_descs = get_category_descriptions(lang)
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# Build category list
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category_lines = []
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for cat in cats:
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desc = cat_descs.get(cat, f"Related attributes of {cat}" if lang == "en" else f"{cat}的相關屬性")
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category_lines.append(f"- {cat}: {desc}")
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categories_text = "\n".join(category_lines)
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if lang == "en":
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prompt = f"""/no_think
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You are an object attribute analysis expert. Please break down the user's input object into the following attribute categories.
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[Required Categories]
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{categories_text}
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[Important] The return format must be valid JSON, and each node must have a "name" field:
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```json
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{{
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"name": "Object Name",
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"children": [
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{{
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"name": "Category Name",
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"children": [
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{{"name": "Attribute 1"}},
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{{"name": "Attribute 2"}}
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]
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}}
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]
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}}
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```
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Return JSON only, no other text.
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User input: {query}"""
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else:
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prompt = f"""/no_think
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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。
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【必須包含的類別】
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{categories_text}
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【重要】回傳格式必須是合法的 JSON，每個節點都必須有 "name" 欄位：
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```json
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{{
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"name": "物件名稱",
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"children": [
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{{
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"name": "類別名稱",
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"children": [
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{{"name": "屬性1"}},
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{{"name": "屬性2"}}
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]
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}}
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]
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}}
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```
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只回傳 JSON，不要有任何其他文字。
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用戶輸入：{query}"""
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return prompt
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# ===== Dynamic category system prompts =====
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def get_step0_category_analysis_prompt(
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query: str,
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suggested_count: int = 3,
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exclude_categories: List[str] | None = None,
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lang: LanguageType = "zh"
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) -> str:
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"""Step 0: LLM analyzes and suggests categories"""
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if lang == "en":
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exclude_text = ""
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if exclude_categories:
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exclude_text = f"\n[Forbidden Categories] {', '.join(exclude_categories)} (These are already fixed categories, do not suggest duplicates)\n"
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return f"""/no_think
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Analyze "{query}" and suggest {suggested_count} most suitable attribute categories to describe it.
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[Common Category References] Characteristics, Shape, Color, Size, Brand, Price Range, Weight, Style, Occasion, Season, Technical Specifications
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{exclude_text}
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[Important]
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1. Choose categories that best describe the essence of this object
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2. Categories should have logical relationships
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3. Do not choose overly abstract or duplicate categories
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4. Must suggest creative categories different from the reference list
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Return JSON only:
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{{
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"categories": [
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{{"name": "Category1", "description": "Description1", "order": 0}},
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{{"name": "Category2", "description": "Description2", "order": 1}}
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]
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}}
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Object: {query}"""
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else:
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exclude_text = ""
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if exclude_categories:
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exclude_text = f"\n【禁止使用的類別】{', '.join(exclude_categories)}（這些已經是固定類別，不要重複建議）\n"
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return f"""/no_think
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分析「{query}」，建議 {suggested_count} 個最適合的屬性類別來描述它。
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【常見類別參考】特性、形狀、顏色、尺寸、品牌、價格區間、重量、風格、場合、季節、技術規格
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{exclude_text}
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【重要】
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1. 選擇最能描述此物件本質的類別
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2. 類別之間應該有邏輯關係
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3. 不要選擇過於抽象或重複的類別
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4. 必須建議與參考列表不同的、有創意的類別
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只回傳 JSON：
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{{
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"categories": [
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{{"name": "類別1", "description": "說明1", "order": 0}},
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{{"name": "類別2", "description": "說明2", "order": 1}}
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]
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}}
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物件：{query}"""
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def get_step1_dynamic_attributes_prompt(
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query: str,
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categories: List, # List[CategoryDefinition]
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lang: LanguageType = "zh"
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) -> str:
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"""Dynamic Step 1 - Generate attributes based on category list"""
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# Sort by order and build description
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sorted_cats = sorted(categories, key=lambda x: x.order if hasattr(x, 'order') else x.get('order', 0))
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category_desc = "\n".join([
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f"- {cat.name if hasattr(cat, 'name') else cat['name']}: {cat.description if hasattr(cat, 'description') else cat.get('description', 'Related attributes' if lang == 'en' else '相關屬性')}"
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for cat in sorted_cats
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])
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category_keys = [cat.name if hasattr(cat, 'name') else cat['name'] for cat in sorted_cats]
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if lang == "en":
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json_template = {cat: ["attribute1", "attribute2", "attribute3"] for cat in category_keys}
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return f"""/no_think
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Analyze "{query}" and list attributes for the following categories. List 3-5 common attributes for each category.
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[Category List]
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{category_desc}
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Return JSON only:
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{json.dumps(json_template, ensure_ascii=False, indent=2)}
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Object: {query}"""
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else:
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json_template = {cat: ["屬性1", "屬性2", "屬性3"] for cat in category_keys}
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return f"""/no_think
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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。
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【類別列表】
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{category_desc}
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只回傳 JSON：
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{json.dumps(json_template, ensure_ascii=False, indent=2)}
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物件：{query}"""
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def get_step2_dynamic_causal_chain_prompt(
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query: str,
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categories: List, # List[CategoryDefinition]
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attributes_by_category: Dict[str, List[str]],
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existing_chains: List[Dict[str, str]],
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chain_index: int,
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lang: LanguageType = "zh"
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) -> str:
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"""Dynamic Step 2 - Generate causal chains for dynamic categories"""
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sorted_cats = sorted(categories, key=lambda x: x.order if hasattr(x, 'order') else x.get('order', 0))
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# Build available attributes
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available_attrs = "\n".join([
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f"[{cat.name if hasattr(cat, 'name') else cat['name']}] {', '.join(attributes_by_category.get(cat.name if hasattr(cat, 'name') else cat['name'], []))}"
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for cat in sorted_cats
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])
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if lang == "en":
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# Already generated causal chains
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existing_text = ""
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if existing_chains:
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chains_list = [
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" → ".join([chain.get(cat.name if hasattr(cat, 'name') else cat['name'], '?') for cat in sorted_cats])
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for chain in existing_chains
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]
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existing_text = "\n[Already generated, do not repeat]\n" + "\n".join([f"- {c}" for c in chains_list])
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# JSON template
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json_template = {cat.name if hasattr(cat, 'name') else cat['name']: f"selected {cat.name if hasattr(cat, 'name') else cat['name']}" for cat in sorted_cats}
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return f"""/no_think
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Generate causal chain #{chain_index} for "{query}".
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[Available Attributes]
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{available_attrs}
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{existing_text}
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[Rules]
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1. Select one attribute from each category
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2. Causal relationships must be logical
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3. Do not repeat
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Return JSON only:
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{json.dumps(json_template, ensure_ascii=False, indent=2)}"""
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else:
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# 已生成的因果鏈
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existing_text = ""
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if existing_chains:
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chains_list = [
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" → ".join([chain.get(cat.name if hasattr(cat, 'name') else cat['name'], '?') for cat in sorted_cats])
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for chain in existing_chains
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]
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existing_text = "\n【已生成，請勿重複】\n" + "\n".join([f"- {c}" for c in chains_list])
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# JSON 模板
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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}
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return f"""/no_think
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為「{query}」生成第 {chain_index} 條因果鏈。
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【可選屬性】
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{available_attrs}
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{existing_text}
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【規則】
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1. 從每個類別選擇一個屬性
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2. 因果關係必須合理
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3. 不要重複
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只回傳 JSON：
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{json.dumps(json_template, ensure_ascii=False, indent=2)}"""
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# ===== DAG relationship prompt =====
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def get_step2_dag_relationships_prompt(
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query: str,
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categories: List, # List[CategoryDefinition]
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attributes_by_category: Dict[str, List[str]],
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lang: LanguageType = "zh"
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) -> str:
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"""Generate natural relationships between adjacent categories"""
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sorted_cats = sorted(categories, key=lambda x: x.order if hasattr(x, 'order') else x.get('order', 0))
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# Build attribute listing
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attr_listing = "\n".join([
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f"[{cat.name if hasattr(cat, 'name') else cat['name']}] {', '.join(attributes_by_category.get(cat.name if hasattr(cat, 'name') else cat['name'], []))}"
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for cat in sorted_cats
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])
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# Build direction hints
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direction_hints = " → ".join([cat.name if hasattr(cat, 'name') else cat['name'] for cat in sorted_cats])
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if lang == "en":
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return f"""/no_think
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Analyze the attribute relationships of "{query}".
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{attr_listing}
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[Relationship Direction] {direction_hints}
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[Rules]
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1. Only establish relationships between adjacent categories (e.g., Materials→Functions, Functions→Usages)
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2. Only output pairs that have true causal or associative relationships
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3. An attribute can connect to multiple downstream attributes, or none at all
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4. Not every attribute needs to have connections
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5. Relationships should be reasonable and meaningful
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Return JSON:
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{{
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"relationships": [
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{{"source_category": "CategoryA", "source": "attribute name", "target_category": "CategoryB", "target": "attribute name"}},
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...
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]
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}}
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Return JSON only."""
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else:
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return f"""/no_think
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分析「{query}」的屬性關係。
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{attr_listing}
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【關係方向】{direction_hints}
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【規則】
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1. 只建立相鄰類別之間的關係（例如：材料→功能，功能→用途）
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2. 只輸出真正有因果或關聯關係的配對
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3. 一個屬性可連接多個下游屬性，也可以不連接任何屬性
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4. 不需要每個屬性都有連接
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5. 關係應該合理且有意義
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回傳 JSON：
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{{
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"relationships": [
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{{"source_category": "類別A", "source": "屬性名", "target_category": "類別B", "target": "屬性名"}},
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...
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]
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}}
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只回傳 JSON。"""
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