gbanyan
91f7f41bc1
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>
101 lines
2.4 KiB
Python
101 lines
2.4 KiB
Python
from pydantic import BaseModel
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from typing import Optional, List, Dict
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from enum import Enum
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class AttributeNode(BaseModel):
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name: str
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category: Optional[str] = None # 材料, 功能, 用途, 使用族群
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children: Optional[List["AttributeNode"]] = None
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AttributeNode.model_rebuild()
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class AnalyzeRequest(BaseModel):
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query: str
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model: Optional[str] = None
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temperature: Optional[float] = 0.7
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categories: Optional[List[str]] = None # 如果為 None，使用預設類別
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class AnalyzeResponse(BaseModel):
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query: str
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attributes: AttributeNode
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class ModelListResponse(BaseModel):
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models: List[str]
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# ===== Multi-step streaming schemas =====
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class Step1Result(BaseModel):
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"""Step 1 的結果：各類別屬性列表"""
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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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class CausalChain(BaseModel):
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"""單條因果鏈"""
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material: str
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function: str
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usage: str
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user: str
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class StreamAnalyzeRequest(BaseModel):
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"""多步驟分析請求（更新為支持動態類別）"""
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query: str
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model: Optional[str] = None
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temperature: Optional[float] = 0.7
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chain_count: int = 5 # 用戶可設定要生成多少條因果鏈
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# 新增：動態類別支持
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category_mode: Optional[str] = "dynamic_auto" # CategoryMode enum 值
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custom_categories: Optional[List[str]] = None
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suggested_category_count: int = 3 # 建議 LLM 生成的類別數量
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class StreamAnalyzeResponse(BaseModel):
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"""最終完整結果"""
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query: str
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step1_result: Step1Result
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causal_chains: List[CausalChain]
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attributes: AttributeNode
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# ===== Dynamic category system schemas =====
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class CategoryMode(str, Enum):
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"""類別模式"""
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FIXED_ONLY = "fixed_only"
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FIXED_PLUS_CUSTOM = "fixed_plus_custom"
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CUSTOM_ONLY = "custom_only"
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DYNAMIC_AUTO = "dynamic_auto"
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class CategoryDefinition(BaseModel):
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"""類別定義"""
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name: str
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description: Optional[str] = None
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is_fixed: bool = True # LLM 生成的為 False
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order: int = 0
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class Step0Result(BaseModel):
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"""Step 0: LLM 分析建議類別"""
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categories: List[CategoryDefinition]
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class DynamicStep1Result(BaseModel):
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"""動態版本的 Step 1 結果"""
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attributes: Dict[str, List[str]] # {類別名: [屬性列表]}
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class DynamicCausalChain(BaseModel):
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"""動態版本的因果鏈"""
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chain: Dict[str, str] # {類別名: 選中屬性}
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