- Add curated occupations seed files (210 entries in zh/en) with specific domains - Add DBpedia occupations data (2164 entries) for external source option - Refactor expert_source_service to read from local JSON files - Improve keyword generation prompts to leverage expert domain context - Add architecture analysis documentation (ARCHITECTURE_ANALYSIS.md) - Fix expert source selection bug (proper handling of empty custom_experts) - Update frontend to support curated/dbpedia/wikidata expert sources Key changes: - backend/app/data/: Local occupation data files - backend/app/services/expert_source_service.py: Simplified local file reading - backend/app/prompts/expert_transformation_prompt.py: Better domain-aware prompts - Removed expert_cache.py (no longer needed with local files) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
202 lines
5.9 KiB
Python
202 lines
5.9 KiB
Python
"""Expert 本地資料來源服務
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從本地 JSON 檔案讀取職業資料,提供隨機選取功能。
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"""
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import json
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import logging
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import random
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from pathlib import Path
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from typing import List, Tuple
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logger = logging.getLogger(__name__)
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# 資料目錄
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DATA_DIR = Path(__file__).parent.parent / "data"
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class LocalDataProvider:
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"""從本地 JSON 檔案讀取職業資料"""
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def __init__(self, source: str):
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"""
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Args:
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source: 資料來源名稱 (dbpedia/wikidata)
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"""
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self.source = source
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self._cache: dict = {} # 記憶體快取
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def load_occupations(self, language: str = "en") -> List[dict]:
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"""
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載入職業資料
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Args:
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language: 語言代碼 (en/zh)
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Returns:
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職業列表 [{"name": "...", "domain": "..."}, ...]
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"""
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cache_key = f"{self.source}:{language}"
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# 檢查記憶體快取
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if cache_key in self._cache:
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return self._cache[cache_key]
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# 讀取檔案
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file_path = DATA_DIR / f"{self.source}_occupations_{language}.json"
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if not file_path.exists():
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logger.warning(f"資料檔案不存在: {file_path}")
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return []
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try:
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with open(file_path, "r", encoding="utf-8") as f:
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data = json.load(f)
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occupations = data.get("occupations", [])
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logger.info(f"載入 {len(occupations)} 筆 {self.source} {language} 職業")
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# 存入快取
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self._cache[cache_key] = occupations
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return occupations
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except Exception as e:
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logger.error(f"讀取職業資料失敗: {e}")
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return []
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def random_select(self, count: int, language: str = "en") -> List[dict]:
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"""
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隨機選取指定數量的職業
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Args:
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count: 需要的數量
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language: 語言代碼
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Returns:
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隨機選取的職業列表
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"""
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all_occupations = self.load_occupations(language)
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if not all_occupations:
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return []
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if len(all_occupations) <= count:
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return all_occupations
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return random.sample(all_occupations, count)
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class ExpertSourceService:
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"""統一的專家來源服務"""
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def __init__(self):
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self.curated = LocalDataProvider("curated") # 精選職業
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self.dbpedia = LocalDataProvider("dbpedia")
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self.wikidata = LocalDataProvider("wikidata")
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def get_experts(
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self,
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source: str,
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count: int,
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language: str = "en",
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fallback_to_llm: bool = True
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) -> Tuple[List[dict], str]:
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"""
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從指定來源獲取專家資料
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Args:
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source: 來源類型 ("dbpedia" | "wikidata")
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count: 需要的專家數量
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language: 語言代碼
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fallback_to_llm: 失敗時是否允許 fallback(由呼叫者處理)
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Returns:
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(專家資料列表, 實際使用的來源)
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Raises:
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ValueError: 當獲取失敗且資料為空時
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"""
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# 選擇 provider
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if source == "curated":
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provider = self.curated
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# 精選職業支援 zh 和 en,預設使用 zh
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if language not in ["zh", "en"]:
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language = "zh"
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elif source == "wikidata":
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provider = self.wikidata
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else:
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# 預設使用 dbpedia
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provider = self.dbpedia
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source = "dbpedia"
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experts = provider.random_select(count, language)
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if not experts:
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raise ValueError(f"No occupations found from {source} ({language})")
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logger.info(f"從 {source} 取得 {len(experts)} 位專家")
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return experts, source
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def get_available_sources(self) -> List[dict]:
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"""
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取得可用的資料來源資訊
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Returns:
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來源資訊列表
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"""
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sources = []
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# 檢查精選職業(中文)
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curated_zh = DATA_DIR / "curated_occupations_zh.json"
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if curated_zh.exists():
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with open(curated_zh, "r", encoding="utf-8") as f:
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data = json.load(f)
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sources.append({
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"source": "curated",
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"language": "zh",
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"count": data["metadata"]["total_count"],
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"created_at": data["metadata"]["created_at"]
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})
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# 檢查精選職業(英文)
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curated_en = DATA_DIR / "curated_occupations_en.json"
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if curated_en.exists():
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with open(curated_en, "r", encoding="utf-8") as f:
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data = json.load(f)
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sources.append({
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"source": "curated",
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"language": "en",
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"count": data["metadata"]["total_count"],
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"created_at": data["metadata"]["created_at"]
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})
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# 檢查 DBpedia
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dbpedia_en = DATA_DIR / "dbpedia_occupations_en.json"
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if dbpedia_en.exists():
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with open(dbpedia_en, "r", encoding="utf-8") as f:
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data = json.load(f)
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sources.append({
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"source": "dbpedia",
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"language": "en",
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"count": data["metadata"]["total_count"],
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"fetched_at": data["metadata"]["fetched_at"]
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})
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# 檢查 Wikidata
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wikidata_zh = DATA_DIR / "wikidata_occupations_zh.json"
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if wikidata_zh.exists():
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with open(wikidata_zh, "r", encoding="utf-8") as f:
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data = json.load(f)
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sources.append({
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"source": "wikidata",
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"language": "zh",
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"count": data["metadata"]["total_count"],
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"fetched_at": data["metadata"]["fetched_at"]
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})
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return sources
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# 全域服務實例
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expert_source_service = ExpertSourceService()
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